There is a trend occurring in big data analytics that will unlock countless treasures. Data mountains have turned into data streams. Streams that are mapped, filtered, merged, reduced, flattened, aggregated and visualized. The cutting edge is not limited to graphical rendering of what we already know or suspect but patterns and mysteries that lay in hidden patterns poised to shock, awe, heal and even harm. The legacy options like warehouses, marts, cubes and pivots still have a role to play but the modern frontier describes phenomena like fast data or accelerated data. Data can also be slow or dark. Where data was once processed, it is now streamed. Our analytics move from the static to the dynamic to the chaotic and the predictive.

What does this mean for programmers?  Data analytics will move away from static data arrays to data interaction within data streams. Static, object oriented programing no longer addresses the demands for real time data analytics. Web communication will continue to grow whereby more attention is given to payload management and typescript that the browser can understand. Developers will begin to model the processing of the data streams, declare how data streams will interact with each other, and define the interaction methodology, all within a subscription format. Technologies like RXJS, methodologies like functional reactive programming, and data stream interaction with observables through JavaScript are the future of data analytical programming.

Behaviors mined from a steady stream of data will be discovered in real time whereby server notifications are sent to browsers without the browser making the request. Mobile apps aren’t going away anytime soon; but, browser advancements will make building IOS apps less necessary.