Tue, 5 January 2010
Game-Changing Architectural Advances Take Data Analytics to New Performance Heights
New architectures for data and logic processing are ushering in a game-changing era of advanced analytics. These new approaches support massive data sets to produce powerful insights and analysis -- yet with unprecedented price-performance. As we enter 2010, enterprises are including more forms of diverse data into their business intelligence (BI) activities. They're also diversifying the types of analysis that they expect from these investments. At the same time, more kinds and sizes of companies and government agencies are seeking to deliver ever more data-driven analysis for their employees, partners, users, and citizens. It boils down to giving more communities of participants what they need to excel at whatever they're doing. By putting analytics into the hands of more decision makers, huge productivity wins across entire economies become far more likely. But such improvements won’t happen if the data can't effectively reach the application's logic, if the systems can't handle the massive processing scale involved, or the total costs and complexity are too high. In this sponsored podcast discussion we examine how convergence of data and logic, of parallelism and MapReduce -- and of a hunger for precise analysis with a flood of raw new data -- are all setting the stage for powerful advanced analytics outcomes. To help learn how to attain advanced analytics and to uncover the benefits from these new architectural activities for ubiquitous BI, we're joined by Jim Kobielus, senior analyst at Forrester Research, and Sharmila Mulligan, executive vice president of marketing at Aster Data Systems. The discussion is moderated by BriefingsDirect's Dana Gardner, principal analyst at Interarbor Solutions. Read a full transcript of the podcast, or download a copy. Sponsor: Aster Data Systems.
Direct download: BriefingsDirect-Architectural_Advances_Take_Data_Analytics_to_New_Heights.mp3
Category:podcasts -- posted at: 12:46pm EDT