Many business intelligence (BI) vendors and CIOs have positioned big data analysis to focus on data reporting. They then collect and store as much data as they can hoping someone, a data scientist or a team of specialists, can analyze the data and make sense of it.
However, the industry hasn’t been very good at deciding what data to keep and what to throw out.
What’s in Store for Data Discovery?
Data discovery will soon eclipse data reporting as the focus of BI and big data analytics, according to a recent report by Gartner Inc.
“By 2015, the majority of BI vendors will make data discovery their prime BI platform offering, shifting BI emphasis from reporting-centric to analysis-centric,” the report notes.
Gartner predicts that this trend will be powered by smarter data discovery techniques rather than sheer computing power. Companies will do this by moving away from a reliance on IT and emphasizing analysis led by business users.
“IT will focus most of its effort on data modeling and governance,” according to Gartner. “As a result, data discovery will displace IT-authored static reporting as the dominant BI and analytics user interaction paradigm for new implementations by 2015.”
A Domino Effect Caused by User Shifts
The current base of business users with access to analytics and BI is only 30%. However, the shift toward data discovery means the number of people with access to BI and analytics will increase.
Over the next few years, the model of simply collecting and reporting on data will be replaced with something that truly analyzes and makes sense of data. Data discovery revolves around the ability to integrate multiple data sources, analyze the data thoroughly, and display it interactively.
The ability to capture markets is crucial for companies that want to make an impact in the BI software and analytics market. User-friendly software solutions that are accessible by a less-technical audience (not just IT) will be a crucial step forward in capturing markets.
Software like TIBCO Spotfire enables business users to compile data from whatever data sources they want, pull the information into a cohesive view of related data, and view it through interactive dashboards and interfaces.