Business Intelligence 2.0: Simpler, More Accessible, Inevitable
Say goodbye to complicated interfaces, disconnected analytics and shelfware. An emerging era for BI will bring simplicity, broad access and better ties between analysis and action.
BI 2.0 will disrupt the BI industry in quite a few ways, and foot-dragging can be expected. Some more obvious effects will be:
Convergence: The unnatural separation of BI technology and staff from the rest of the operations of the enterprise will fade as BI becomes ubiquitous and mission-critical.
Batch Data Warehousing: This activity will continue, but at a reduced rate as the need for information exchange with partners, customers, regulators and other stakeholders become a 24/7 proposition. Faster computers, more memory and better metadata (semantic models) will support better data comprehension and reduce the need for data integration.
Methodologies: Data warehouse methodologies that have been laid down and tuned for the past decade will take a while to pry loose from the collective consciousness. Many best practices will be largely invalidated by BI 2.0 and new ones will emerge, but conventional wisdom is tenacious. Expect a lot of friction here. Remember 3NF versus Star Schema MOLAP versus ROLAP?
The "Pyramid": This model of BI usage needs to be scrapped. The idea of separating people into bands of a pyramid based in whether they are power users or report readers never worked in the first place. Even "unsophisticated" users had a need to do a little modeling once a while, that's why they have Excel. In BI 2.0, roles are infinitely malleable and a person can operate in different roles simultaneously.
BI Licensing: It's very likely that BI software sales and licensing will evolve, too. If organizations can transform from 100 BI users to 10,000 in a month, the market will not allow the incumbents to reap a 100x windfall in revenue. Open-source and On-Demand channels will put more pressure on the traditional vendors to retire expensive, per-seat perpetual licenses.
Data Comprehension: Data integration is a painstaking process that is sifted through by people, and then the process is automated with a tool. Tools are emerging that can take over the tedious integration work, at least to some extent, and the rise of Master Data Management (MDM) hubs can further reduce the time-consuming work load. Coupled with better semantics-based metadata, on-the-fly data comprehension solutions -- for both internal data and for connected flows of data from partners will be emerging within the next 12-18 months.
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