Business intelligence is changing. I've argued in several reports that there is no longer just one intelligence--i.e., business intelligence--but multiple intelligences, each supporting a unique architecture, design framework, end-users, and tools. But all these intelligences are still designed to help business users leverage information to make smarter decisions and support the creation of either reporting or analysis applications.
The four intelligences are:
- Business Intelligence. Addresses the needs of "casual users," delivering reports, dashboards, and scorecards tailored to each user's role, populated with metrics aligned with strategic objectives and powered by a classic data warehousing architecture.
- Analytics Intelligence. Addresses the needs of "power users," providing ad hoc access to any data inside or outside the enterprise to answer business questions that can't be identified in advance using spreadsheets, desktop databases, OLAP tools, data mining tools and visual analysis tools.
- Continuous Intelligence. Collects, monitors, and analyzes large volumes of fast-changing data to support operational processes. It ranges from near real-time delivery of information (i.e., hours to minutes) in a data warehouse to complex event processing and streaming systems that trigger alerts.
- Content Intelligence. Gives business users the ability to analyze information contained in documents, Web pages, email messages, social media sites and other unstructured content using NoSQL and semantic technology.
You may wonder how all these intelligences fit together architecturally. They do, but it's not the clean, neat architecture that you may have seen in data warehousing books of yore. Figure 1 below depicts a generalized architecture that supports the four intelligences.
The top half of the diagram represents the classic top-down, data warehousing architecture that primarily delivers interactive reports and dashboards to casual users (although the streaming/complex event processing (CEP) engine is new.) The bottom half of the diagram adds new architectural elements and data sources that better accommodate the needs of business analysts and data scientists and make them full-fledged members of the corporate data environment.
A recent report I wrote describes the components of this architecture in some detail and provides market research on the adoption of analytic platforms (e.g. DW appliances and columnar and MPP databases), among other things. The report is titled: "Big Data Analytics: Profiling the Use of Analytical Platforms in User Organizations." You can download it for free at Bitpipe by clicking on the hyperlink in the previous sentence.
Since "Multiple Intelligences" framework and BI ecosystem that supports it represent what I think the future holds for BI, I'd love to get your feedback.
Posted October 21, 2011 9:35 AM
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