In-Database Analytics: The Heart of the Predictive Enterprise

03/02/10

Visionary organizations are adopting an emerging practice known as “in-database analytics,” which supports more pervasive embedding of predictive models in business processes and mission-critical applications. With in-database analytics, enterprises migrate their predictive analysis (PA), data mining (DM), and other compute-intensive analytic functions from separate, standalone applications to execute in the enterprise data warehouse (EDW). Doing so allows IT professionals to leverage the EDW’s full parallel-processing, scalability, and optimization features. In-database analytics can help enterprises cut costs, speed development, and tighten governance on advanced analytics initiatives. Business process and applications (BP&A) professionals should implement in-database analytics in conjunction with ongoing efforts to consolidate and scale their EDW.

Sponsored By Aster Data Systems

Evolving from Departmental Islands of BI to a Cohesive Enterprise BI Environment

01/06/10

Enterprise BI environments help ensure a single version of the truth and a low long-term cost of ownership, while providing high performance, scalability, and rapid application development. However, achieving enterprise BI can take several months or years, and in the meantime, departments need access to fast, reliable BI. As a result, small departmental "islands" of BI surface throughout an organization, designed to satisfy immediate business needs. Although convenient, these applications lead to multiple versions of the truth and incur high costs of ownership. The solution, therefore, is to gradually consolidate departmental BI applications into a cohesive enterprise BI environment.

Sponsored By MicroStrategy