Experts forecast business intelligence market trends for 2009
James G. Kobielus
Senior analyst at Cambridge, Mass.-based Forrester Research covering BI and data warehousing.
BI moves into the cloud. Enterprises of all sizes will adopt hosted, subscription-based services in greater numbers to supplement or, in increasing numbers, replace their premises-based BI platforms. In a soft economy, any on-demand pay-as-you-go offering becomes more attractive across all customer segments. Just as important, the increasing scalability, performance, flexibility, and availability demands on the enterprise BI infrastructure are spurring many users to consider outsourced offerings.
BI adopting Web 2.0 development paradigm. Mashups will move into mainstream BI practice as budget-stressed organizations push more development to users through self-service tools. The chief enablers for this new paradigm are the growing range of commercial, in-memory, BI-integrated mashup tools that let power users develop rich reports, dashboards, and analytic applications on the fly from within their browsers and spreadsheets. Data modelers and other traditional BI developers will supervise governance of user-generated BI mashups.
BI growing more federated. Enterprises will turn to federated data environments to support operational BI across stubbornly decentralized information silos that are scattered throughout their service-oriented architectures (SOAs). To respond to this growing requirement, IT organizations will supplement their enterprise data warehouses by beefing up their enterprise information integration middleware and semantic virtualization layers.
BI evolving into advanced analytic applications. Enterprises have substantially completed their adoption of core BI, enterprise data warehouse, and enterprise content management platforms and will increasingly turn to powerful predictive analytics, data mining, statistical analysis, and text analytics tools to leverage that information for business optimization. One consequence of this trend will be the growing adoption of in-database analytics techniques, under which users will process these compute- and data-intensive functions inside the enterprise data warehouses, taking advantage of that platform's massive parallel processing.