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In the two decades since author Michael Lewis published Moneyball: The Art of Winning an Unfair Game, his book has become the analogy for a data-driven business. It’s the story of how Billy Beane, General Manager of the Oakland Athletics, used data to recruit undervalued baseball players and build a dominant team, despite having the second-lowest payroll… Continue reading From Moneyball to DataChat: The Evolution of Analytics
One of DataChat’s key differentiators is traceability. Our platform automatically documents every step it takes to produce your analytics, in plain English. That way anyone can verify what DataChat did, regardless of their technical knowledge. We think this traceability is crucial to making data-driven decisions confidently. If you don’t know how the proverbial sausage was… Continue reading Unnesting the Nest: The DataChat Flattening Technique to Humanize Complex Analytics
How a Fortune 100 tech company used DataChat to get visibility into $15 billion worth of contracts—before they renewed Invisible billions One of the world’s most successful tech companies had a problem with untraceable spending. Business units at this Fortune 100 enterprise would submit procurement requests (PRs) to sourcing managers, who would then find vendors… Continue reading A $15 Billion Data Problem
We asked DataChat’s co-founder, Rogers Jeffrey Leo John, to tell us about the origins of the company. What was missing from the marketplace? How has DataChat pushed the envelope? Q: How did DataChat start? The idea formed after Jignesh Patel, our co-founder, was a visiting scientist at Pivotal Labs. He observed their data teams and… Continue reading Unveiling DataChat: A Captivating Q&A with Co-Founder Rogers Jeffrey Leo John
In June, we had the privilege of presenting our groundbreaking research paper, “DataChat: An Intuitive and Collaborative Data Analytics Platform,” at the SIGMOD conference. Our paper introduced the DataChat platform, designed to provide an intuitive, powerful, and accessible data science approach to all users. Since its unveiling, our approach has garnered substantial interest from various industries, prompting… Continue reading Enhancing Data Analytics with DataChat: A Look at Recent Improvements
This post is part of our data science and analytics learning series. Please contact us if you have a topic you would like us to cover! In data science, we want to avoid GIGO, or Garbage In, Garbage Out. In other words, your output can only be as good as your input. We build… Continue reading 5 Tips for Preparing Your Data for Machine Learning
Enable everyone, regardless of technical skills, to transform complex data into confident decisions
