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Business intelligence market trends and expert forecasts for 2010

Despite the recession, business intelligence (BI) flourished in 2009, but will that BI market trend continue in 2010? See what three industry experts think.

Thanks to increased pressure on companies to do more with less, the business intelligence (BI) market continued...

to grow in 2009. But will last year's popularity of BI software and platforms carry over to 2010? Three industry watchers weigh in with their forecasts for the BI market in 2010.



Wayne Eckerson, TDWI

Wayne Eckerson
Director of research and services for The Data Warehousing Institute


  • Departmental BI stirs the pot. Given the continued tight economic outlook, BI vendors offering faster, better, cheaper solutions built on some combination of Web 2.0, in-memory, cloud or columnar databases will gain traction in the small and medium-sized business market as well as departments in larger companies. These low-cost solutions are already putting significant pressure on enterprise BI vendors to respond with low-cost options of their own to protect their flanks.


  • Enterprise BI adopts analytics and near-real-time delivery. Enterprise BI vendors continue to add modules to their comprehensive BI stacks, focusing in 2010 on analytics and near-real-time data delivery. Analytics -- meaning both enhanced ad hoc reporting and data mining -- has fueled a number of acquisitions already (e.g., IBM buying SPSS), and operational BI continues to make change data capture and trickle feed adapters offered by data integration players hot commodities.

    James Kobielus, Forrester Research
    James G. Kobielus
    Senior analyst at Cambridge, Mass.-based Forrester Research covering BI and data warehousing


  • Self-service operational BI puts information workers in driver's seat: Enterprises have begun to adopt self-service BI to cut costs, unclog the analytics development backlog, and improve the velocity of practical insights. Users are demanding tools to do interactive, deeply dimensional exploration of information pulled from enterprise data warehouses, data marts, transactional applications, and other systems. In 2010, users will flock to self-service BI offerings as the soft economy keeps pressure on IT budgets. Also fueling this trend is the increasing frustration that information workers feel in the face of long backlogs on seemingly mundane BI service requests. In the coming year, BI software as a service (SaaS) subscription offerings will be particularly popular, in a market that has already become fiercely competitive, and so will the new generation of BI mashup offerings for premises-based deployment, especially mashup-oriented BI tools from IBM Cognos and Microsoft.


  • User-friendly predictive modeling comes to the information workplace. Predictive analytics can play a pivotal role in day-to-day business operations. If available to information workers -- not just to Ph.D. statisticians and professional data miners -- predictive modeling tools can help businesspeople continually tweak their plans based on flexible what-if analyses and forecasts that leverage both deep historical data and fresh streams of current event data. In 2010, user-friendly predictive modeling tools will increasingly come to market, either as standalone offerings or as embedded features of companies' BI environments. Many BI vendors will add predictive modeling to their current offerings -- most notably, IBM will converge its Cognos BI and new SPSS data mining offerings -- with a focus on mass-market usability. By the same token, established predictive modeling vendors such as SAS, IBM SPSS, KXEN, Angoss, and Portrait Software will highlight and deepen their existing usability features, such as wizard-driven automation and interactive visualization, to speed information workers through the complex steps for building, validating and exploring predictive models. Just as significant, in-memory BI clients -- such as those from TIBCO Spotfire and QlikTech --provide an important alternative to traditional data mining tools for subject matter experts who wish to explore a multivariate data set from all angles without having to do heavy-hitting data preparation, clustering and classification beforehand.


  • Advanced analytics sinks deep roots in the data warehouse. Advanced analytics demands a high-performance data management infrastructure to handle data integration, statistical analysis, and other compute-intensive functions. In-database analytics is an emerging practice under which those and other resource-intensive processes can be parallelized and thereby accelerated across one or more data warehousing nodes. In-database analytics enables flexible deployment of a wide range of resource-intensive functions, such as data mining and predictive modeling, to a cluster, grid or cloud of high-performance analytic databases. In 2010, in-database analytics will become a new best practice for data mining and content analytics, in which the enterprise data warehousing professionals must now collaborate closely with the subject matter experts who build and maintain predictive models. To support heterogeneous interoperability for in-database and in-cloud analytics, open development frameworks -- especially MapReduce and Hadoop -- will be adopted broadly by data warehousing and analytics tools vendors.


  • Social network analysis brings powerful predictive analysis to the online economy. Before long, social networks will pervade all business and personal applications, including all mobile, broadband, and streaming media services. From an enterprise perspective, social networks are the buzz that can spell the difference between success and failure in a reputation-driven online economy. In 2010, enterprises will avidly adopt social network monitoring and marketing tools while deploying advanced analytics to search for opportunities to better reach customers in these environments. Forrester sees 2010 as the year social network analysis truly emerges as the new frontier in advanced analytics, supporting mining of behavioral, attitudinal and other affinities among individuals. Social network analysis thrives on the deepening streams of information -- structured and unstructured, user-generated and automated -- that emanate from Facebook, Twitter and other new Web 2.0 communities. In the coming year, many vendors of predictive modeling tools will enhance their social network analysis features to support real-time customer segmentation, target marketing, churn analysis, and anti-fraud. The killer app for all this will become the real-time "next best offer" that your contact center makes from all this intelligence, or the marketing campaign you rearrange on the fly to save it from near-failure.


  • Low-cost data warehousing delivers fast analytics to the midmarket. Though enterprises can certainly do BI without a data warehouse, this critical infrastructure platform is essential for high-performance reporting, query and analytics against large data sets. In one of the most important BI trends of the past several years, the price of a fully configured data warehousing appliance platform has dropped by an order of magnitude and, with the development of public SaaS data warehouse cloud services, it will continue to decline. In 2010, many data warehousing vendors will lower the price of their basic appliance products to less than $20,000 per usable terabyte, which constitutes the new industry threshold pioneered by Oracle, Netezza and other leading data warehouse vendors. At the same time, enterprises will see a growing range of cost-effective solution appliances in 2010, combined data warehouse appliances with preconfigured BI, advanced analytics, data cleansing, industry information models, and other data management applications and tools.


  • Data warehousing virtualizing into the cloud. The data warehouse, like all other components of the BI and data management infrastructure, is entering the cloud. In 2010, we'll see vendors continue to introduce cloud, SaaS, and virtualized deployments of their core analytic databases. To support flexible mixed-workload analytics, the enterprise data warehouse will evolve over the coming five to 10 years into a virtualized cloud that allows data to be transparently persisted in diverse physical and logical formats to an abstract, seamless grid of interconnected memory and disk resources that can support diverse workloads, latencies and topologies. Massive parallelism, all-in-memory architectures, solid-state drives, and virtualized storage will increasingly revolutionize enterprise data warehouse environments -- both cloud- and appliance-based -- over this coming decade. In 2010, we will see most enterprise data warehouse vendors roll out pioneering offerings that offer all of these architectural innovations. However, 2010 will not be the "year of the cloud" for the data warehouse industry as a whole, since Teradata, Oracle, IBM, Microsoft and others will still be rolling out their initial public/private cloud platform services and partnerships. Nevertheless, the industry is moving inevitably toward cloud-based services that supplement appliances, licensed software and other deployment options.

    Gartner Inc.
    Various Gartner Inc. analysts covering BI, including Bill Hostmann, Kurt Schlegel, James Richardson, Nigel Rayner and Andreas Bitterer


  • Through 2012, hype around predictive analytics will outpace available skill sets in 80% of organizations. There seems to be renewed hype around all things predictive. BI leaders are being urged to go beyond historical reporting and make their BI solutions predictive. Unfortunately, developing predictive and descriptive models is hard work that requires a great deal of expertise, and there just isn't enough expertise to go around. Without a very significant investment in training, most companies will find they simply don't have the skills required to make their BI programs more predictive.


  • Through 2012, an additional 35% of Oracle's and SAP's application customers will change their strategic BI platform. Because of the BI platform market consolidation, the major ERP vendors (Oracle and SAP) now have BI platforms in the Leaders quadrant of the Gartner Magic Quadrant. The decision of whether or not firms should move to one of these vendors' BI platforms is increasingly a source of inquiries for Gartner BI analysts. This decision will rise in importfance as SAP and Oracle improve and expand their packaged analytic and performance management applications and target organizations that want to buy rather than build these applications.


  • Through 2011, organizations that use performance management applications to support a performance-driven culture will outperform their peers by 30%. Most organizations measure performance, they don't manage it. The traditional focus has been on measuring high-level, financially oriented outcomes after the event. The business climate emerging from the global downturn demands a focus on leading performance and risk indicators to provide a forward-looking focus that must permeate all levels of an organization, rather than just providing top-level measures. Changes in business strategy will be reflected in changes in performance metrics, which will drive change in behaviors across the organization.


  • Open source business intelligence tools production deployments will grow fivefold through 2012. Open source BI adoption approximately doubles every year, as open source BI vendors are continuously catching up with commercial BI platforms. Deployments of open source BI products follow the same model as commercially licensed products, starting with reporting, then analysis and dashboarding. While commercial vendors are still far ahead in their overall technology capabilities, however, open source adoption increases because it is often considered "good enough." To the surprise of some end-user organizations that were looking for a "free BI solution" for large-scale implementations, even open source BI deployment costs can enter the million-dollar range through high development and labor costs on top of the support subscription.

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