Big Data Trendz

Thanks to Vinay Shukla( Leading Data Science Product Management at Hortonworks) Our customers increasingly leverage Data Science, and Machine Learning to solve complex predictive analytics problem. A few examples of these problems are churn prediction, predictive maintenance, image classification, and entity matching. While everyone wants to predict the future, truly leveraging Data Science for Predictive Analytics remains the domain of a select few. To expand the reach of Data Science, the Modern Data Architecture (MDA) needs to address the following 4 requirements: Enable Apps to consume predictions and become smarter Bring predictive analytics to the IOT Edge Become easier, more accurate & faster to deploy and manage Fully support  data science life cycle The below diagram represents where Data science fits in the MDA. DATA SMART APPLICATIONS The end-users consumes data, analytics and the results of Data Science analytics via data centric applications (or...