The role and attitude toward business analytics has changed dramatically over the past decade. The proliferation of digital data, alongside the rapid growth of a related ecosystem of business intelligence tools – estimated at $18.3 billion by Gartner in 2017 – has created a sea change.
Powerful analytics capabilities, previously considered a nice-to-have for large enterprises with deep pockets, have become commonplace. Today’s companies have become very good at driving insights from structured data in order to improve business performance. However, as companies outgrow the traditional relational database and data warehouse models and gravitate toward streaming data and data lakes, they often hit a brick wall: Data analysts often don’t possess the engineering skills and tools needed to access, prepare and query this data, resulting in a lack of analytical output.
Author: Ori Rafael