Don't Panic! It's Just Data (EM360Tech)

It's episode 2 of this fantastic 12 part series with Cloudera.

In this podcast, Scott Taylor speaks to Abhas Ricky, Managing Director, Global Head – Strategy & Transformation at Cloudera. Abhas starts by talking about why people implement the cloud and how enterprises can have a better understanding of the costs involved. Secondly, he explains how organisations should define their total cost of ownership model. Also, Abhas explains how ephemeral workloads can be beneficial and the differences between analytical and operational workloads. Finally, he outlines where the complications and nuances come in around the cost of data and analytics.

Next week's episode: Critical Technology Decisions for Cloud

Make sure you're subscribed so that you don't miss an episode of this fantastic series.

Rainfall. Temperature. Humidity. Natural disasters. Human methods of reading and predicting weather can be tracked all the way back to native tribes and ancient civilisations - and it’s still prevalent in the modern world today. 

Whether (no pun intended) it’s an agricultural organisation looking to leverage precipitation data for planting schedules, energy companies looking at temperature trends to predict energy consumption patterns or transportation outfits looking to avoid delays, mastering weather data can really help modern companies to protect themselves against the unknown. 

In this episode of the EM360 Podcast, Analyst Susan Walsh speaks to Christian Schluchter, CTO at Meteomatics, to discuss: 

• Key use cases of weather data
• Mastering data access and predictive analytics
• The importance of being data driven

The data analysis landscape is on the precipice of a paradigm shift. Generative AI (GenAI) promises revolutionary insights, but traditional systems struggle to feed its insatiable appetite for well-structured data. Imagine GenAI as a high-powered engine – it needs meticulously organised fuel to reach its full potential.

In this episode of the EM360 Podcast, Analyst Christina Stathopoulos guides Deborah Leff (CRO at SQream) and Jason Hardy (CTO, AI at Hitachi Vantara) as they dissect:

• The Bottlenecks of Traditional Systems
• Unlocking GPU Potential
• Fueling Insights with Structured Data
• Faster Time to Insights

This episode goes beyond theory, exploring real-world examples (like a company querying a staggering 64 quadrillion rows) It showcases the potential for SQream and Hitachi Vantara to empower organisations to make data-driven decisions with unprecedented speed and accuracy.

Data provenance is essential for maintaining trust and integrity in data management. It involves tracking the origin of data and understanding how it has been processed and handled over time. By focusing on fundamental principles such as identity, timestamps, and the content of the data, organisations can ensure that their data remains accurate, consistent, and reliable.

Implementing data provenance does not require significant changes or large investments. Existing technologies and techniques can be seamlessly integrated to provide greater transparency and control over data. With data provenance, businesses can confidently manage their data, enhancing decision-making and fostering stakeholder trust.

In this episode, Jon Geater, Co-Chair of the Supply Chain Integrity Transparency and Trust (SCITT) Working Group, speaks to Paulina Rios Maya, Head of Industry Relations, about data provenance. 

Key Takeaways: 

• Data provenance is knowing where data comes from and how it has been handled, ensuring trust and integrity.
• The fundamental principles of data provenance include identity, timestamps, and the content of the data.
• Data provenance can be implemented by integrating existing technologies and techniques without significant changes or investments.
• Data provenance helps with compliance, such as GDPR, by providing a transparent record of data handling and demonstrating compliance with requests.

Chapters: 

00:00 - Introduction and Background

02:01 - Understanding Data Provenance

05:47 - Implementing Data Provenance

10:01 - Data Provenance and Compliance

13:50 - Success Stories and Industry Applications

18:10 - Conclusion and Call to Action

Summary

This discussion explores the complexities and strategies surrounding edge computing and data management, highlighting the importance of security, the challenges of vendor lock-in, the implications of data repatriation, and the necessity of ensuring high-quality data for AI systems. It emphasises the need for organisations to balance edge processing with centralised storage while future-proofing their data strategies against rapid technological changes.

Building on their discussion, Jimmy Tam highlights the transformative role of edge computing in modern data management, emphasising the importance of governance, compliance, and interoperability to address the challenges of data sprawl and vendor lock-in.

Takeaways

• Edge computing is transforming how organisations manage data.
• Security at the edge is paramount to prevent intrusions.
• Data sprawl poses significant challenges for edge data management.
• Governance and compliance are essential for effective data management.
• Vendor lock-in can limit flexibility and adaptability in technology.
• Data interoperability is crucial for avoiding vendor lock-in.
• Data repatriation is a growing trend among organisations.
• AI systems require access to comprehensive data for training.
• Speed of data relevance is critical for effective AI applications.
• Flexibility in data strategies is essential for future-proofing organisations.

Sound Bites

"Data sprawl is a significant problem."

"Governance and compliance are crucial."

"Data repatriation is absolutely real."

"Speed of data relevance is critical."

Chapters

00:00 Introduction to Edge Computing and Data Management

02:53 Security Strategies for Edge Data

06:06 Vendor Lock-In and Data Interoperability

09:00 Data Repatriation and Cost Optimisation

11:57 Ensuring Quality Data for AI Systems

14:46 Balancing Edge Processing and Centralised Storage

17:59 Future-Proofing Data Strategies

Across organisations, we see a drive for next-generation systems as organisations require more scalability and flexibility. With these demands comes the need for a change in architecture so that businesses can help develop the next generation of systems and move from traditional relational databases to NoSQL databases. In this podcast, Ronald van Loon speaks to Dr Mohammed Haji, Manager - EMEA North Solutions Engineering at Couchbase and Mritunjay Singh, Principal Solution Architect at BT to understand how NoSQL can transform enterprise application.

Firstly, they discuss NoSQL integration for supporting cloud-native applications, and the key role NoSQL plays in new stack technology. Then they consider how enterprise are using NoSQL to improve data performance and using it to support emerging trends. Also, Mritunjay and Mohammed review how data is categorised compared to SQL and the effect this has on scaling. Finally, they explore what organisations need to focus on when adopting a NoSQL solution to optimise the end result.

Spatial data, also known as geospatial data, affects our everyday lives.

A term used to describe data related to locations on Earth’s surface, spatial data can be used in everything from heat maps and political maps to smaller-scale indoor representations like in hospitals and offices. 

In this episode of the EM360 Podcast, Analyst John Santaferraro speaks to Todd Lewis, Founder and CEO of Spatial DNA, to discuss:

• Digital revolution and the challenges it’s produced
• Helping customers overcome complexity 
• The future of spatial data

Spatial DNA is a partner of Safe Software.

Data democratisation is the continuous process of enabling company-wide access to data, regardless of technical know-how, in a bid to spread a data-led decision-making mindset across all departments of an organisation.

It can be a big challenge - and serious investment - for companies as employee education and tool implementation is not trivial undertakings.

How can companies set up their data democratisation strategy?

In this episode of the EM360 podcast, Content Producer Matt Harris talks to Giuseppe Mura, Director of Solution Engineering at StreamSets, as they tackle:

• The steps companies should utilise to set up their data democratisation strategy
• How the demand for DataOps will be affected as businesses adapt their data integration processes
• Bringing in non-IT-native and non-DevOps experts and providing them with everything they need

While organisations are gradually becoming more data-driven, there are still organisations that rely solely on instinct. According to Talend's 2021 Data Health Survey, a whopping 36% of executives are still making gut based decisions, a method which has proved time and time again to be both inefficient and unpredictable. One of the contributing factors to gut based decision making is a lack of trust in data. Data quality varies from industry to industry but within single organisations, it can also vary from person to person. In fact, 38% of data users state that there are no data quality standards in place in their organisation, so why would executives trust data to make decisions?

The key to becoming data-driven means ensuring that everyone, from the data-producer to the data-user, is involved in the data lifecycle. This means decentralising data processes to ensure that every member of the team both has a transparent understanding of how data is being used but also feels equally involved in the process. In this episode of Data Transforming Business, we speak to Antony Elliott, Regional VP of Enterprise Sales for EMEA North, Talend about the best ways to maintain healthy data in data-driven organisations.

In this podcast, Scott Taylor, Principal Consultant at MetaMeta Consulting, is joined by Robert Hodges, CEO at Altinity, to discuss ClickHouse, the first open-source, SQL data warehouse that competes with the major DBMS players. Over the course of the conversation, they look at:

• The history and background of ClickHouse
• Benefits of open source from a data perspective
• Management perspectives of the data journey
• Applying ClickHouse across small to large organisations

Instant analytics and reporting culminate in the new open-source, column-oriented DBMS, ClickHouse. The system has grown to be one of the most popular database projects, with thousands of users generating analytical reports via real-time SQL queries since it publicly launched in 2016 following an 8 year internal testing period with Yandex. When faced with trillions of rows of data and the need to filter, explore, and interact with it, ClickHouse is the solution for businesses.

Data custodianship today involves managing and protecting vast quantities of sensitive information, requiring organisations to ensure security, regulatory compliance, and ethical usage. It’s not just about protecting data from breaches but also about responsible storage, access, and deletion that aligns with strict industry standards and evolving privacy regulations.

The ethical dimensions of data custodianship add further complexity as organisations balance the need for data-driven insights with privacy rights and transparent usage. Mismanagement can lead to significant financial, legal, and reputational risks, making effective custodianship essential for maintaining customer trust and regulatory compliance.

In this episode, Paulina Rios Maya, Head of Industry Relations, speaks to Debbie Reynolds, Founder and Chief Data Privacy Officer at Debbie Reynolds Consulting, about compliance with global regulations, the role of AI in data management, and the necessity of human oversight in technology.

Key Takeaways: 

• Data custodianship emphasises that data belongs to individuals, not companies.
• Organisations must have a comprehensive plan for data management throughout its lifecycle.
• Transparency and communication with consumers are essential in data handling.
• Different types of data require different levels of protection based on risk.
• Building trust with consumers requires responsible data practices.
• Organisations need to prioritise basic data protection strategies over compliance with every regulation.

Chapters: 

00:00 - Introduction to Data Custodianship

03:03 - Understanding Responsibilities in Data Handling

05:59 - Balancing Innovation and Data Protection

08:45 - Building Trust Through Responsible Data Practices

12:07 - Navigating Compliance and Data Governance

14:54 - Leveraging AI for Enhanced Data Custodianship

18:06 - The Role of Humans in Technology and Data Management

Organisations who are in the early stages of data analytic maturity struggle with poor data quality, inconsistent processes and lack of co-ordination across their organisation. Also, those organisations with low BI maturity don’t have formal governance programs in place at all. These low maturity organisations often have BI platforms that are more traditional and reporting centric. In this podcast, Ronald van Loon speaks to Ed Thompson, CTO at Matillion about how an organisation can achieve data and analytics maturity.

Firstly, Ed outlines a typical customer experience and how you define data milestone along with the tools needed to start a data journey. Then he explains the challenges of data integration and how businesses maintain data governance over such large amounts of data. Finally, we learn about suitable cloud strategies as well as how to prepare teams to be ready for data, analytics and machine learning.

Data powers the cogs of every business today and nearly every company wants to transform through the help of it. In a nutshell, data has become a true 'asset' to the modern enterprise, especially in respect of how data analysis can be used to inform and drive business decisions.

How Data Analysis Can Inform Business Decisions

Joining Scott Taylor, Principal Consultant at MetaMeta Consulting, to unpick and analyse this further is Philip Dutton, Co-CEO and Co-Founder of Solidatus, and Wade Munsie, Global Chief Data Officer at GSK Consumer Healthcare. Philip and Wade share their thoughts on the realism of what goes into making data an asset, data-led decision-making, and the purpose of the CDO. The pair answer key business questions such as: how should companies begin their data transformation journeys and manage their assets effectively? How should a business approach the purpose of the CDO from an investment and governance standpoint? And, how should we deal with data quality? Additional topics of discussion include data ecosystem sustainability and setting up a CDO from scratch.

Web data extraction. The ability to transform any website into structured data.

Using a residential proxy network, companies have been able to fine-tune their data collection for a range of use cases - from threat intelligence and email protection to ad verification and market research. 

But why do companies need this now? How do the different stacks of data extraction work and how can you make sure which one works best for you? And how is AI being used in this technology to reach industry-leading scalability and reliability?

In today’s episode of the EM360 Podcast, Head of Content Matt Harris speaks to Eitan Bremler, VP of Products at NetNut, to discuss:

• Data extraction and why its a problem for companies
• The different stacks of data extraction
• How AI/ML should fit in to your data strategy

As cloud adoption grows, so do the challenges of managing costs effectively. Cloud environments offer scalability and flexibility but often come with hidden fees, unpredictable expenses, and resource sprawl that can quickly inflate budgets. Without the right tools and strategies, businesses may struggle to track spending, identify waste, and maintain budget alignment. 

Usage-based reporting is pivotal in this process, providing the granular visibility needed to understand real-time consumption patterns and optimise costs. Businesses can align expenses directly with value-driven activities by tracking how, where, and when resources are used. From preventing overspending to fostering accountability, usage-based reporting empowers teams to proactively manage their cloud expenses, turning cloud cost management into a strategic advantage rather than a recurring headache.

In this episode, George Firican, Founder of LightsOnData, speaks to Rem Baumann, Resident FinOps Expert at Vantage, about usage-based reporting and its benefits. 

Key Takeaways: 

• Organisations face challenges in tracking complex cloud costs.
• Usage-based reporting provides context to cloud spending.
• Metrics should align with business goals for effective decision-making.
• Communication between finance and engineering teams is crucial.
• Identifying cost optimisation opportunities can lead to significant savings.
• Different industries require customised cost metrics.
• Cloud providers offer basic tools, but deeper insights are needed.
• Regular monitoring of metrics ensures financial transparency.

Chapters: 

00:00 - Introduction to Cloud Cost Management

03:03 - Understanding Cloud Complexity and Cost Tracking

05:53 - The Role of Usage-Based Reporting

09:06 - Metrics for Cost Optimization

12:02 - Industry-Specific Applications of Cost Metrics

14:49 - Aligning Cloud Costs with Business Goals

18:09 - Conclusion and Key Takeaways

Today’s episode explores the ways that AI is reshaping how organisations do business in this digital economy. In particular, the discussion focuses on what it means for the future and the million dollar question: will AI replace human beings? Spencer Doyle, Chief Business Developer at Noodle.ai, joins us to give his perspective on AI in the industry.

For information regarding your data privacy, visit acast.com/privacy

Sustainable sourcing is essential for businesses committed to environmental and social responsibility, but achieving it requires accurate and reliable data. Master Data Management (MDM) ensures that all sourcing data—such as supplier information, certifications, and compliance records—is consistent and up-to-date. This enables organisations to make informed decisions that align with their sustainability goals, reduce waste, and promote ethical practices throughout their supply chain.

MDM is the foundation of a successful sustainability strategy. By providing a single source of truth for all critical data, MDM helps businesses monitor and track their sustainability efforts effectively. With accurate data, companies can identify opportunities to improve resource efficiency, reduce carbon footprints, and ensure compliance with environmental standards, ultimately leading to a more sustainable and resilient business model.

In this episode, George Firican, Founder of LightsOnData, speaks to Matthew Cawsey, Director of Product Marketing and Solution Strategy, and Paarijat Bose, Customer Success Manager at Stibo Systems, to discuss sustainable sourcing and why accurate data matters. 

Key Takeaways:

• Sustainable sourcing involves understanding the provenance and environmental impact of products, ensuring compliance with regulations, and meeting sustainability goals.
• Data completeness and accuracy are crucial in meeting regulatory requirements and avoiding issues like greenwashing.
• Managing sustainability data requires a solid foundation of MDM to ensure data accuracy, stewardship, and semantic consistency.
• MDM solutions help companies collect, manage, and share sustainability data, enabling them to meet compliance requirements and achieve their sustainability goals.

Chapters:

00:00 - Introduction and Overview

01:07 - The Challenge of Collecting Data for Compliance and Reporting

02:31 - Data Accuracy and Completeness in the Supply Chain

05:23 - Regulations and the Demand for Transparent and Complete Data

08:41 - The Role of Master Data Management in Sustainability

15:51 - How Data Management Technology Solutions Help Achieve Sustainability Goals

21:02 - The Need to Start Early and Engage with Data Management Solutions

22:01 - Conclusion and Call to Action

Artificial intelligence. The catch-all term defines the machines that can mimic and display sentient cognitive skills such as learning and problem-solving. A key part of modern technology, the advancements of AI indicate just how far the human race has come.

AI can be used by businesses to interpret and use massive volumes of data.

In this third episode of a three-part EM360 podcast series with Findability Sciences, Data Whisperer and Analytics Expert, Christina Stathopoulos speaks to the company’s Founder and CEO Anand Mahurkar, as the pair explore:

• Getting the most out of wide data
• Bringing the power of AI to traditional automation solutions
• Calculating ROI for AI projects

Data management is essential for retailers to manage their data effectively to gain valuable insights into customer behavior, preferences, and purchase patterns. By doing so, retailers can make data-driven decisions and improve their operations, sales, and marketing strategies.

However, managing data can be challenging for retailers due to the volume, variety, and velocity of data generated by multiple sources, such as social media, mobile devices, and online platforms. 

Retailers must also comply with data privacy regulations and ensure the security of their customers' personal information. Additionally, they need to invest in advanced technology and skilled personnel to manage data effectively.

In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Ramesh Shurma, Founder and CEO at Orion Governance, to discuss:

• Major data challenges faced by retailers
• Protecting data assets in the face of recession
• Governance predictions for the next five years

As data continues becoming a core part of how businesses operate and make decisions, managing data quality has never been so important. 

Poor data quality can hit all enterprise levels hard, from marketers annoying prospects to supply chains becoming unable to automate processes properly.

In this second episode of the three-part EM360 Podcast series with Anomalo on data quality, Elliot Shmukler, Co-Founder and CEO at Anomalo joins Analyst Christina Stathopoulos to discuss:

• The right time for data quality monitoring
• What happens if you wait too long
• Who should be involved

This episode marks our halfway point through our 12 part series with Cloudera.

In this podcast, Jeff Fletcher, Senior Director of Product Management at Cloudera, explains why we need to rethink how we operationalise ML within the enterprise. Jeff starts by talking about what technology types apply to ML and what people should keep in mind about the operational side when testing. Also, he outlines the boundaries of machine learning, AutoML, and artificial intelligence and how cloud fits into this process. Finally, Jeff explains the importance of feeding and caring for how the data is trained.

Next week's episode: Hybrid Cloud and the Power of Yes

Make sure you're subscribed so that you don't miss an episode of this fantastic series.

Augmented intelligence is driving the well-overdue reevaluation of data models. Michel Morvan at Cosmo Tech and Robert Plana at Assystem join us on this podcast to talk with us about augmented intelligence, as well as Cosmo Tech’s role in it. 

Having a 360-degree view of your business means having a comprehensive and holistic understanding of every aspect of your organisation. 

It involves collecting and integrating data from various sources and departments to create a unified, real-time view. This panoramic perspective enables businesses to make informed decisions, identify opportunities, and address challenges across the entire enterprise.

In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Prash Chandramohan, Senior Director of Product Marketing at Informatica. They discuss:

• Having a 360-degree view of your business
• Driving great customer experiences
• Is your data ready for AI?

Today’s business intelligence groups can take advantage of Octopai’s automated centralised cross-platform metadata search engine. This allows such groups to quickly discover and also govern shared metadata. While metadata management is nothing new, new methodologies are transforming the effect it can have on business success. Joining us in this episode to talk about Octopai’s platform and optimising metadata is Amnon Drori, CEO and Co-Founder of the company.

"There's been a lot of wrangling of data, a lot of wrangling of humans as well, which is a big theme for today," says Warwick Leitch, Product Management Director at insightsoftware.

In this episode of the 'Don't Panic, It's Just Data' podcast, Debbie Reynolds, CEO and Chief Data Privacy Officer at Debbie Reynolds Consulting LLC, speaks with Leitch from insightsoftware. They discuss the vital role of financial strategy and collaborative planning, particularly as it pertains to the decisions made by IT executives.

The question they address is: In a world awash with data, how do we transform it into actionable insights? Warwick shares his wealth of experience, offering practical advice and illuminating the path to successful budgeting and forecasting.

One such challenge addressed in the podcast is how organisations are securing executive buy-in. "And 51 percent of people find it difficult to engage senior executives to buy into the process, which is a roadblock. And 57 percent of organisations struggle cross-functionally," Warwick reveals. 

It's not just about the numbers. Warwick also emphasises the human element, reminding us that "Without people, we don't have anything." In an era where AI looms large, it's crucial to remember that technology serves to enhance, not replace, human collaboration.

Tune in to the podcast and learn how to navigate the complexities of financial strategy and collaborative planning.

Takeaways

• Executive buy-in is crucial for successful budgeting.
• A clear vision helps guide the budgeting process.
• Thoughtful execution is key to effective planning.
• Fostering a culture of collaboration enhances participation.
• Data accuracy is vital in today's fast-paced environment.
• Avoid overcomplicating the budgeting process.
• Gamification can improve engagement in budgeting.
• AI can significantly streamline forecasting and reporting.
• Regularly updating forecasts leads to better accuracy.
• Understanding business measures is essential for effective planning.

Chapters

00:00 Introduction to Collaborative Financial Planning

05:01 The Importance of Executive Buy-In

10:09 Thoughtful Execution in Budgeting

15:01 Fostering a Culture of Collaboration

19:48 Defining Business Measures and Data Accuracy

24:52 Common Pitfalls in Collaborative Budgeting

29:52 The Future of Collaborative Planning with AI

What is the relationship between product content and customer experience?

A symbiotic one, say experts, but what technologies need to be implemented and how can companies bring in new tools to eliminate their digital debt?

In this episode of the EM360 Podcast, Analyst George Firican speaks to Derek Corrick, GM of Data at Pivotree and Justin Anovick, Chief Product Officer at Syndigo, to discuss:

• The relationship between product content and CX
• Leveraging AI/ML and how that impacts clients
• Best practices for solid content strategy

Data governance in the modern world is the managing, utilising and securing of data in enterprise systems, and it’s becoming increasingly more important as organisations face new data privacy regulations as well as the need to make data-driven decisions.

Well-designed data governance programs often include governance teams, steering committees and data stewards. But behind these lie data standards, policies and philosophies that can help businesses handle astounding amounts of data in the right way.

In this episode of the EM360 Podcast, Analyst Christina Stathopoulos speaks to Ramesh Shurma, Founder and CEO at Orion Governance, to discuss:

Current data governance space

Bottom-up vs top-down approaches

Lowering TCO and increasing ROI

Managing cloud costs effectively has become a significant challenge for organisations relying on public cloud services. FinOps addresses these challenges by ensuring efficient spending and governance of cloud resources. Key practices in FinOps include achieving complete visibility into cloud usage and costs, fostering cross-functional collaboration between finance, operations, and engineering teams, and utilising data-driven decision-making to optimise cloud investments. 

By embracing a centralised team, organisations can instil a culture of governance and efficiency in cloud cost management. This approach can lead to enhanced resource utilisation and substantial cost savings. With Vantage, your organisation can cultivate a robust cloud cost governance and efficiency culture, ensuring your cloud investments yield maximum value.

In this episode of the EM360 Podcast, Kevin Petrie, VP of research at BARC US, speaks to Ben Schaechter, CEO and co-founder of Vantage, to discuss: 

• FinOps
• Vantage’s platform 
• Cloud costs and FinOps practices

Chapters

00:00 - Introduction and Overview

02:02 - Understanding FinOps and Cloud Cost Governance

07:45 - Best Practices in FinOps: Centralization and Collaboration

13:50 - The Role of Data-Driven Insights in Optimizing Cloud Costs

Cloud modernization transforms organizations and enables continuous innovation.

A cloud modernization program accelerates your analytics initiatives to gain the agility, speed, and scale needed to drive business value and deliver a competitive advantage. Informatica has enabled many leading customers to move their on-premises workloads to the cloud seamlessly and to innovate at scale. Learn how Informatica’s Cloud Modernization Program has allowed customers to streamline processes, improve data delivery, and accelerate time to insights while reducing migration costs and mitigating risk with minimum disruption to ongoing business operations.

On this episode of the EM360 Podcast, Analyst John Santaferraro speaks to Pratik Parekh, Group Vice President and General Manager of Cloud Modernization at Informatica, to explore:

• Cloud modernization challenges
• Recommended cloud modernization approaches to reduce migration cost, risk, and time 
• How customers accelerated their cloud journey

Episode 5 of our 12 part Cloudera sees a returning guest joining us.

In this podcast, Jan Kunigk, CTO EMEA, returns to discuss what is needed to set apart a modern data warehouse PaaS (platform as a service) in the cloud from the traditional warehouse solutions. Jan explains the benefit that container technology has in a data warehouse and how that impacts the end-users. He also describes how containerisation in a PaaS offering leads to cloud-native flexibility and how organisations can leverage this for multi and hybrid cloud mobility for cloud spend. Finally, he outlines the role of open standards to truly facilitate the mobility of queries, data, and metadata that enterprises demand from their warehouse solution.

Next week's episode: Machine Learning - Take Risks and Fail

Make sure you're subscribed so that you don't miss an episode of this fantastic series.

Deep learning is a subgenre of machine learning and AI that mimics human behaviour - lending itself to predictive modelling and statistics. 

But how can we take the power of deep learning and make it more accessible to the citizen data scientist?

In this episode of the EM360 Podcast, Analyst Christina Stathopoulos speaks to Richard Heyns, Founder and CEO of Brytlyt, about:

• Deep learning and artificial neural network systems
• DL vs ML
• Embedding AI into the database

Kickstarting our third series of Data Transforming Business, EM360’s David Argent met with Nick Curcuru, formerly at Mastercard, and Matt Maccaux, formerly at Dell EMC, to talk big data. In this episode, our speakers go back to basics, starting by exploring where the term ‘big data’ came from. As well as this, they strip back any confusion surrounding big data and tell us what it means fundamentally.

For information regarding your data privacy, visit acast.com/privacy

Telemetry data pipelines are designed to collect, process and transmit telemetry data from various sources towards a place where businesses can store, analyse and utilise it for better decision-making. 

Important for SREs, DevOps, ITOps, SecOps, DataOps and the wider tech professional, taking control of your telemetry data to address data challenges in a compliant and secure way should be a common goal for the modern business. 

In this episode of the EM360 Podcast, Analyst Kevin Petrie speaks to Tucker Callaway, CEO at Mezmo, to discuss:

• Understanding telemetry data pipelines
• Addressing data challenges with telemetry data
• Optimising performance and enhancing security with telemetry data

Safe Software's Feature Manipulation Engine (FME) plays a pivotal role in the City of Fremont's operations, particularly in ensuring accurate and efficient data submissions under the Racial and Identity Profiling Act (RIPA). By automating complex workflows and enhancing data quality, FME not only ensures seamless compliance with RIPA requirements but also optimises processes for their ITS and GIS divisions.

FME also drives innovation in projects like the DroneSense programme and their Cityworks asset management integration. With seamless data integration and powerful visualisations, FME empowers the City of Fremont to enhance operations, improve asset management, and support informed decision-making.

In this episode, Jonathan Reichental, founder at Human Future, speaks to John Leon, GIS Manager for the City of Fremont, to discuss: 

• FME 
• RIPA
• Public Safety 

Chapters:

00:00 - Introduction and Overview of the City of Fremont and IT/GIS Division

03:01 - Explanation of the Racial and Identity Profiling Act (RIPA)

04:27 - Challenges in Meeting RIPA Standards and Utilizing FME

06:21 - How FME Ensures Error-Free RIPA Data Submissions

09:40 - Benefits of Using FME for RIPA Compliance

10:39 - Other Innovative Projects Utilizing FME in the City of Fremont

13:30 - Future Plans for FME in the City of Fremont

17:17 - Recommendations for Government Agencies: Leverage FME for Data Submissions

A recent 451 Research survey of enterprise users showed that 84% found at least some of their strategic decisions at their organisations are data-driven. Further to this, the survey found that data is becoming increasingly important to organisations. So, how should companies be acting on their data? Here to lend his expertise on the matter is John Walls at Looker. John shares his thoughts on the opportunities related to self-service analytics and how to deliver the benefits without compromising governance or unified metrics.

As organisations strive to stay competitive in the age of AI, data trust has become a critical factor for success. Without it, even the most advanced AI initiatives are bound to fall short.

With the rapid advancement of technology, prioritising trust in data is essential for unlocking AI's full potential and driving meaningful results. Conversely, a lack of data trust can undermine decision-making, operational efficiency, and the success of AI initiatives.

In this episode, Christina Stathopoulos, Founder at Dare to Data, speaks to Jay Limburn, Chief Product Officer at Ataccama, to explore these pressing topics. Together, they share actionable insights, real-world examples, and innovative strategies to help businesses harness the power of trusted data.

Key Takeaways

• Data trust is essential for confident decision-making.
• AI can significantly reduce mundane tasks.
• Organizations must focus on their data strategy.
• Customer experience is a key area for AI application.
• Data teams are crucial for successful AI initiatives.
• Proactive data management is becoming the norm.
• The chief data officer's influence is growing.
• Data quality and security are critical challenges.
• AI can enhance regulatory reporting processes.
• Trust in data is vital for successful AI projects.

Chapters

00:00 - Introduction to Data Trust and AI Integration

09:36 - The Role of AI in Operational Efficiency

12:47 - Balancing Short-term and Long-term Data Priorities

15:00 - Enhancing Customer Experience through AI

19:08 - Aligning Workforce and Culture for AI Success

21:03 - Innovative Strategies for Data Quality and Security

24:35 - Final Thoughts on Data Trust and AI Success

The convergence of Master Data Management (MDM) and Artificial Intelligence (AI) is transforming how businesses harness data to drive innovation and efficiency. MDM provides the foundation by organising, standardising, and maintaining critical business data, ensuring consistency and accuracy across an organisation. 

When paired with AI, this clean and structured data becomes a powerful asset, enabling advanced analytics, predictive insights, and intelligent automation. MDM and AI help businesses uncover hidden patterns, streamline operations, and make more informed decisions in real-time.  

By integrating MDM with AI, organisations can move beyond simply managing data to actively leveraging it for competitive advantage. AI algorithms thrive on high-quality, well-structured data, and MDM ensures just that—minimising errors and redundancies that could compromise results. This synergy empowers companies to personalise customer experiences, optimise supply chains, and respond proactively to market changes. 

In this episode, Kevin Petrie, VP of Research at BARC US, speaks to Jesper Grode, Director of Product Innovation at Stibo Systems, about the intersection between AI and MDM. 

Key Takeaways: 

• AI and master data management should be integrated for better outcomes.
• Master data improves the quality of inputs for AI models.
• Accurate data is crucial for training machine learning models.
• Generative AI can enhance product launch processes.
• Prompt engineering is essential for generating accurate AI responses.
• AI can optimise MDM processes and reduce operational costs.
• Fast prototyping is vital for successful AI implementation.

Chapters: 

00:00 - Introduction to AI and Master Data Management

02:59 - The Synergy Between AI and Master Data

05:49 - Generative AI and Master Data Management

09:12 - Leveraging Master Data for Small Language Models

11:58 - AI's Role in Optimizing Master Data Management

14:53 - Best Practices for Implementing AI in MDM

The San Antonio River Authority (SARA) has experienced a transformative shift in data management, thanks to the powerful capabilities of FME. By integrating FME, SARA has streamlined data integration, improved efficiency, and enhanced decision-making processes across multiple departments. FME’s ability to automate data transformation, standardise formats, and manage large volumes of spatial data has allowed the authority to optimise workflows, reduce manual errors, and accelerate project timelines.

A key highlight of SARA’s success with FME is its use in predictive flood modelling and the standardisation of data workflows. By leveraging FME, SARA can more accurately predict flood risks, improving public safety and response times.

This innovation not only enhances internal operations but also helps SARA lead in sustainable water management. With its versatility in handling diverse data sources and streamlining communication between systems, FME is a powerful investment for organisations seeking to improve operational efficiency and long-term strategic decision-making.

In this episode, Debbie Reynolds, Founder and Chief Data Privacy Officer at Debbie Reynolds Consulting, speaks to Jordan Merson, Enterprise Applications Supervisor at San Antonio River Authority, about the game-changing impact of FME.

Key Takeaways: 

• Data management challenges often stem from a lack of standardisation.
• FME allows for the integration of various data sources seamlessly.
• Predictive modelling can enhance emergency response efforts.
• FME provides tools for real-time data monitoring and alerts.
• The user-friendly interface of FME accelerates onboarding for new team members.
• FME can handle both spatial and non-spatial data effectively.
• Collaboration and knowledge sharing are key to successful data management.

Chapters: 

00:00 - Introduction to Data Management and FME

02:30 - Jordan's Journey in IT and Data Management

05:43 - Challenges Before FME Implementation

08:36 - Transformative Impact of FME on Data Processes

10:02 - Real-World Applications of FME at San Antonio River Authority

14:06 - Predictive Flood Modeling and Emergency Operations

16:31 - Standardization and Efficiency with FME

17:59 - Final Thoughts and Recommendations on FME

The trend of data at our fingertips is continuing. Virtually, everything we do is impacted by data. 

From driving your car to shopping to fighting pandemics such as Covid-19. Everything is impacted by data and understanding is improved by embracing and using it 

Data powers many technologies and itself is neither good nor bad. As data influences more of our life, we have to ensure that we use it responsibly so as to improve the lives of everyone from customers, employees, citizens, and the planet we all live on. We face many challenges and data plays a critical role in helping us make the best decisions.

In the last episode of a three-part podcast series with Safe Software, Analyst Susan Walsh speaks to Don Murray, President and co-founder of Safe Software, to explore:

• How data was critical in the fight and management of Covid 19 around the world. 
• The importance of using data responsibly so that people and organizations understand the often unintended consequences of their actions.    
• The critical role of data is to drive decisions to meet the challenges we face as individuals, organizations, and a planet. Our future depends on using data.

There is no time like now for all of us to embrace data.

Cloud-native is the new gold rush for businesses seeking speed, efficiency, and innovation. But are you getting the most out of your investment? Legacy troubleshooting and observability tools can be hidden anchors, dragging down your developers' productivity.

The result? You're not reaping the full benefits of cloud-native, and your competitors are leaving you in the dust. 

Chronosphere, a leader in modern observability, can empower your developers and unlock the true potential of cloud-native. Buckle up and get ready to discover how observability can become your secret weapon for unleashing developer agility and innovation.

In this episode of the EM360 Podcast, VP of Research at Eckerson Group, Kevin Petrie speaks to Ian Smith, Field CTO at Chronosphere, to discuss: 

• Observability 
• Cloud-native software developers
• Developer inefficiency
• The Chronosphere solution
• Data pipeline best practices 

One of the biggest challenges businesses face when it comes to data visualisation is handling the volume of data and the need for faster processing methods. 

There's a common misconception that effective data visualisation must be fancy and interactive, but simple visuals can be just as powerful. Ann K. Emery, an expert in the field, believes that accessibility doesn't have to be time-consuming or expensive. 

In this podcast, she shares actionable strategies for creating accessible visualizations with Paulina Rios Maya, Head of Industry Relations at EM360Tech. 

Key Takeaways

• Avoiding red-green colour combinations, 
• Ensuring proper colour contrast
• Using direct labelling instead of legends. 
• Avoiding using all-caps
• Using grey to highlight important information
• Employing small multiples to simplify complex visualisations. 

Chapters: 

00:00 - Introduction

00:54 - Defining Accessibility in Data Visualization

02:17 - Big A Accessibility Tips

06:36 - Little a Accessibility Strategies

12:28 - The Future of Data Accessibility

Episode 10 of our 12 part series with Cloudera.

In this podcast, Scott Taylor speaks to Wim Stoop, Product Marketing Director at Cloudera, about the data centre of the future by running a private cloud. Wim previously appeared in episode 8 to discuss security and governance. This time, he explores the current landscape and challenges of public cloud and what the futuristic utopia of private cloud in data centres means in terms of implementation, benefits, and future-proofing. Wim also touches on whether data analytics on-prem can behave as it does in public and the challenges private cloud addresses around cluster sprawl, upgrade complexity, and missed SLAs, in which he draws on a few helpful use cases.

Next week's episode: Enterprise Data Cloud in Action

Make sure you're subscribed so that you don't miss an episode of this fantastic series.

Geographic Information Systems (GIS) have transformed urban landscape analysis and government policy creation, albeit not without challenges. In the past, GIS analysts often visited locations to piece together information physically.

With the help of cutting-edge platforms like Safe Software’s FME, cities like Burnaby, British Columbia, have revolutionised their operations. This has led to a significant enhancement in the quality of life for its residents. From predictive modelling to real-time data analysis, the potential for innovation appears boundless, underscoring the importance of GIS technology in improving urban operations.

In this episode of the EM360 Podcast, Wayne Eckerson speaks to Herman Louie, GIS Analyst at the City of Burnaby, to discuss: 

• Design and implementation of GIS solutions
• Safe Software’s FME platform 
• Transition to NG9-1-1 
• The future of GIS 

We are in the final stretch of our 12 part series with Cloudera.

In this podcast, Scott Taylor speaks to Chris Darvill, RVP Solutions Engineering at Cloudera, about the business benefits of data visualisation. Chris begins by explaining how companies can bring data to life with data visualisation tools, before exploring what it means to have a 'common language' between data teams and the business. He then sheds light on the relationship between data storytelling and data visualisation - including the human element in visualisation - and outlines the key aspects that data leaders need to consider when implementing these types of tools. 

Next week's episode: Data Centres of the Future: Private Cloud

Make sure you're subscribed so that you don't miss an episode of this fantastic series.

Privacy by Default and Design is a fundamental principle of the General Data Protection Regulation (GDPR). It prioritises transparency, user control, and data security from the outset. This approach ensures that privacy is integrated into systems and processes by default rather than as an afterthought. 

By embedding these practices, organisations enhance trust and accountability while meeting regulatory requirements. However, challenges such as resistance to change and the need for cultural transformation must be addressed to implement this principle effectively.

In this episode of the Don’t Panic It’s Just Data, Tudor Galos, Senior Privacy Consultant, speaks to Paulina Rios Maya, Head of Industry Relations, about the impact of privacy by default and design extend to user experience, where issues like consent fatigue and the necessity for user-friendly interfaces arise. 

Key Takeaways:

• Organisations face challenges in implementing privacy by default and design, including resistance to change and the need for cultural transformation.
• Privacy by default and design impact user experience, with issues like consent fatigue and the need for user-friendly interfaces.
• Regulations like GDPR and CCPA incorporate privacy by default and design principles, emphasising compliance and accountability.

Chapters:

00:00 - Introduction and Overview

01:00 - Core Principles of Privacy by Default and Design

02:19 - Difference from Traditional Privacy Practices

04:09 - Challenges in Implementing Privacy by Default and Design

05:33 - Impact of Privacy by Default on User Experience

08:14 - Alignment of Privacy by Default with Regulations

09:04 - Ensuring Compliance and Trust

11:24 - Implications of Emerging Technologies on Privacy

13:15 - Innovations in Privacy-Enhancing Technologies

15:50 - Conclusion

Moving from an on-prem infrastructure to a frictionless cloud model has become a key goal for many companies. 

From scalability to improved security, as well as cost-saving benefits, moving to the cloud bring a lot of benefits. But what challenges are enterprises facing in their migration, and how can this process be made easier?

In this episode of the EM360 Podcast, Analyst Susan Walsh speaks to Alex Merced, Developer Advocate at Dremio, to discuss:

• On-prem data lakes 
• Moving to a frictionless cloud
• How to streamline the migration process

Generative AI and unstructured data are transforming how businesses improve customer experiences and streamline internal processes. As technology evolves, companies find new ways to gain insights, automate tasks, and personalize interactions, unlocking new growth opportunities. 

The integration of these technologies is reshaping operations, driving efficiency, and enhancing decision-making, helping businesses stay competitive and agile in a rapidly changing landscape. Organizations that embrace these innovations can better adapt to customer needs and market demands, positioning themselves for long-term success.

In this episode, Doug Laney speaks to Katrina M. Conn, Senior Practice Director of Data Science at Teradata, and Sri Raghavan, Principal of Data Science and Analytics at AWS, about sustainability efforts and the ethical considerations surrounding AI. 

Key Takeaways:

• Generative AI is being integrated into various business solutions.
• Unstructured data is crucial for enhancing customer experiences.
• Real-time analytics can improve customer complaint resolution.
• Sustainability is a key focus in AI resource management.
• Explainability in AI models is essential for ethical decision-making.
• The combination of structured and unstructured data enhances insights.
• AI innovations are making analytics more accessible to users.
• Trusted AI frameworks are vital for security and governance.

Chapters: 

00:00 - Introduction to the Partnership and Generative AI

02:50 - Technological Integration and Market Expansion

06:08 - Leveraging Unstructured Data for Insights

08:55 - Innovations in Customer Experience and Internal Processes

11:48 - Sustainability and Resource Optimization in AI

15:08 - Ensuring Ethical AI and Explainability

23:57 - Conclusion and Future Directions

Data is the backbone of any successful business, and having a 360-degree view of it is crucial to understand the key metrics and drivers of the organization. 

By collecting, processing, and analyzing data from various sources such as customer interactions, financial transactions, and employee performance, your business can gain valuable insights into its operations. 

This 360-degree view of the business data will allow your company to take a data-driven approach to decision-making, leading to better results and improved performance.

In this episode of the EM360 Podcast, Analyst Susan Walsh speaks to Dan Everett, VP of Product and Solution Marketing at Informatica about:

• Connecting different types of data 
• Collecting, analysing and storing data while complying with regulations
• Business-wide observability challenges

The digital age is fueled by data, and the engines powering that data are data centres. However, this growth comes at a significant energy cost. In the latest episode of the EM360Tech Don’t Panic It’s Just Data podcast, Shubhangi Dua speaks with Rolf Bienert, Technical & Managing Director of the OpenADR Alliance, to shed light on the urgent need for sustainable energy practices within the data centres industry. 

In this episode, we discuss the stark reality of escalating energy consumption, driven by factors like the rise of AI, and the critical importance of moving beyond superficial "green" initiatives to implement genuine, impactful solutions.

From talking about the historical context of data centres energy usage, the evolution of energy demands and the challenges of achieving net-zero goals, Rolf provides valuable insights into innovative solutions such as smart grids, microgrids, and virtual power plants. These hold immense potential for managing energy distribution efficiently and sustainably. 

Beyond technological solutions, the podcast addresses the critical role of regulatory frameworks and industry standards in fostering sustainable practices. The frameworks are necessary to adapt to modern energy consumption patterns, ensuring interoperability and reducing costs. It spotlights the importance of collaboration between IT and utility sectors, as well as open communication with the public, to address concerns about energy consumption and build trust. 

Takeaways

• Data centres are increasingly becoming significant consumers of energy.
• Sustainability in data centre is often perceived as branding rather than genuine effort.
• AI's demand for processing power is escalating energy needs.
• Smart grids are essential for managing energy distribution effectively.
• Microgrids and virtual power plants offer promising solutions for energy sustainability.
• Enterprises can leverage renewable energy to become energy providers.
• Regulatory frameworks need to adapt to modern energy consumption patterns.
• Standards are crucial for ensuring interoperability and reducing costs.
• Collaboration between IT and utility sectors is vital for sustainable energy management.
• Open communication is key to addressing public concerns about energy consumption.

Chapters

00:00 Introduction to Data Centres Sustainability

03:22 Historical Perspective on Data centres Energy Consumption

08:32 The Role of Smart Grids in Energy Management

12:40 Understanding Microgrids and Virtual Power Plants

21:30 Enterprise Strategies for Sustainable Data Centres

29:51 Regulatory Challenges and Opportunities

32:34 The Importance of Standards in Data Centres Growth

Advanced analytics are powering today's decision making and operational efficiency. Today’s organisations can now take advantage of real-time decision making with thanks to newer technologies. However, does this guarantee quality? Joining us in this episode to discuss how to manage the quality of real-time data is Syncsort’s Aisan Baird.

Is the modern data stack dead? How can you better leverage your MDS? And how can you stay ahead of the curve in a market which is seeing more and more new trends emerging constantly?

These were questions posed at the recent Modern Data Stack Roadshow; Fivetran's follow-up to the successful Modern Data Stack Conference. These half-day events convene top industry experts to discuss how to drive impact and business growth using data.

With plenty of exciting talking points raised by the industry leaders in attendance, how are some of the biggest movers and shakers talking about the data space right now?

In this episode of the EM360 Podcast, Analyst Susan Walsh speaks to Mark Van De Wiel, Field CTO at Fivetran, to explore: 

• Keeping up with the modern data stack
• Leveraging your modern data stack
• Advice on tackling complex data challenges

Lagan Group Holdings is a leader in the construction and asset management space, and a key part of their strategy is to become more data-driven, using data for strategic advantage. A challenge, however, is that data is scattered in a number of systems—from billing to procurement to payroll, making it difficult to create a single view of key data assets. Lagan has overcome these challenges, and have implemented a self-service business intelligence & reporting to gain data-driven insights. Join Jim Fennell from Lagan Group and Donna Burbank from Global Data Strategy as they discuss the challenges and benefits of using self-service BI to become a data-driven organisation.

For information regarding your data privacy, visit acast.com/privacy

This is the second episode of the series and here Donna Burbank is joined by representatives of Syncsort and Hortonworks. The panel discuss whether Hadoop augments the data warehouse or replaces it and conclude by looking at how business users and IT can work together in these ecosystems in the future. Whether you are a Chief Data Officer looking to understand what new technologies and methodologies are available or a businessperson trying to understand the challenges around data quality, listen to this educational podcast to discover how data quality and data governance can support your business transformation initiatives.

For information regarding your data privacy, visit acast.com/privacy

The trend of data at our fingertips is continuing. Virtually, everything we do is impacted by data. 

From driving your car to shopping to fighting pandemics such as Covid-19. Everything is impacted by data and understanding is improved by embracing and using it 

Data powers many technologies and itself is neither good nor bad. As data influences more of our life, we have to ensure that we use it responsibly so as to improve the lives of everyone from customers, employees, citizens, and the planet we all live on. We face many challenges and data plays a critical role in helping us make the best decisions.

In the last episode of a three-part podcast series with Safe Software, Analyst Susan Walsh speaks to Don Murray, President and co-founder of Safe Software, to explore:

• How data was critical in the fight and management of Covid 19 around the world. 
• The importance of using data responsibly so that people and organizations understand the often unintended consequences of their actions.    
• The critical role of data is to drive decisions to meet the challenges we face as individuals, organizations, and a planet. Our future depends on using data.

There is no time like now for all of us to embrace data.

Application Programming Interface, or API, was initially built to tackle the historic IT issue of system integrations. The software enables two applications and their individual data siloes to communicate with ease, leaving companies to focus on matters that do not allow for automation. However, this isn't the only tech problem that API, when managed correctly, can be used to solve.

Martin Buhr, CEO and Founder of Tyk is joining Scott Taylor, Principal Consultant at MetaMeta Consulting, to explore how API management can drive digital transformation and continuity. Martin lends his expertise on making data 'talk' and delves into how GraphQL and Tyk's Universal Data Graph is changing the game. He also discusses the differences and benefits of best-in-class solutions versus home-grown solutions, before explaining the importance of digital transformation projects through use cases and customer stories.

In today’s data-driven world, real-time analytics has become a cornerstone for businesses seeking to make smarter, faster decisions. From enhancing user experiences to enabling continuous intelligence, the ability to process data in real-time is transforming industries. Yet, challenges such as legacy systems and the demand for innovative data management approaches persist.

This episode explores the evolution of real-time analytics and its crucial role in modern data processing. We delve into how technology is reshaping the way businesses interact with data and the importance of user-centric design in creating powerful data applications.

Joining Christina Stathopoulos, Founder of Dare to Data, is Rahul Rastogi, Chief Innovation Officer at SingleStore. Together, they discuss the necessity of real-time data in today’s fast-paced business environment, tackle the challenges organizations face in adapting to this shift, and highlight how data serves as the foundation for AI-driven innovation. 

Don’t miss this insightful discussion packed with practical strategies and forward-looking ideas!

Key Takeaways

• Real-time analytics has evolved from a luxury to a necessity.
• Streaming technologies like Kafka and Spark have revolutionized data processing.
• Legacy systems are often monolithic and ill-suited for real-time analytics.
• Modern data platforms enable easier data management and integration.
• Continuous intelligence requires a solid analytics foundation.
• User experience is critical for the adoption of data applications.
• Organizations must treat data as a valuable asset.
• Data governance and quality are essential for effective analytics.
• The separation of compute from storage enhances scalability.
• Real-time processing with low latency improves user satisfaction.

Chapters

00:00 - Introduction to Real-Time Analytics

06:14 - The Evolution of Technology in Data Processing

10:09 - Challenges of Legacy Systems

14:23 - Innovative Approaches to Data Management

18:06 - Building a Foundation for AI Innovations

21:27 - User Experience in Data Applications

Data productization. The art of turning raw data into business-ready consumable data products. 

Applying product management principles to data management, data productization can connect your business objectives to data and stay ahead of the curve. 

But what things should you consider when building a data product? What challenges are likely to arise? And how can you effectively bridge the gap between data teams and business units to ensure the successful adoption and utilization of these products by end users?

In this episode of the EM360 Podcast, Analyst Kate Strachnyi speaks to Colin Brown, CMO at Revelate and Nicolas Doyen, CPO at Revelate, to discuss:

• Building a data product
• Ensuring successful adoption by end users
• Technologies shaping the future of data productization

Managing large volumes of data in the context of AI and machine learning applications presents challenges related to data quality, data preparation, and automation.

The requirements of data management are changing with the advent of generative AI, requiring more flexibility and the ability to handle larger volumes of data. Pimcore leverages AI and machine learning to automate data utilization and improve data intelligence. 

By streamlining data management and integrating various data sources, Pimcore drives revenue growth for its customers. The platform combines data management and experience management to deliver personalized data across communication channels. Pimcore’s MDM solution addresses the challenges of integrating data for both human and machine consumption. The choice between physical and virtual MDM hubs depends on the use case and industry. 

In this episode of the EM360 Podcast, Doug Laney, Data and Analytics Strategy Innovation Fellow at West Monroe speaks to Dietmar Rietsch, Managing Director and Co-Founder of Pimcore, to discuss: 

• Data management
• AI
• Machine learning
• Data quality

Machine Learning Operations, or MLOps, is a set of practices that aims to deploy and maintain machine learning models reliably and efficiently.

Similar to the DevOps approach, MLOps seeks to increase automation and improve the quality of production models while focusing on business requirements.

In the first part of this three-episode series on the ‘Transformational Serverless Acceleration for Analytics’, Analyst Christina Stathopoulos speaks to Richard Heyns, Founder and CEO of Brytlyt to cover:

• Why do two-thirds of models built with the intention to deploy never make it to deployment
• Databases and the critical role they play
• Scaling up analytics and ML

The data-driven revolution has enabled brands to achieve true customer centricity — but only if they have the right data analysis and experience orchestration capabilities.

Whether creating a single customer view, generating predictive insights, or orchestrating seamless omnichannel experiences, organisations must work to make sure their customer data is accurate, accessible, and actionable.

The data-driven revolution is transforming the customer experience

Hosting this episode of the EM360 Podcast is Susan Walsh, Founder, and MD of The Classification Guru. Joining her is the Head of Martech Strategy at ActionIQ, James Meyers, who will be sharing his insight on the data-driven revolution and its growing impact on the customer journey and customer experience (CX) as a whole.

With an ever-growing number of competitors entering the market, it's vital for businesses to grow and retain their customer relationships by ensuring they have a polished, data-driven CX strategy. Tune in to learn about:

Why siloed data continues to be one of the biggest pain points, for organisations looking to create seamless CX

The types of valuable insights marketers can obtain if their company's data is de-siloed

Use cases of customer data platforms and how they're helping to power CX strategies today

Decisions organisations face when choosing between building a CPD in-house or licensing from a vendor

Hybrid working has become a common talking point of many organisations in the last year as the increase of remote working has transformed several industries. As one might expect, a change in our work culture drastically changes the demands of our workers, meaning that more skilled professionals are required to handle independent working. The problem is that in its current state, the UK is underprepared for this paradigm shift; according to Coursera's Global Skills Report, the UK has the lowest proficiency for business skills in Europe, ranking only at a 29% proficiency. 

There is hope for the UK yet; since the pandemic, 24% more women and 32% more unemployed people have enrolled for STEM courses in the UK. This would help to fix the gender gap in STEM, a current concern for many businesses, and it will also help to increase our number of skilled professionals that can perform in the private sector.

In this Data Transforming Business podcast, EM360 Head of Content Max Kurton speaks to Anthony Tattersall, VP of EMA at Coursera. Throughout the discussion, Anthony guides us through some of the most popular courses in the UK, the business skills that are trending the most in the UK and the action needed to help fix the skills gaps within enterprise technology.

Data visualisation is increasing in popularity as companies move towards making intelligent data-driven decisions. Analytics providers are recognising this and, as a result, are offering innovative ways to visualise insights. Joining us on this podcast today is Jimmie Lenz, Principal at The Financial Risk Group, to demonstrate how SAS are moving to the forefront of data visualisation.

Cloud storage and data democratization are two strategic technology trends that have revolutionised the enterprise. Whilst the first enables organisations to store data and run workloads off-site, the latter expedites decision making by making data accessible to an entire team. However, in line with the ever-evolving tech landscape, both cloud storage and data democratization must move and evolve with technological changes, updates, and transformations.

What are data lakes doing to improve data quality?

Joining us to discuss unlocking the future of cloud storage and data democratization and answer 'What are data lakes doing to improve data quality?' is Thomas Hazel, Founder, CTO and Chief Scientist at ChaosSearch. Thomas begins by outlining the evolution and current state of cloud storage and data lakes, before looking at the challenges and opportunities each one benefits businesses. He also explores the philosophy that organisations must put up complicated gates to scale and access data, including top tips on how to avoid this damaging mindset. Final thoughts focus on the benefits of Object Storage from a standpoint of scalability, security, and ROI.

Data pipeline automation is revolutionizing the way organisations handle data. 

This new approach to data management is challenging the traditional modern data stack, which relied on a series of disparate tools to handle different aspects of data processing. With data pipeline automation, organizations can simplify their data stack, relying on a single tool to manage the entire process. 

This shift will allow businesses to focus on insights and decision-making, rather than spending time wrangling data. As a result, data pipeline automation will become the key component of the post-modern data stack.

In this episode of the EM360 Podcast, Analyst Christina Stathopoulos speaks to Sean Knapp, Founder and CEO at Ascend.io, and we’re here to talk about:

• Solving data stack challenges
• Automation in data pipelines
• What the ultimate solution will be

Open source technologies are transforming how businesses manage real-time data on cloud platforms. By leveraging flexible, scalable, and cost-effective open-source tools, organisations can process and analyse large volumes of data with speed and precision. These technologies offer unmatched transparency, customisation, and community-driven innovation, making them ideal for real-time monitoring, analytics, and IoT applications.

As data demands grow, open-source solutions ensure that businesses stay agile, reduce vendor lock-in, and maintain full control over their cloud infrastructure. The result? Faster insights, smarter decision-making, and enhanced performance—all powered by open source. 

In this episode, Paulina Rios Maya, Head of Industry Relations at EM360Tech, speaks to Mikhail Epikhin, Chief Technology Officer at Double Cloud, about The Power of Open Source in Cloud Platforms. 

Key Takeaways:

• Open-source technologies provide standard building blocks for products.
• Community-driven innovation is essential for the evolution of technology.
• Flexibility in data infrastructure is crucial for real-time processing.
• Observability and monitoring are vital for performance optimisation.
• Managed services can accelerate product development and feature implementation.

Chapters:

00:00 - The Power of Open Source in Cloud Platforms

05:24 - Apache Airflow: Enhancing Real-Time Data Management

10:08 - Balancing Open Source and Managed Services

13:57 - Best Practices for Scalability and Performance

This is the third episode of the series and Donna Burbank is joined by Erwin, Sandhill Consulting and Swisscom. The panel discuss innovative ways to increase revenue and reduce costs using data-driven digital technologies. Whether you are a Chief Data Officer looking to understand what new technologies and methodologies are available or a businessperson trying to understand the challenges around data quality, listen to this educational podcast to discover how data modelling can support your business transformation initiatives.

For information regarding your data privacy, visit acast.com/privacy

Data engineering is how companies design and build systems for collecting and using their data at scale.

A critical practice as companies are pressured to make more and more data-driven decisions, data engineering is essential for enterprises to get ahead. 

In this episode of the EM360 Podcast, Editor Matt Harris speaks to Salma Bakouk, Co-Founder and CEO at Sifflet, to discuss;

• Trends shaping the data engineering industry
• Caring about data reliability and observability
• What the future brings

Managing network traffic efficiently is essential to control cloud costs. Network flow

reports are critical in providing detailed insights into data movement across cloud

environments. These reports help organisations identify usage patterns, track

bandwidth consumption, and uncover inefficiencies that may lead to higher expenses.

With a clear understanding of how data flows, businesses can make informed decisions

to optimise traffic, reduce unnecessary data transfers, and allocate resources more

effectively. This helps lower cloud costs, improves network performance, and enhances

security by revealing unusual or potentially harmful traffic patterns.

In this episode, Wayne Eckerson from Eckerson Group speaks to Ben Schaechter,

CEO of Vantage, about optimising network traffic costs with Vantage’s Network Flow

Reports.

Key Takeaways:

● Network Flow Reports provide detailed insights into AWS costs.

● They help identify specific resources driving network traffic costs.

● Organisations can reduce costs by up to 90% with proper configuration.

● The shift towards cost management in cloud services is critical.

● FinOps teams are becoming essential for cloud cost optimization.

● Anomaly detection can alert teams to unexpected cost spikes.

● Vantage integrates with multiple cloud providers for comprehensive cost

management.

● Effective cost management does not have to impact production workflows.

Chapters:

00:00 - Introduction to Vantage and Network Flow Reports

02:52 - Understanding Network Flow Reports and Their Impact

06:09 - Real-World Applications and Case Studies

09:03 - The Shift in Cost Management Focus

11:54 - Tangible Benefits of Implementing Network Flow Reports

15:07 - The Role of FinOps in Cost Optimization

18:00 - Conclusion and Future Insights

As businesses endeavour to effectively action their data, business intelligence (BI) software and analytics operating systems have become all the more important and cherished. Not only do BI software fulfil their purpose of helping companies attain useful business insights, but they can also support flexibility and strengthen governance.

Joining Ronald van Loon and EM360 to lend his BI expertise is Ian Macdonald, Principal Technologist at Pyramid Analytics. Firstly, Ian gives a comprehensive introduction to analytics operating systems, before giving an overview of the BI market. He also delves into the improved work capabilities that BI provides to businesses, how BI can improve remote work experiences for employees, and how it helps employees achieve unique goals within their individual roles.

Furthermore, Ian outlines the challenges businesses face when creating analytics environments within their organisation. He also advises on the technologies and organisational processes needed to successfully implement analytics.

Robotic process automation (RPA) has gained significant traction within the last year. However, despite having secured a place in the market, RPA is still fairly new. In light of this, Ronald van Loon speaks with Rob Hughes, VP – Head of Marketing EU at Automation Anywhere to find out more about this exciting technology.

Firstly, Rob defines RPA and what makes it such a hot topic today. In particular, he addresses the confusion between artificial intelligence (AI) and RPA and outlines AI's role in the RPA realm. Then, Rob explores what is driving the increasing popularity of RPA and demonstrates the use cases for it across various industries. Finally, he discusses the challenges associated with RPA implementation and how to deploy it successfully.

Data observability refers to the ability to collect, measure, and analyse data from various sources in order to understand the current state and behaviour of a system.

This includes monitoring the system's performance, availability, and errors, as well as identifying patterns and anomalies in the data. 

By implementing data observability, organisations can gain insights into their systems and make data-driven decisions to improve performance, optimize resources, and reduce costs. Common tools used for data observability include logging, metrics, tracing, and alerting. 

In this episode of the EM360 Podcast, Analyst Christina Stathopoulos speaks to Lior Gavish, Co-Founder and CTO at Monte Carlo, to discuss:

• Getting started with data observability
• Observability trends for 2023
• How to implement and common challenges

A returning guest comes back to provide more fantastic insight into our 12 part Cloudera series.

Join Scott Taylor and Paul Mackay, EMEA Cloud Lead from Cloudera, as they discuss how data - and the devices on which it's generated - becomes ever more prolific and why businesses need a hybrid cloud strategy that can span a multitude of different environments and enable them to say yes, not no. 

Next week's episode: Security and Governance

Make sure you're subscribed so that you don't miss an episode of this fantastic series.

In traditional data architecture, data was always centralised in a data warehouse or a data lake and governed by a centralised team. 

However, with the rise of distributed systems, microservices, and agile methodologies, this approach has proven to be inadequate for managing data at scale. Data Mesh proposes a different approach, where data is treated as a product and owned by the teams that produce it. 

In other words, it's a way of thinking about data management that focuses on decentralisation and autonomy. But how can companies use this to their advantage?

In this episode of the EM360 Podcast, Analyst Christina Stathopoulos spoke to Paolo Platter, Co-Founder and CTO at Agile Lab, about: 

• Successful data mesh strategies
• Benefits vs monolithic data lakes
• Customer success stories

Agile Lab works with an array of clients across the globe, creating business vertical solutions to address specific challenges and needs in their field of activity. To hear about their success stories and the ways in which they exceed their clients' expectations, skip to 19:40.

Corporate Performance Management (CPM) is a set of processes, methodologies, and tools used by organisations to measure and manage their performance and achieve their strategic objectives. 

CPM encompasses various activities that help businesses plan, monitor, and analyze their performance against key performance indicators (KPIs) and targets.

But why is it so important? How does this technology interact with other business functions? And how can companies get started?

In this episode of the EM360 Podcast, Analyst Doug Laney speaks to Arthur Forbus, Managing Director and COO at HollandParker, to discuss:

• CPM and why every company needs it
• Misconceptions around CPM
• How to raise your CPM game

Maximising data relationships through text analytics, particularly with tools like LLMS and Knowledge Graphs, offers organisations unprecedented insights and capabilities. By leveraging these advanced technologies, businesses can unlock hidden connections and patterns within their data, leading to more informed decision-making and strategic planning. 

Integrating Ontotext's solutions is a game-changer, empowering organisations to extract, organise, and visualise complex information from unstructured data sources. With Ontotext's expertise in semantic technology, businesses can construct robust knowledge graphs that offer a comprehensive understanding of their data landscape. This comprehensive approach not only facilitates better analysis and interpretation of data but also ignites innovation and propels business growth in today's increasingly data-driven world.

In this episode of the EM360 Podcast, Paulina Rios Maya, Head of Industry Relations, speaks to Doug Kimball, Chief Marketing Officer at Ontotext, to discuss: 

• AI in Enterprise Knowledge 
• LLMs 
• Knowledge Graphs 

Chapters

00:00 - Challenges of Integrating LLMs into Enterprise Knowledge Management Systems

04:35 - Enhancing Compatibility and Efficacy with Knowledge Graphs

07:21 - Innovative Strategies for Integrating LLMs into Knowledge Management Frameworks

11:07 - The Future of LLM-Driven Knowledge Management Systems: Intelligent Question Answering and Insight Enablement

Safe Software’s FME is transforming Omaha’s approach to urban mobility with groundbreaking solutions for asset management, e-scooter tracking, and parking management. 

FME’s robust data integration capabilities are at the core of Omaha’s advancements. The data integration platform enables real-time tracking of e-scooters, offering precise data on their locations and usage patterns. This innovation enhances the management and accessibility of e-scooters, making urban mobility more efficient and user-friendly.

Automated parking management processes, facilitated by FME, streamline city operations and reduce manual efforts. This automation leads to smoother parking experiences for residents and visitors, while dynamic rate adjustments, powered by FME, ensure that parking fees are responsive to real-time demand, optimising availability and revenue.

In this episode, Wayne Eckerson from Eckerson Group speaks to Jacob Larson, an Applications Analyst from the City of Omaha, to discuss Omaha’s usage of FME. 

Key Takeaways:

• FME helps automate the tracking of e-scooters in real time.
• Data sharing agreements with providers like Lime enhance tracking capabilities.
• Omaha's parking management has been transformed through automation.
• FME allows for dynamic changes in parking rates based on events.
• The integration of GIS data with third-party APIs is crucial for parking management.
• Omaha is pioneering a real-time parking information system in the US.

Chapters: 

00:00 - Introduction to Omaha's Data Initiatives

01:03 - FME's Role in Asset Management

04:53 - Real-Time Tracking of E-Scooters

07:48 - Automating Parking Management

10:06 - Innovations in Parking Availability

12:59 - Dynamic Parking Rate Management

Ensuring the reliability and effectiveness of AI systems remains a significant challenge. Generative AI must be combined with access to your company data in most use cases, a process called retrieval-augmented generation (RAG). The results from GenerativeAI are vastly improved when the model is enhanced with contextual data from your organization. 

Most practitioners rely on vector embeddings to surface content based on semantic similarity. While this can be a great step forward, achieving good quality requires a combination of multiple vectors with text and structured data, using machine learning to make final decisions. 

Vespa.ai, a leading player in the field, enables solutions that do this while keeping latencies suitable for end users, at any scale. 

In this episode of the EM360 Podcast, Kevin Petrie, VP of research at BARC US speaks to Jon Bratseth, CEO of Vespa.ai, to discuss: 

• the opportunity for Generative AI in business
• why you need more than vectors to achieve high quality in real systems
• how to create high-quality GenerativeAI solutions at an enterprise scale

Instant analytics and reporting culminate in the new open-source, column-oriented DBMS, ClickHouse. The system has grown to be one of the most popular database projects, with thousands of users generating analytical reports via real-time SQL queries since it publicly launched in 2016 following an 8 year internal testing period with Yandex. When faced with trillions of rows of data and the need to filter, explore, and interact with it, ClickHouse is the solution for businesses.

ClickHouse is the Future of Analytics and Reporting

In this podcast, Scott Taylor, Principal Consultant at MetaMeta Consulting, is joined by Robert Hodges, CEO at Altinity, to discuss ClickHouse, the first open-source, SQL data warehouse that competes with the major DBMS players. Over the course of the conversation, they look at:

The history and background of ClickHouse

Benefits of open source from a data perspective

Management perspectives of the data journey

Applying ClickHouse across small to large organisations

Government organisations face a multitude of challenges when it comes to managing their data effectively. From interoperability issues between systems to the need for seamless collaboration across agencies, the complexity can be overwhelming. Safe Software's FME platform offers a comprehensive solution to these challenges by providing a flexible and intuitive data integration platform tailored to the unique needs of government agencies.

With FME, government organisations can overcome the barriers that hinder efficient data management. FME enables streamlined operations and improved decision-making processes by seamlessly connecting disparate systems and applications. Whether it's digital plan submissions, emergency services coordination, or interagency health data sharing, FME empowers government agencies to achieve their data integration goals with ease.

In this episode of the EM360 Podcast, Doug Laney, Data and Analytics Strategy Innovation Fellow at West Monroe speaks to Tom Seymour, Government Sales Team Lead at Safe Software, to discuss:  

• Data integration and interoperability 
• Safe Software’s FME platform 
• FME in governments 
• Advantages of FME 
• ROI with FME 

Organisations are turning to business intelligence (BI) and data analytics to give their strategy a competitive edge. This is especially so in an age of digital transformation. At hand to lend their expertise on the matter are Yellowfin’s Glen Rabie and TreeHive Strategy’s Donald Farmer.

Business leaders are in the midst of the biggest digital transformation revolution that the enterprise has ever seen. As the pandemic continues to accelerate the adoption of digital products and services, corporate culture, operations, technologies, stakeholder relationships/partnerships, and customer management/experience continues to evolve. Data transformation has made the most significant impact. No longer just an add-on, data and analytics are driving organisations on a daily basis, informing key decisions in real-time.

In this podcast, Scott Taylor, Principal Consultant at MetaMeta Consulting, sits down with Andy Isenman, Head of Technology: Cloud and Data at Heathrow, Mark Smith, General Manager of Microsoft Solutions, and Nick Baladi, Account Director at Adatis, to talk about utilising the analytics of big data to transform your business. The conversation specifically focuses on the optimisation of data to aid businesses in a post-pandemic economy, in which parallels are drawn to how Adatis assisted Heathrow to be a more responsive organisation by using Microsoft cloud solutions. The cohort of leading data experts discuss the impact of COVID-19 on data and cultural transformation, the importance of being data-driven, and how the multi-stakeholder partnership has successfully aided and benefited Heathrow's data journey and initiatives. Andy, Mark, and Nick also share some words of wisdom for organisations who are looking to begin their data journey and explore where they see data transformation heading in the future.

When an organisation talks about data integration, there are a lot of hurdles to overcome. To achieve results they need to make sure their data is of high quality, organised and formatted. However, this is easier said than done as data engineers are trying to extract data from an ever-changing source. With cloud-based applications and siloed data, it raises a lot of questions as to how to achieve a unified view and gain insightful analytics.

In this podcast, Ronald van Loon speaks to Mark Maxwell, Head of UKI Strategic Sales at Fivetran. Firstly, Mark outlines why an organisation should incorporate data integration into their analytic strategy. Then he explains what key decisions are needed for data warehousing and their workloads and analytics processes. Also, Mark demonstrates what a typical automated data integration process involves when an organisation is starting this journey. Finally, he looks at how this solution can help teams focus on analytics over ETL.

In this episode, Rachel Thornton, Fivetran's CMO, discusses the highlights of Big Data London 2024, including the launch of Fivetran Hybrid Deployment, which addresses the needs of organisations with mixed IT environments.

The conversation delves into integrating AI into business operations, emphasizing the importance of a robust data foundation. Additionally, data security and compliance challenges in the context of GDPR and other regulations are explored. The episode concludes with insights on the benefits of hybrid deployment for organisations.

Key Takeaways: 

• Big Data London 2024 is a significant event for data leaders.
• Fivetran Hybrid Deployment caters to organizations with mixed IT environments.
• AI integration requires a strong data foundation.
• Data security and compliance are critical in today's landscape.
• Organizations must understand their data sources for effective AI use.
• Hybrid deployment allows for secure data management.
• Compliance regulations are becoming increasingly stringent. 
• Data readiness is essential for AI integration.

Chapters: 

00:00 - Introduction to Big Data London 2024

02:46 - Launch of Fibntran Hybrid Deployment

06:06 - Integrating AI into Business Operations

08:54 - Data Security and Compliance Challenges

11:50 - Benefits of Hybrid Deployment

Predictive data intelligence is the use of data, AI-driven algorithms, and machine learning techniques to quickly connect data consumers with the most relevant data they need to drive their business initiatives and deliver greater value.

The goal of predictive analytics is to go beyond simply describing data to enable data consumers to accelerate the next-best actions to take for more effective decision making. For example, a retailer can understand their most relevant and high-quality data sets to better forecast consumer demand for a product, or a financial institution may identify the most accurate, complete customer data used to fuel analytics that help identify the likelihood of default on a loan.

In this episode of the EM360 Podcast, Analyst John Santaferraro speaks to Informatica’s Ian Stahl, Senior Director of Product Management and Chris Phillips, VP of Product Management to discuss:

• Shifting from business intelligence to predictive data intelligence
• Data sharing and data marketplaces
• The data consumption revolution

Data culture is becoming an increasingly important philosophy in the modern enterprise.

Making data-driven decisions is critical to the success of a company in today’s world, and there really is no better way to do that than ensuring a data culture runs through the firm.

There are plenty of studies that show a correlation between the maturity of a data culture and the success of a business, including this one from Collibra which states “Organisations with higher levels of maturity across their data culture are likely to realise higher business benefits and performance versus peers.”

In this episode of the EM360 Podcast, Editor Matt Harris spoke to Databricks’ Field CTO Robin Sutara at Big Data London 2022 to discuss:

Building and maintaining a data culture

Data culture maturity

The Women in Data movement

For organisations of any size, data management is key and data virtualisation is the next logical step in making that a reality. The role that data virtualisation plays within data management is to bridge the gap between IT and the business. This allows the combination of data in real-time and allows for true business transformation, so that the data is available to everybody while keeping it secure, allowing users or other applications to gain the access and insights they need.

In this podcast, Ronald van Loon speaks to Paul Moxon, Senior SVP of Data Architecture & Chief Evangelist, Charles Southwood, Regional VP – Northern Europe & MEA at Denodo and Sylvain Dutilh – Principal BI Administrator at Landsbankinn. They discuss the vital role data virtualisation plays in modern data management and accelerating digital transformation strategies. Also, how this promotes a culture of data democratisation across an organisation. Next, they explore some interesting case studies and also discuss why data fabric is a key resource in improving exploration and discovery. Finally, they look at typical data virtualisation deployment scenarios and the next steps within the context of an organisation’s data journey.

The traditional data warehousing landscape is changing. The concept of private data cloud offers a compelling alternative to both cloud PaaS and traditional data warehousing. Imagine a secure, dedicated environment for your data, existing entirely within your organisation's control.

Yellowbrick, a leader in private data cloud solutions, empowers businesses to leverage their data on their terms. Their Bring Your Own Cloud (BYOC) approach offers unmatched flexibility and control. You can deploy Yellowbrick anywhere your data needs to be—public cloud, private cloud, or even the network edge. This ensures compliance with regulations and keeps your data exactly where you want it and can bring down costs. 

In this episode of the EM360 Podcast, Wayne Eckerson, President of Eckerson Group, speaks to Mark Cusack, Chief Technology Officer of Yellowbrick, to discuss:

• The need for hybrid multi-cloud data platforms 
• How Yellowbrick differentiates
• The future of private data cloud
• Why Yellowbrick? 

Welcome to season 5! This new and exciting series from Cloudera will take us on a journey across all things cloud and data over the next 12 weeks.

In this podcast, Scott Taylor speaks to Paul Mackay, EMEA Cloud Lead at Cloudera. Firstly, Paul outlines what an enterprise data cloud is and how to assess the need for a cloud initiative effectively. Next, he details how organisations make the right choices to leverage cloud correctly and the data management implications. Finally, Paul explains the importance of enterprise-class security and governance.

Next week's episode: Optimise the Cost of Data and Analytics with Hybrid Cloud

Make sure you're subscribed so that you don't miss an episode of this fantastic series.

Location intelligence. Location intelligence is crucial for a company's data-driven decision-making process, providing insights into the relationship between location and business operations. It helps identify new market opportunities, optimize operations, improve customer experiences, mitigate risks, and provide a competitive advantage.

By analyzing location-specific information, companies can make informed decisions that drive growth, reduce costs, and increase profitability. Ultimately, location intelligence is a valuable tool for companies seeking to make strategic decisions that optimize operations, enable growth, and gain a competitive edge in their respective industries.

In this episode of the EM360 Podcast, Analyst Susan Walsh speaks to Adam Ejsmont, Co-Founder of Echo Analytics, about:

• Location intelligence in the modern world
• Data collection and ensuring data privacy
• Why investing in location intelligence is critical

In the fourth episode of the series, Donna Burbank chairs a panel consisting of the CTO from DS Virgin Racing Formula E Team and also representatives from HPE and Cloudera. They discuss how new business models are emerging as data-driven technology provides opportunity for change. The also look at whether the CDO, traditionally a ‘back office’ role is now one of the most important roles within an organisation. Whether you are a Chief Data Officer looking to understand what new technologies and methodologies are available or a businessperson trying to understand the challenges, listen to this educational podcast to discover how important data can be to support your business transformation initiatives.

For information regarding your data privacy, visit acast.com/privacy

The promise of the public cloud has instead paved the way for inconvenient costs. This is a result of applications becoming more refined, leaving companies wondering where to deploy them. Does this mean that private cloud is the way forward? Joining us in this episode to talk public versus private is JR Rivers, Co-Founder and Chief Technology Officer at Cumulus Networks.

All businesses understand that there is real value in data and that it is a strategic asset for all organisations. However, a lot of companies are still struggling to rapidly unlock this value due to a lack of resources and time. In order to capitalise on this, organisations need to have a solid data warehousing solution in place. In this podcast Ronald van Loon speaks with Weelin Lim, Chief Product Officer at TrueCue and Pratim Das, Head of Solutions Architecture, Data and AI at Microsoft to understand the strategic power of data warehousing and people analytics.

Firstly, they address the business challenges that end to end data warehousing, and people analytics can address. Then, Weelin and Pratim discuss what's needed from an organisational, technological, cultural, and team perspective when adopting these solutions and who the SaaS end-to-end data warehousing solution is right for. They also explore the steps organisations need to take to meet the demands of evolving analytics environments and to put a people analytics strategy into practice. Finally, Weelin and Pratim discuss the short term and long term business impact of an end-to-end data warehousing strategy and offer their advice for organisations looking to implement this and a people analytics solution.

Advanced analytics is the next step for organisations that want to be at the cutting edge of data analysis. For decades, organisations have been generating reports, primarily documenting 'What happened?' or 'What is happening?'. Essentially, it was once solely about descriptive analytics reporting, until some decided to take it to the next level with diagnostic analytics - i.e. looking at why things happen. Fast forward to more recent years and the evolution of technologies like data lake and warehouse have led to explosive growth in data volume, velocity, and variety and increased the demand for organisations to garner greater insights from data. This is how advanced analytics was born.

Advanced analytics: the next stage in data evolution

On this podcast, Susan Walsh, Founder and MD of The Classification Guru, joins Jack Lambert, Technical Partnerships Manager at Jaguar TCS Racing. and Mark Whalley, Manager at Vertica. The trio of data experts shed light on the use cases of advanced analytics through the lens of Vertica's technology partnership with Jaguar TCS Racing. From looking at the current state of the industry to analysing the technical implementation of software into an organisation, you can expect a deep dive into the advanced analytics methods and tools driving the future of data.

Discover:

How Vertica is using advanced analytics to help businesses accelerate their data analysis

The birth, journey, and growth of the technology partnership between Vertica and Jaguar TCS Racing

Top tips on how to implement advanced analytics

Fivetran automates data movement out of, into and across cloud data platforms. 

It automates the most time-consuming parts of the ELT process from extracts to schema drift handling to transformations, so data engineers can focus on higher-impact projects with total pipeline peace of mind. 

With 99.9% uptime and self-healing pipelines, Fivetran enables hundreds of leading brands across the globe, including Autodesk, Condé Nast, JetBlue, Lufthansa, Morgan Stanley and Pitney Bowes, to accelerate data-driven decisions and drive business growth. 

In this episode of the EM360 Podcast, Analyst Christina Stathopoulos speaks to Fivetran’s Founder and COO Taylor Brown at Big Data LDN to discuss:

• The data space and how Fivetran fits in
• How customers are reacting to generative AI and ML
• Trends set to shake up the industry in 2024 and beyond

Analytical data is the beating heart of enterprise. It's the critical information we collect to improve customer relations, make better business decisions, and find growth opportunities. But to get it business-ready requires careful consideration and preparation for the right analytics solution.

Where There's Data, There's Growth and Profitability

In this podcast, Susan Walsh, Founder and MD of The Classification Guru, walks through the practice of transforming business data through analytics with Glen Rabie, CEO at Yellowfin, and Dan Schafer, Senior Database Administrator at Rocknel.

Learn from the experts how to simplify complex data and transform spreadsheet data for better business use, ways to approach different data sets more effectively, and how to tackle user-adoption problems head-on.

Key Learnings:

What organisations should pay most attention to when selecting a data analytics tool, especially from an implementation perspective

The importance of supporting an organisation after an analysis tool has been implemented

Want to find out more about Yellowfin's approach to transforming business through data? Click here!

Big Data LDN 2024, the UK’s leading data, analytics, and AI event, is less than a week away – promising two days filled with ground-breaking stories, expert insights, and endless innovation.

Taking place at the Kensington Olympia in London on September 18-19, this year’s event features fifteen theatres and over 300 expert speakers sharing insights on some of the industry’s hottest topics – from generative AI to data analytics and privacy. 

With the event less than a week away, EM360Tech’s Head of Podcast Production, Paulina Rios Maya, grabbed Big Data LDN’s Event Director, Andy Steed, for a chat about his expectations for this year’s event and its growing importance in the data world.

In the episode, they discuss: 

• The exciting themes or breakthroughs attendees can expect to see showcased this year
• How Big Data London remains relevant in such a rapidly evolving field
• The unique networking opportunities or interactive experiences attendees have at the conference
• The standout sessions or keynote speakers at the conference

Chapters:

00:00: Introduction to Big Data LDN 2024

01:35: Showcasing Data Stories, Transformations, and Challenges

02:33: The Networking Opportunities with Industry Leaders and Peers at Big Data LDN 2024

05:01: Staying Relevant with a Focus on Generative AI and Real-World Use Cases

06:55:The Importance of Data Events for Community Building and Learning

About Big Data LDN 2024

Big Data London is the UK's largest data and analytics event, attracting over 16,500 visitors each year. Taking place at the Olympia in London on September 18-19, this year’s event features fifteen theatres and over 300 expert speakers across the two-day conference. 

Attendees can meet face-to-face with tech providers and consultants to find solutions to your data challenges and view the latest product releases and software demos to enhance your business' data capabilities.

It’s also a great opportunity for attendees to strengthen their business network with new and existing partners, and immerse themselves within the data community and network with speakers, colleagues and practicioners all in 2 days at Big Data LDN.

This week's guest is making his third appearance in our 12 part series with Cloudera.

In this podcast, Scott Taylor welcomes back Paul Mackay, EMEA Cloud Lead from Cloudera, to lend his expertise on how CDP is driving business transformation with cloud-native data and analytics. Paul appeared in episode 1 and episode 7 to lay the foundations of what enterprise data cloud is and explain the benefits of hybrid cloud strategies. This time, he draws on examples from major banks, telcos, and manufacturers to explain some of the use cases that are currently being delivered on CDP.

Next week's final episode: GO ALL IN ON DIGITAL

Make sure you're subscribed so that you don't miss an episode of this fantastic series.

Data has become a valuable asset for businesses in every industry. In particular, it enables organisations to fine-tune their strategies, deliver better customer experience, and much more. As a result, cloud has become increasingly commonplace within enterprise environments. Simultaneously, Internet of Things (IoT) has also grown in popularity and will continue to do so as our future becomes increasingly connected.

In light of this, Ronald van Loon, Director at Adversitement, speaks with Hannu Valtonen, VP Product & Co-founder at Aiven, to explore real-time data's role in application development in the cloud. Firstly, Hannu delves into how companies use data in store and in operation for a competitive advantage. He then goes onto outline how organisations can use this to deliver a better customer experience.

Data management is essential for the enterprise to get right, especially now as firms across all sectors are collecting and using vast amounts of data. 

But what exactly is good data management? Why do we need it? And what are some of the unacknowledged ramifications that have serious impacts on our day-to-day lives?

In this episode of the EM360 Podcast, Analyst Doug Laney speaks to Misha Kapushesky, CEO at Genestack and Vivek Iyer, Team Lead, Human Genetics Informatics, from the Wellcome Institute, to discuss:

• What makes good data management
• How data impacts everyday life
• Driving behavioural and cultural change

In an era dominated by the relentless surge of information, data has become the lifeblood of modern businesses and organisations. As the volume, variety, and velocity of data continue to escalate at an unprecedented pace, the role of data leaders has become increasingly pivotal. 

These architects of the digital realm are entrusted with the formidable task of not only harnessing the power of data but also steering their organizations through the complex and ever-evolving data landscape.

In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Niamh O’Brien, Senior Manager of Solution Architecture at Fivetran to discuss:

• Challenges faced by data leaders today
• Becoming GenAI ready
• The big opportunity for CDOs and their teams