- Posted: Jun 08, 2012 at 9:50 AM
- 3,061 Views
- 1 Comment
Loading User Information from Channel 9
Something went wrong getting user information from Channel 9
Loading User Information from MSDN
Something went wrong getting user information from MSDN
Loading Visual Studio Achievements
Something went wrong getting the Visual Studio Achievements
Right click “Save as…”
Microsoft StreamInsight™ is a powerful platform that you can use to develop and deploy complex event processing (CEP) applications. Its high-throughput stream processing architecture and the Microsoft .NET Framework-based development platform enable you to quickly implement robust and highly efficient event processing applications. Event stream sources typically include data from manufacturing applications, financial trading applications, Web analytics, and operational analytics. By using StreamInsight, you can develop CEP applications that derive immediate business value from this raw data by reducing the cost of extracting, analyzing, and correlating the data; and by allowing you to monitor, manage, and mine the data for conditions, opportunities, and defects almost instantly.
By using StreamInsight to develop CEP applications, you can achieve the following tactical and strategic goals for your business:
Monitor your data from multiple sources for meaningful patterns, trends, exceptions, and opportunities.
Analyze and correlate data incrementally while the data is in-flight -- that is, without first storing it--yielding very low latency. Aggregate seemingly unrelated events from multiple sources and perform highly complex analyses over time.
Manage your business by performing low-latency analytics on the events and triggering response actions that are defined on your business key performance indicators (KPIs).
Respond quickly to areas of opportunity or threat by incorporating your KPI definitions into the logic of the CEP application, thereby improving operational efficiency and your ability to respond quickly to business opportunities.
Mine events for new business KPIs.
Move toward a predictive business model by mining historical data to continuously refine and improve your KPI definitions.