In the second episode of Data Chatter Season 2, Aswin Saravanan shares how the data -> impact value-chain works, his framework to guide decision making for business leaders and challenges with fragmented data along with tips on navigating the same.
In Episode 1 of Data Chatter Season 2, meet Liz Gebhard, the Interim Transformation Officer at World of Books. She previously spent a decade in leadership roles at Amazon. Liz shares her storied experience with data, beginning her corporate career at Target in supply chain and technology development during the early 2000s era of nascent online retail. Her move to Amazon marked a significant shift, requiring her to learn SQL and self-serve data due to the culture’s reliance on data-driven decisio...
Data Chatter is back with a (belated) second season! In this season, Karthik Shashidhar, now cofounder and CEO of Babbage Insight, chats with business leaders on how they make decisions using data, and how they hope AI will transform the industry
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...
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 Ti...
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 C...
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...
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 ...
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 mo...
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 gue...
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 ...
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 ...
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....
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 rel...
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...
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 Rese...
“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...
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 t...
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 dat...
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...
