Explore every episode of Data Chatter
| Pub. Date | Title | Duration | |
|---|---|---|---|
| 22 Jun 2021 | 1. Excel-lent Graphics | 00:57:34 | |
When we read or talk about “data science”, most of the talk is around modelling - the maths behind it, the “cool” modelling techniques, what kind of CPUs or GPUs are required, and all that. What we normally talk less about is how data science interacts with business. In this inaugural episode of Data Chatter, I talk to S Anand, co-founder and CEO of Gramener, about this so-called “interaction layer”. Our conversation is almost completely focussed on two such interfaces - Microsoft Excel, and data visualisation. We talk about various aspects of what it takes to communicate data to business, and pros and cons of different tools. Anand is a co-founder of Gramener, a data science company. He leads a team that automates insights from data and narrates these as visual data stories. He is recognized as one of India's top 10 data scientists, and is a regular TEDx speaker. Show Notes: 00:03:40 - On how Anand was “always a data guy” Links: Gramener: https://gramener.com Data Chatter is a podcast on all things data. It is a series of conversations with experts and industry leaders in data, and each week we aim to unpack a different compartment of the "data suitcase". | |||
| 02 Aug 2021 | 7. From Random Walks to Random Forests: Analytics and data science on Wall Street | 00:49:00 | |
One of the first industries to extensively use advanced maths to do better was financial services. Ever since Fischer Black and Myron Scholes published their seminal paper on option pricing in 1973, Wall Street firms hired mathematicians and scientists by the droves, getting them to model asset prices in order to get an edge in the market. Even today, top hedge funds such as Renaissance, Citadel and Two Sigma prefer to hire scientists rather than finance professionals to manage their portfolios. However, in the last decade or so, as Data Science and Artificial Intelligence have taken over the rest of the world, Wall Street has not maintained its leadership position in the use of maths to make money. How and why did this happen? In order to understand this, we talk to Hari Balaji, co-founder of Romulus, an award winning unstructured data automation platform for Financial Services firms. Prior to founding Romulus, Hari spent a decade in quant & data roles at Goldman Sachs across Hong Kong and Singapore. Hari is an alumnus of IIT Madras & IIM Ahmedabad. Show Notes 00:03:15 - What is data science and what is artificial intelligence? 00:10:40 - What Hari’s company does 00:14:00 - Toolbox versus hammer-nail approaches 00:15:00 - This history of math in the financial services industry 00:28:45 - Wall Street is never a first mover but a great follower 00:33:30 - How Wall Street uses data science nowadays 00:41:00 - Why most innovations have happened at smaller firms 00:44:00 - Why the financial industry doesn’t behave like the Tech world Data Chatter is a podcast on all things data. It is a series of conversations with experts and industry leaders in data, and each week we aim to unpack a different compartment of the "data suitcase". | |||
| 19 Oct 2021 | 14. Programming Data Science: R vs Python | 01:00:34 | |
There are two dominant programming languages used for data science nowadays - R and Python, each having its own set of loyal users. Both have their own strengths and weaknesses. In this episode, we look at what each langauge is good and bad at, what kind of people are more likely to use each, and how being able to program in both and switch seamlessly can indeed be a superpower. Today’s guest is Abdul Majed Raja RS, a Data Scientist at Atlassian. Abdul Majed likes to call himself an Analytics Consultant with over a decade of experience helping organisations solve their business problems. He's also a Content Creator trying to help newcomers navigate the Data Science space easily and learn continuously. You can find him on Twitter and on Youtube at 1littlecoder. Show Notes: 00:03:00: How Abdul got into analytics I don't like Notebooks - Joel Grus - Interface between R and Python - reticulate. Julia Silge Youtube Channel for latest Tidymodels tutorials Advantages of Using R Notebooks For Data Analysis Instead of Jupyter Notebooks - Max Woolf Data Chatter is a podcast on all things data. It is a series of conversations with experts and industry leaders in data, and each week we aim to unpack a different compartment of the "data suitcase". The podcast is hosted by Karthik Shashidhar. He is a blogger, newspaper columnist, book author and a former data and strategy consultant. Karthik currently heads Analytics and Business Intelligence for Delhivery, one of India’s largest logistics companies. You can follow him on twitter at @karthiks, and read his blog at noenthuda.com | |||
| 16 Aug 2021 | 9. Making Data Science Work | 00:49:27 | |
Everyone wants to do “data science”. Companies want to introduce “machine learning” in their products. Most fund raises by startups nowadays are accompanied by a statement of intent to invest in data, and data science. Back in 2006, mathematician Clive Humby, who was working for Tesco, made the statement that “data is the new oil” (to give context, we were in the middle of a massive bull run in oil prices then). And so companies are investing in data. However, just investing in data capture and hiring data scientists is not enough for a company to get value. It is important to structure the relationship between data and business, and how the data team is managed, in the right way for the data team to be effective. Today’s guest is Anuj Krishna. Over the last 14 years, Anuj has worked with multiple enterprises on both, the translation side as well as the execution side of analytics. He has helped create standard processes for analytical problem solving that are in use in multiple enterprises. Anuj was an early employee of MuSigma, and then went on to co-found TheMathCompany. In his current role, Anuj is Head of Assets at TheMathCompany, and is also responsible for operations related to TheMathCompany. Show Notes: 00:03:00: How business and data science currrently interact 00:06:30: Translating from analytics to business 00:13:00: Structuring a data science team 00:22:00: Data science versus business intelligence 00:29:00: How can a business person get best value out of a data team? 00:32:00: Why data science projects fail 00:38:30: Evolution of the data science industry over the last decade Links: Data Chatter is a podcast on all things data. It is a series of conversations with experts and industry leaders in data, and each week we aim to unpack a different compartment of the "data suitcase". | |||
| 22 Dec 2021 | 15. On Data And Journalism | 00:50:04 | |
There is a conception, or misconception, that journalists are not good at maths. It is rather common to see newspaper headlines and graphics that make basic mathematical and logical errors. On the other hand, in the last decade or so, we have seen a massive rise in “data journalism”. With more and more data being available, journalists are able to write stories exclusively based on data. How do these two square off? To answer this, we have Sukumar Ranganathan, editor in chief of the Hindustan Times. He was previously editor of Mint, of which he was one of the founding editors. It was while he was at Mint that he gave a big push to the then nascent field of “data journalism”, inviting writers such as HowIndiaLives, Rukmini S and myself to write data-backed pieces for Mint. He has previously worked in editorial leadership roles at The Hindu Businessline and Business Today. Sukumar has degrees in chemical engineering, maths, and business administration, and is interested in mathematics, science and technology, the history of business, new media, and data-based political journalism. He reads and collects comic books and is an amateur birder. He tweets under the ID @HT_ed Show Notes: 00:03:15: Are journalists really bad at maths? Data Chatter is a podcast on all things data. It is a series of conversations with experts and industry leaders in data, and each week we aim to unpack a different compartment of the "data suitcase". The podcast is hosted by Karthik Shashidhar. He is a blogger, newspaper columnist, book author and a former data and strategy consultant. Karthik currently heads Analytics and Business Intelligence for Delhivery, one of India’s largest logistics companies. You can follow him on twitter at @karthiks, and read his blog at noenthuda.com | |||
| 12 Oct 2021 | 13: Is this real, Data Science, or is it a fantasy? | 00:46:20 | |
Over the last decade, we have seen tremendous advances in big data, data science, artificial intelligence and machine learning. Every compnay wants to be a tech-first comapny now, and wants to “do data science". Companies can probably double their valuation by just adding a “.ai" to their names. Companies that actually use artificial intelligence and machine learning maybe have an even higher premium on their valuations. However, is Data Science worth the hype? Is AI going to take over the world? And why is data science being eaten by computer science? What happned to classical analytics, operations resarch and statistics? This week’s guest is someone who did data science even before the phrase had b een invented. Amaresh Tripathy is SVP and Analytics Business Leader at Genpact. Till recently he was a Partner with PWC, leading the firm’s Data & Analytics Consulting, and helped build a $500mm business. Previously, Amaresh founded and co-led the Information and Analytics Practice for Diamond Management & Technology Consultants, and also serves as Adjunct Professor of Data Science and Business Analytics at the University of North Carolina, Charlotte. Amaresh has helped Fortune 500 companies in multiple industries (healthcare, retail & consumer, communications) to help define and implement their analytics and AI strategies and institutionalize data enabled decision making. He has led organizations to help embed analytics in their front, middle and back office functions and manage the change process. Show Notes: 00:03:00: Definitions - data science, artificial intelligence, machine learning, etc. Links: Thomas Davenport and DJ Patil on Data Science as the “sexiest job of the 21st century” (2012 article) Hal Varian on statistics as a “sexy job” Data Chatter is a podcast on all things data. It is a series of conversations with experts and industry leaders in data, and each week we aim to unpack a different compartment of the "data suitcase". The podcast is hosted by Karthik Shashidhar. He is a blogger, newspaper columnist, book author and a former data and strategy consultant. Karthik currently heads Analytics and Business Intelligence for Delhivery, one of India’s largest logistics companies. You can follow him on twitter at @karthiks, and read his blog at noenthuda.com/blog | |||
| 09 Aug 2021 | 8. Data Science For Babies | 01:02:36 | |
There is an ongoing debate on when children should be taught to code. There is one group of people which insists that computer programming is a lifelong skill, and is best taught early. The opposing argument is that coding is possibly a fad, and that children will learn it when they have to. But what about data science? The field itself is less than 15 years old. Does it make sense to introduce it to children at an early age? According to Rahul Raghavan, the guest on this episode, the answer is an overwhelming “yes”. Rahul is a Montessori educator and founder of pep School v2, a Montessori school in Bangalore. Before getting into education, he was in the corporate world, working in impact investing (with VentureEast) and then with Amazon. You can follow him on Twitter at @rahulrg Show Notes: 00:02:55 - Introduction to the Montessori method Links: Commentary on the viral video on “why should I learn maths?” Florence Nightingale’s chart on causes of death in the Crimean War Geometric intuition on how sqrt(2) + sqrt(3) is approximately equal to pi Data Chatter is a podcast on all things data. It is a series of conversations with experts and industry leaders in data, and each week we aim to unpack a different compartment of the "data suitcase". | |||
| 12 Jan 2022 | 16. Teaching Data Through Stories | 00:54:38 | |
The phrase “using data to tell stories” is so commonly used nowadays that it runs the risk of becoming a cliche, if it hasn’t become one already. This episode’s guest flips this logic around - instead of using data to tell stories, he uses stories to teach data science! Arvind Venkatadri is a faculty member at Srishti Manipal School of Art, Design and Technology. His research/teaching interests include TRIZ, Computation in R, Design using Open Source Electronics Hardware, and Complexity Science. He is part of the School of Foundation Studies at SMI. This is a very wide ranging conversation. We talk about, among other things, The Three Musketeers, Lawrence of Arabia and Legally Blonde. We talk about how Arvind leverages all of these to teach his students data science and logic and game theory. At a time when the field of data science is rife with “pile stirring”, where a large section of practitioners treat it as an extension of software engineering, Arvind’s approach, centred on stories and the human experience, is really refreshing. His approach also gives a pointer on how to widen the base in terms of attracting people into data science. I must apologise for one thing - this conversation was recorded during Deepavali in November 2021, so you can occasionally hear the sound of firecrackers in the background. I really hope you can get past that and listen to Arvind’s stories. Show Notes 00:03:00: Arvind’s journey into teaching Data Science in an art school 00:05:45: Teaching data science to art students 00:15:45: Teaching statistics through art and stories. Wassily Kandinsky 00:23:00: Teaching coding through art 00:31:00: Shapes and colours and emotions 00:44:00: Lawrence of Arabia (can’t say more here in the description!) 00:50:00: Data science and the human experience Links: Arvind’s course on R for artists and designers An intro to Wassily Kandinsky's work Data Chatter is a podcast on all things data. It is a series of conversations with experts and industry leaders in data, and each week we aim to unpack a different compartment of the "data suitcase". The podcast is hosted by Karthik Shashidhar. He is a blogger, newspaper columnist, book author and a former data and strategy consultant. Karthik currently heads Analytics and Business Intelligence for Delhivery, one of India’s largest logistics companies. You can follow him on twitter at @karthiks, and read his blog at noenthuda.com | |||
| 14 Sep 2021 | 11. Unknown Unknowns: Risk and Uncertainty | 01:25:14 | |
The fundamental principle underlying all analytics and data science is Probability. And probability was first invented, or should I say discovered, to assess risk. So what is risk? Can we quantify and measure it? How do we handle risk in life? Is risk always bad? Today’s guest on Data Chatter is Bala Vamsi Tatavarthy, who is co-founder and investment advisor at Aravali Asset Management, a global arbitrage fund. Vamsi was my classmate at IIT Madras, where he studied computer science but spent most of his time gaming. He then went to IIM Ahmedabad, where he continued to game heavily and graduated with a gold medal. He now runs a hedge fund, and spends a lot of time gaming. Moreover, he was one of the last traders to trade on behalf of Lehman Brothers, on 15th September 2008. Risk, as you can imagine, is a vast subject, and so this is a long podcast. We talk about measuring risk, problems with too much measurement of risk, how risk can be managed, and all that. We also talk about movies, games, the differneces between poker and bridge and physics envy. Show Notes 00:03:45: Defining Risk, and Lehman Brothers’ collapse 00:09:00: Can risk be created or destoryed? Is it conserved? 00:15:00: Risk, probability distributions and long tails 00:20:45: Uncertainty, volatility and risk 00:28:30: Hedging 00:35:00: Utility functions 00:42:30: Games and risk 00:54:00: Bridge and poker, and finite and infinite games 01:04:15: Ergodicity 01:07:30: VaR, Risk-metrics and Goodhart’s Law 01:14:30: Correlation Links: “Risk once created cannot be destroyed” The Wired article about Gaussian Copula, used to estimate correlations Too Big To Fail, by Andrew Ross Sorkin Data Chatter is a podcast on all things data. It is a series of conversations with experts and industry leaders in data, and each week we aim to unpack a different compartment of the "data suitcase". | |||
| 30 Aug 2021 | 10. From Science To Data Science | 00:59:42 | |
When I was graduating college in the mid 2000s, the word in job descriptions that most commonly appeared alongside “data” was “analytics”. However, around 2010, the phrase “data science” (HBR link) got coined, and took over the world in the next five years. Nowadays it seems everyone wants to be a “data scientist” However, where is the science in data science? And why are so many people with PhDs in pure science moving to data science? To understand this better, I bring back one of the old guests of Data Chatter. Dhanya P is an aerospace engineer turned neuroscientiest turned data scientist. She is co-founder of Messy Fractals and Kabaddi Adda, and a Senior Scientist at Sapien Labs. Dhanya talks about her journey from neuroscience to data science, why a PhD is good training for data science, and what the “science” in data science is all about. You can follow Dhanya on Twitter at d2a2d Show Notes: 00:02:30: Dhanya’s journey from Aerospace Engineering to Neuroscience to Data Science Data Chatter is a podcast on all things data. It is a series of conversations with experts and industry leaders in data, and each week we aim to unpack a different compartment of the "data suitcase". | |||
| 05 Oct 2021 | 12. Carts and graphs: Storytelling through maps | 00:50:30 | |
In this edition of data chatter, we will talk about maps. Maps are excellent devices for telling stories. Think of the maps you see around election times that show which parties won seats where. in fact, the first ever scatter plot - Dr. John Snow’s figure of cholera cases in London, was essentially a map. Or think of the famous map of Napoleon’s invasion of Russia. And telling stories through maps is an exercise in data science. Data overlaid on maps can help tell really powerful stories. And as we learn in today’s conversation, the process of mapping is no diferent from the process of data science. Our guest is Raj Bhagat Palanichamy, or as he calls himself “mapper for life”. Raj works for the World Resources Insitute India, where he leads projects on urban development, water resources and transport. In this conversation, Raj talks about his journey into mapping, how he makes his maps, and how WWE influences the way he tells his stories. Highlights: 00:03:00: Raj's journey into the world of maps and mapmaking Raj's 30 day map challenge in 2020 Data Chatter is a podcast on all things data. It is a series of conversations with experts and industry leaders in data, and each week we aim to unpack a different compartment of the "data suitcase". | |||
| 14 Jun 2021 | 0. Trailer | 00:02:20 | |
This is the trailer of "data chatter", a new podcast on all things data. Data Chatter is a series of conversations with experts and industry leaders in data, and each week we aim to unpack a different compartment of the "data suitcase". The podcast is hosted by Karthik Shashidhar. He is a blogger, newspaper columnist, book author and a former data and strategy consultant. Karthik currently heads Analytics and Business Intelligence for Delhivery, one of India’s largest logistics companies. You can follow him on twitter at @karthiks | |||
| 12 Jul 2021 | 4. Itihaasa (history) of Analytics in India | 00:56:44 | |
Analytics and Data Science have become mainstream career choices for graduating students in India nowadays. Analytics companies are nowadays among the largest recruiters at engineering colleges. How did we get here? How did data and analytics become so big, and so mainstream in India? In order to understand this, we need to understand the full history of analytics in India, and this is a story that goes back over a hundred years. Today’s guest is N Dayasindhu, co-founder and CEO of itihaasa Research and Digital. For the past two decades, he has been working on R&D and innovation management especially focused on IT. He is working on the evolution of business and technology focused on IT and related domains in the Indian context. In an earlier avatar, he was a consultant advising MNCs setting up high-performance R&D and IT organizations in India. He was also a researcher in the R&D arm at Infosys and holds a couple of US patents. His research is published in Technology Forecasting and Social Change, Technovation, ACM SIGMIS, etc. He occasionally writes in The Indian Express, The Hindu,The Economic Times, The Hindu Business Line, Founding Fuel, etc. He has guest lectured in the IIMs, the Wharton School at UPenn, NUS Singapore, etc. He has an FPM (PhD) from IIM Bangalore, M.Sc. in Physics from IIT Madras and a B.Sc. in Physics from Loyola College, Chennai. Show Notes: 00:03:20 - PC Mahalanobis returns to India (1910s) 00:12:30 - Using analytics for engineering problems at IISc (1950s) https://ece.iisc.ac.in/index.php/about-us/history 00:23:00 - Analytics in the industry in India (1960s) 00:33:00 - Big tech coming into India (1980s) 00:35:30 - GE sets up captive in India (1990s) 00:39:45 - Analytics services startups; IT firms get into analytics (ealrly 2000s) 00:49:30 - Analytics training institutes in India (2010s) 00:52:00 - How to characterise analytics professionals in India Links Dayasindhu’s interview with L^2, the alumni magazine of IIM Bangalore ---------- Data Chatter is a podcast on all things data. It is a series of conversations with experts and industry leaders in data, and each week we aim to unpack a different compartment of the "data suitcase". | |||
| 19 Jul 2021 | 5. Conjoints and Coupons: The evolution of quantitative marketing | 00:51:04 | |
In business schools in India, there is a misconception that marketing is not quantitative, and that it is for the more “creative” people. However, if you look at its history, marketing has always been a highly quantitative subject. To know more about data and quant in marketing, we talk to Prithwiraj Mukherjee, an assistant professor of marketing at IIM Bangalore. Prithwiraj teaches marketing management and marketing research at the MBA and doctoral levels. His MOOC titled Quantitative Marketing Research is available on EdX and Swayam. He research interests include behavioral decision making where he models biases, and digital marketing where he investigates influencer fraud and clickbait. Prithwiraj has a PhD in marketing from ESSEC in Paris, and degrees in chemical engineering from NITK Surathkal and IISc He can be found on twitter at @peeleraja Show Notes: 00:03:40 - Introduction on numbers in marketing Data Chatter is a podcast on all things data. It is a series of conversations with experts and industry leaders in data, and each week we aim to unpack a different compartment of the "data suitcase". | |||
| 26 Jul 2021 | 6. Manhattans and Moneyball to Kabaddi: How analytics evolves with sports | 01:08:13 | |
For a lot of people, their first introduction to data and analytics happens through sport. Fans have tracked batting and bowling averages for many decades now. In the 1990s, with the coming of satellite TV in India, cricket fans had their first brush with bar graphs and line graphs, with “manhattans” and “worms” respectively. In the last two decades, following the publication of Michael Lewis’s Moneyball, the field of sports analytics hsa exploded. A couple of months before this podcast was released, it was revealed that footballer Kevin De Bruyne had hired a sports analytics firm in order to better negotiate his contract with Manchester City. And along the way, analytics has entered smaller sports such as kabaddi and volleyball. Today’s conversation is a double header, featuring the husband-wife duo of Arvind Sivdas and Dhanya P, who are also founders of KabaddiAdda, a Kabaddi platform. They have worked in analytics in cricket, badminton, volleyball and kabaddi, among other sports. We talk about the evolution of sports analytics, how to quantify “continuous sports”, the role of fantasy sport and several other things. Show Notes 00:02:50 - How they got into sports analytics 00:13:00 - The popularity of “matchups” in sports nowadays 00:20:00 - How Roger Federer used analytics to transform his game 00:25:00 - Why performance analytics has limited impact in (association) football 00:30:30 - The importance of buy-in from the management, and evaluating success 00:32:45 - How Kabaddi has evolved in the last few years 00:37:15 - The parallels between Kabaddi and Basketball 00:46:00 - Analytics in Kabaddi 00:47:00 - Data collection for sports like Kabaddi 00:49:40 - Biomechanics studies in Kabaddi 00:51:30 - How to fund analytics in smaller sports? 00:55:10 - The role of betting and fantasy in developing analytics 00:59:20 - “Moneyball” - where is it being underused, where is it being overused etc. 01:01:00 - Convincing CSK that cricketers peak in their 30s On how CSK won IPL 2018 with "dad's army" Data Chatter is a podcast on all things data. It is a series of conversations with experts and industry leaders in data, and each week we aim to unpack a different compartment of the "data suitcase". | |||
| 05 Jul 2021 | 3. Make BI Great Again | 00:55:41 | |
“Business intelligence” has become a rather unfashionable term in the world of data and analytics. From generating buisness insights from intelligent use of data, it has largely devolved to become a software engineering function - to connect databases to front end tools. However, there is far more to business intelligence than just writing queries. In this episode, Karthik talks to another BI professional - Balaji Kuppuswamy, director of BI products at Youtube. They talk about what BI really is, the skills involved in BI, where it sits in an organisation, and how it can truly add value. Show Notes: 00:03:30 - What is the definition of Business Intelligence? 00:07:20 - BI’s marketing and branding problem 00:12:50 - The role of science in BI 00:15:20 - Interactive dashboards 00:19:00 - What’s it like being a data scientist in BI? 00:27:30 - How Balaji got into BI 00:32:00 - Using BI tools 00:36:00 - Integrating intelligence into BI tools 00:39:00 - Building up a BI team. 00:48:00 - Agile in BI Links: Kaiser Fung’s article on BI and data science Avinash Kaushik on “datapukes" Data Chatter is a podcast on all things data. It is a series of conversations with experts and industry leaders in data, and each week we aim to unpack a different compartment of the "data suitcase". | |||
| 29 Jun 2021 | 2. The Big Deal about Big Data | 00:55:56 | |
Around a decade ago, “big data” became fashionable. There were lots of jokes and memes created around “big data”. Everyone wanted to do big data. Now, in 2021, the hype around big data may have died down, but how to roganise and store data remains an important problem for organistions to solve. Today’s guest is Rangarajan Vasudevan, founder and CEO of TheDataTeam, which builds AI solutions for customer intelligence. We talk about the history of big data, what companies look for when they want to organise their data, technolgies and all such. Show Notes: 00:03:00 - What is Big Data? Data Chatter is a podcast on all things data. It is a series of conversations with experts and industry leaders in data, and each week we aim to unpack a different compartment of the "data suitcase". | |||