The term ‘Business Intelligence’ was used as far back as 1865 by Richard Millar Devens in the Cyclopædia of Commercial and Business Anecdotes to describe how a banker increased profits by acting upon information before his competitors could. This language was used sparingly until the 1980’s when data warehouses, OLAP and information systems gained prominence. Then Gartner analyst Howard Dresner proposed Business Intelligence as an umbrella term to describe how best practices and technology could be employed to improve decision-making. Fast forward ten years and the verbiage is widespread.
Business Intelligence and analytics tools have been such game-changing technologies because they help businesses improve their decision-making. In the end, it’s that process that decides success or failure. Based purely on how prevalent BI has become in the enterprise arena, the common sense observation is that it has become wildly successful at producing actionable insights. However, given the massive proliferation in data volumes, sources and collection techniques, and the expansion and availability of new technologies, we can comfortably say that Business Intelligence as we’ve known it since Richard Millar Devens first uttered the words, is dead.
When we think about traditional BI, we think about an IT-led coalition of analysts that pluck and pull data from their data warehouse to load into a reporting solution and act as a system of record keeping. The truth is, these practices are no longer relevant for a large majority of analytics adopters, as new approaches to generating insights have roots deeply ingrained in self-service and end-user autonomy. Modern BI practitioners don’t necessarily have any connection to IT, and even fewer have undergone technical training.
Centralized provisioning and tightly governed platforms are a thing of the past, and are being counterbalanced and replaced by tools and processes that promote analytical agility and business user autonomy. According to analyst house Gartner, Inc., the majority of solution buying in BI and analytics now comes in the form of modern platforms which focus on user engagement, and this fact has essentially reorganization the vendor landscape. We can gain a lot of insight into the state of current technology markets based on what software providers offer their customers, and this couldn’t be made any more obvious.
The practice of Data Analytics in 2017 is largely dominated by self-service functionality, providing a wide variety of business users with forward-thinking software tools and a state of data democratization that enables on-the-fly analysis for evolving business needs.
The next wave of BI, already dubbed ‘BI 2.0’ will zone in not on the analysis, but the data itself. The focus will increasingly be put on data volumes and the complexities of modern digital business. This includes the incorporation service-oriented architecture, bringing a different approach to the table. Anodot’s VP of Customer Success Avi Avital provides his view on the future of BI: “Handling scale requires not just new tools, but a fundamental shift in how we approach the task. Instead of just looking at the aggregate data, there must be a new appreciation for the anomaly and its impact on a business.”
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