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Business Intelligence: Industry Predictions for 2016
An annual report from Tableau Software lists the top ten trends of business intelligence for 2016.
Listed below are the predictions for 2016 and a summary of predictions from 2014 and 2015.
| Predictions for 2014 Trends | Predictions for 2015 Trends | Predictions for 2016 Trends |
| The End of Data Scientists | Governance is transformed | Governance and Self-Service Analytics Become Best Friends |
| Cloud Business Intelligence Goes Mainstream | Social Intelligence is a Competitive Advantage | Visual Analytics Become a Common Language |
| Big Data finally Goes to the Sky | Analytics Emerge Across the Organization | The Data Product Chain Becomes Democratized |
| Agile Business Intelligence Extends its Lead | Communities Differentiate | Data Integration Gets Exciting |
| Predictive Analytics will move Into the Mainstream | Everything Integrates | Advanced Analytics is no Longer Just for Analysts |
| Embedded Business Intelligence Puts Analytics into the Path of Everyday Business Activities | Cloud Analytics isn’t just for Cloud Data anymore | Cloud Data and Cloud Analytics Take Off |
| Storytelling becomes a priority | Conversations with Data Replace Static Dashboards | The Analytics Center of Excellence (COE) become Excellent |
| Mobile Business Intelligence becomes the primary experience for leading-edge organizations | Data and Journalism Complete Their Merge | Mobile Analytics Stands its Own |
| Organizations begin to analyze Social Data in Earnest | Mobile matures | People Begin to Dig Into IoT Data |
| NoSQL is the new Hadoop | Smart Analytics Start to Emerge | New Technologies Rise to Fill the Gap |
It’s not surprising to see that “Visual Analytics Become a Common Language” is a predicted trend for this year, 2016. As more and more businesses adopt business intelligence for informed decision making, more employees are going to be required to be involved with the data. Having easy-to-decipher visual representations of the data allow more employees to be engaged with the data, rather than just the IT team or the one, in-house data scientist.