Business intelligence (BI) has long been associated with applications: dashboards and user tools for viewing and interacting with reports, and analyst tools for querying databases, analyzing, and modeling the results.
Today a large number of these tools and software are designed to make it easier to visualize data and digest insights from it, both proprietary and open source.
In many industries, the role and act of BI analysis has become a necessary standard for delivering large amounts of data, and interpreting what that data is telling us. Therefore it is a valuable advantage to have experience or formal education in the field of BI / data analysis, it is of great help that we also see the simplification of the BI tools which are drastically assisting users in daily operations.
The reliance on data, in any industry, is growing exponentially. Virtually any application of data requires analytics or BI to extract meaning and subsequent action. Analysis and knowledge extraction from data has been traditionally an isolated area, mainly achievable by Statisticians or Mathematicians. Nowadays, with so much data available in every field and every industry the use of data is becoming more and more common. For example various fields such as law, financing, HR, marketing, and media have employees learning about analytics and basic statistics in order to be able to do their job. This demand is driving BI tools to become more user friendly; understandable by even the novice analyst.
As an outcome of the progress of BI thus far (from the original data base management to today’s embedded analytics), and considering the growth of data available and the Internet of Things (IoT), this is how I see the future trend for BI:
Most BI tools struggle to handle unstructured data, which means that a substantial portion of available data remains unanalyzed, however there is great progress with technologies that handle ETL and Non- Relational Databases that at some point will merge with BI.
Data generation and data storage is growing exponentially, especially unstructured data. BI tools and applications will gain data processing power in order to sufficiently digest, manage and analyze larger amounts of data than what is currently possible. This data processing power will work cross-platform and be tool/application exchangeable. Despite some limitations BI tools work with multiple data sources at the same time, but different among themselves (Oracle, Access, SQL, etc.). I suspect future tools will work with any data stored in any platform, and run by any application (software).
The use of historical data to identify trends and make automated guesses and recommend actionable steps about future actions is becoming a strong trend. This is called prescriptive analytics. Machines will do the work and humans will watch from the sidelines.
It’s an exciting time for BI, there are many advances to look forward to. It will be interesting to see the evolution and where it takes us. What sort of improvements or features would you like to see?