Integrated Business Intelligence on Big Data Stacks.
Read the new post from our CTO on the changing landscape of B.I and analytics on Big Data stacks.
Until recently Big Data stacks have primarily focused on SQL capabilities. Of late, support for Business Intelligence(BI) applications and workloads is coming into focus for both Big Data providers and consumers.
BI is not just faster, better SQL: in its essence BI is about enabling the Business Analyst to express Business Logic in the language of Business(Dimensions, Facts, Hierarchies, KPIs, Trends etc). In this vein, a BI platform is about simplifying the process of developing and deploying Business centric Analytic solutions, just as a Database simplifies and standardizes building Data Solutions.
Integrated Data Platform: There are many time tested BI platform architectures, one of which is a single Data Platform that caters to all Analytical needs: Reporting, BI, and Data Science. This architecture is well-suited for the Big Data arena as many system capabilities like elasticity, resource management are available in a generic fashion. Apache Spark makes this an even more compelling option with its highly extensible architecture: at the Language level, at the Translation/Optimization level, and at the Runtime level.