Data Science Lifecycle revolves around using various analytical methods to produce insights and applying Machine Learning techniques to do the predictions from the colle...
DataOps is the use of agile development practices to create, deliver, and optimize data products, quickly and cost-effectively. DataOps is practiced by modern data teams,...
CPG opportunities in the new normal The COVID-19 pandemic has compelled businesses to shift to virtual marketplaces and CPG has been no different. Consumers are increasin...
My recent journeys have brought me before both technology vendors and technology customers, and interestingly enough, both are asking the same question: “How do we unle...
Blockchain analysis is the process of inspecting, identifying, grouping, modeling, and visually representing the data contained in the blockchain. As we know, blockchain ...
This post continues our discussion on the Bayesian vs the frequentist approaches. Here, we consider implications for parametric and non-parametric models In the previous ...
Judea Pearl (left) and Donald Rubin (right) taken in 2014. Full disclosure: I am a big fan of Judea Pearl and his contributions to Bayesian Networks (bnets) and Causal ...
Data Accuracy: Data accuracy is the biggest challenge for many businesses, having accurate data is useful in all its stages to use. Data results in inaccuracies when it i...
images provided by Draganfly Because COVID-19 is transmitted as an airborne disease, being able to detect when people have symptoms from a distance is important. One ...
Image Source: istockphoto Wouldn’t it be nice to have a sneak-peek into the future of your business to make informed decisions and eliminate guesswork? With the help of...