3. The industry will put reporting and slice-and-dice capabilities in their appropriate places and return to its decision-centric roots with a healthy dose of Web 2.0 style collaboration. It was clear to the pioneers of this industry, beginning as early as H.P. Luhn's brilliant visionary piece A Business Intelligence System from 1958, that the goal of these technologies was to support business decision-making activities, and we can trace the roots of modern analytics, business intelligence, and performance management to the decision-support notion of decades earlier. But somewhere along the way, business intelligence became synonymous with reporting and slicing-and-dicing, which is a metaphor that suits analysts, but not the average end-user. This has contributed to the paltry BI adoption rates of approximately 25% bandied about in the industry, despite the fact that investment in BI and its priority for companies has never been higher over the last five years. Making report production cheaper to the point of nearly being free, something SaaS BI is poised to do (see above), is still unlikely to improve this situation much. Instead, we will see a resurgence in collaborative decision-centric business intelligence offerings that make decisions the central focus of the offerings. From an operational perspective, this is certainly in evidence with the proliferation of rules-based approaches that can automate thousands of operational decisions with little human intervention. However, for more tactical and strategic decisions, mash-ups will allow users to assemble all of the relevant data for making a decision, social capabilities will allow users to discuss this relevant data to generate “crowdsourced” wisdom, and explicit decisions, along with automated inferences, will be captured and correlated against outcomes. This will allow decision-centric business intelligence to make recommendations within process contexts for what the appropriate next action should be, along with confidence intervals for the expected outcome, as well as being able to tell the user what the risks of her decisions are and how it will impact both the company’s and her own personal performance.
6. The undeniable arrival of the era of big data will lead to further proliferation in data management alternatives. While analytic-centric OLAP databases have been around for decades such as Oracle Express, Hyperion Essbase, and Microsoft Analysis Services, they have never held the same dominant market share from an applications consumption perspective that the RDBMS vendors have enjoyed over the last few decades. No matter what the application type, the RDBMS seemed to be the answer. However, we have witnessed an explosion of exciting data management offerings in the last few years that have reinvigorated the information management sector of the industry. The largest web players such as Google (BigTable),Yahoo (Hadoop), Amazon (Dynamo), Facebook (Cassandra) have built their own solutions to handle their own incredible data volumes, with the open source Hadoop ecosystem and commercial offerings like CloudEra leading the charge in broad awareness. Additionally, a whole new industry of DBMSs dedicated to Analytic workloads have sprung up, with flagship vendors like Netezza, Greenplum, Vertica, Aster Data, and the like with significant innovations in in-memory processing, exploiting parallelism, columnar storage options, and more. We already starting to see hybrid approaches between the Hadoop players and the ADBMS players, and even the largest vendors like Oracle with their Exadata offering are excited enough to make significant investments in this space. Additionally, significant opportunities to push application processing into the databases themselves are manifesting themselves. There has never been the plethora of choices available as new entrants to the market seem to crop up weekly. Visionary applications of this technology in areas like metereological forecasting and genomic sequencing with massive data volumes will become possible at hitherto unimaginable price points.
7. Advanced Visualization will continue to increase in depth and relevance to broader audiences. Visionary vendors like Tableau, QlikTech, and Spotfire (now Tibco) made their mark by providing significantly differentiated visualization capabilities compared with the trite bar and pie charts of most BI players' reporting tools. The latest advances in state-of-the-art UI technologies such as Microsoft’s SilverLight, Adobe Flex, and AJAX via frameworks like Google’s Web Toolkit augur the era of a revolution in state-of-the art visualization capabilities. With consumers broadly aware of the power of capabilities like Google Maps or the tactile manipulations possible on the iPhone, these capabilities will find their way into enterprise offerings at a rapid speed lest the gap between the consumer and enterprise realms become too large and lead to large scale adoption revolts as a younger generation begins to enter the workforce having never known the green screens of yore.
10. Excel will continue to provide the dominant paradigm for end-user BI consumption. For Excel specifically, the number one analytic tool by far with a home on hundreds of millions of personal desktops, Microsoft has invested significantly in ensuring its continued viability as we move past its second decade of existence, and its adoption shows absolutely no sign of abating any time soon. With Excel 2010's arrival, this includes significantly enhanced charting capabilities, a server-based mode first released in 2007 called Excel Services, being a first-class citizen in SharePoint, and the biggest disruptor, the launch of PowerPivot, an extremely fast, scalable, in-memory analytic engine that can allow Excel analysis on millions of rows of data at sub-second speeds. While many vendors have tried in vain to displace Excel from the desktops of the business user for more than two decades, none will be any closer to succeeding any time soon. Microsoft will continue to make sure of that.