Look Ahead

Data warehousing architecture will be rationalized. Granted, the need to process the acquisitions will create some coordination costs and distractions, but it will still unfold, like a caterpillar into a butterfly, into platform-based BI. The acquisitions will actually create opportunities for technology innovation based on the interaction and integration of architectural layers. The front end of the BI system will become more scalable and rich in actionable information, while the back end, the persisting data store itself, becomes more accessible, manageable and useable. Flexible architecture is required to accommodate future business requirements that cannot be foreseen by the conventional wisdom, and the acquisitions will enable the creation of a critical mass of architecture to integrate. This work in progress will make significant headway.

The acquisitions will reduce vendor risk. The end game for best-of-breed, standalone BI tools is now in sight and provides closure for the future of the respective platforms. End-user enterprises and buyers know which vendors take good care of their acquisitions by designing and implementing strategies and roadmaps, which ones merely increase the price of maintenance and which stall in analysis paralysis.

“Data warehousing made simple” becomes even more simple. Consolidation will bring closer to realization the possibility of data warehousing made simple, not as a dream, but as a realistic opportunity. This will occur by means of front-end BI technology integrated with the middle layer of data integration for complex heterogeneous data. In turn, this will benefit the operational business information persisted at the back-end data or information warehouse, where third-generation systems will close the loop back to the front end, optimizing operational processes. In the short term, however, BI platform wars between vendors will be added to data warehousing religious wars and appliance wars. However, these will be lessened by the requirement imposed by end-user enterprises on their best vendors to cooperate for the benefit of clients in the morning, even if they compete in the afternoon.

Figure 1: How frequently do you update or load your data warehouse today? (Percentages will exceed 100 percent due to multiple responses.)

The Convergence of BI and Business Process Management (BPM) Will Accelerate

The convergence of BI and BPM will accelerate as well as reduce uncertainty and risk about the future of the respective BI platforms, making it clear that BI has never merely meant front-end tools. Tools that just run queries and generate reports have become a commodity. Going forward, the ability to deliver insights directly into a business process, along with pattern matching, advanced analytics and nonobvious relationship analysis will be the domains to which incremental value will migrate.

To manage the business, you have to measure it. To measure it, you have to understand it. To understand it, you have to model it. Modeling the business processes will be the critical path to authentic performance (and process) optimization. This will be confrontational to corporate staff members who are comfortable in their functional silos and turf, but it will be liberating to professionals on both business and IT sides of the house who are committed to delivering value to the whole enterprise by way of its customers (or mission in the nonprofit sector).

At the front end, the key technologies include visualization, dashboard/scorecards, predictive analytics and anything that furthers end-user self-service. At the back end, data warehousing will move beyond data integration - in some cases without having fully mastered it - to business and technology integration. In many cases, this will be driven by the requirement to leverage master data management across operational and analytic systems. Business analysts understand what the customer, product, market, etc. dimensions of master data are and will “coach” their IT colleagues if the latter lag behind. In the middle layer, advances in metadata and the usability of business processing (and performance) modeling will enable the different layers of architecture to work with one another while providing key service in data profiling (auditing), data quality and intelligent information integration.

Figure 2: How frequently do you expect to update or load your data warehouse 18 months from now? (Percentages will exceed 100 percent due to multiple responses.)

The End of the Beginning for the Data Warehousing Appliance

The special-purpose, prescriptively defined, shared-nothing database - now commonly known as the data warehousing appliance - will continue to have market traction, with discounting reaching the point of no return. In the short term, this will result in the proliferation of singleton data marts hastily implemented to address a tactical business pain, scratch a technology itch, or demonstrate to a large vendor that it is not the only game in town. However, the intensifying competition will confirm appliance and appliance-like entries from the “big guys”- many already in production in client installations - resulting in the early innovators being leapfrogged by a second wave of major power players.