AI For Compliance: What, Why, How
With the constant rise and use of technology, Artificial Intelligence (AI) has become a great companion to compliance. Compliance is one of the biggest playing field...
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How To Write A Technical Dissertation
Technical dissertation writing sometimes seems impossible until it is done. A dissertation is among the lengthiest tasks that can take months to get completed. Thus, it e...
Fallacy of Becoming Data-driven – Part 1: Becoming Value-obsessed
I’m sure we all remember the story of “The Little Engine That Could.” A little railroad engine was built for pulling a few cars on and off the switches. When more p...
DSC Weekly Digest 4/12/2022: Demographics Drives Analytics
The Los Angeles Times recently reported on a growing problem not just for California School Districts, but across much of the Northern Hemisphere: The number of children ...
Drag-and-drop Data Pipelining: The Next Disruptor in ML
Recent advances in machine learning (ML) and artificial intelligence (AI) technologies are helping enterprises across industries quickly move from their use cases from th...
6 Business Applications that Badly Need Better AI
The success and growth of AI is undeniable. Yet there are still basic tasks performing poorly, despite or because of automation. In some cases, you can blame reliance on ...
Public wary of Meta’s Metaverse vision
There are signs that Meta’s plans for the metaverse is faltering, including plummeting stock prices and the company’s announcement that it may withdraw from the EU ma...
NLQ: Why You Might Not Need To Call A Data Analyst Anymore
NLQ or Natural Language Query or Text-to-SQL or NL2SQL is an arm of computational linguistics, that helps users to fetch required data, visualizations, and insights, from...
Building a Data Products-centric Business Model
When I was the Vice President of Advertiser Analytics at Yahoo!, I painfully learned that my targeted user personas (Media Planners & Buyers and Campaign Managers) di...
Data Discovery for ML Engineers
Real-world production ML systems consist of two main components: data and code. Data is clearly the leader, and rapidly taking center stage. Data defines the quality of a...