forecast versus actual and 12-month rolling averages to be leveraged with new data sets, helping sales executives better manage their business and ensure compensation plans are best aligned with strategic objectives. Scenario 10: Plant Floor Manufacturer, Data Warehousing and Aggregation A manufacturing enterprise customer designs a high-performance assembly floor plant where instrumentation measurements are generated from Programmable Logic Controllers (PLCs) and recorded into a relational database. Operational efficiencies are calculated against aggregated multidimensional OLAP (MOLAP) views using analysis queries against a proactive cache built from the application OLTP store. Microsoft technology solution set profile SQL Server was used 2008 was used for the relational store, and dimensional views were cached and constructed within Business Intelligence Studio and SSIS. Queries using SSAS interrogate cached views that are updated on the fly and highly optimized for performance. ISV discussion points SQL Server can handle the most demanding OLTP environments, and yet dimensional views as transactions are updating the supporting OLTP tables. ISV Opportunities with SQL Server Analysis Services Effort Using XML for Analysis to communicate with Analysis Services, partners can extend built-in management tools and viewers. ISVs can take advantage of extensibility options with Analysis Services such as assemblies and personalized extensions () . Performance Management/Dashboards Through PerformancePoint Server 2007 ( ), soon to be a part of a future version of PerformancePoint Services for SharePoint () , ISVs are able to provide customers with a deep understanding of trends and what is happening now in their business. Through monitoring, reporting, planning, and analytics, PerformancePoint Server enables rapid scorecard and dashboard construction along with a rich set of tools for probing deeper into dimensional data. With a key performance indicator (KPI) metrics designer, dashboard client, performance map utility, decomposition tree, and analytics modeling,
forecast versus actual and 12-month rolling averages to be leveraged with new data sets, helping sales executives better manage their business and ensure compensation plans are best aligned with strategic objectives. Scenario 10: Plant Floor Manufacturer, Data Warehousing and Aggregation A manufacturing enterprise customer designs a high-performance assembly floor plant where instrumentation measurements are generated from Programmable Logic Controllers (PLCs) and recorded into a relational database. Operational efficiencies are calculated against aggregated multidimensional OLAP (MOLAP) views using analysis queries against a proactive cache built from the application OLTP store. Microsoft technology solution set profile SQL Server was used 2008 was used for the relational store, and dimensional views were cached and constructed within Business Intelligence Studio and SSIS. Queries using SSAS interrogate cached views that are updated on the fly and highly optimized for performance. ISV discussion points SQL Server can handle the most demanding OLTP environments, and yet dimensional views as transactions are updating the supporting OLTP tables. ISV Opportunities with SQL Server Analysis Services Effort Using XML for Analysis to communicate with Analysis Services, partners can extend built-in management tools and viewers. ISVs can take advantage of extensibility options with Analysis Services such as assemblies and personalized extensions () . Performance Management/Dashboards Through PerformancePoint Server 2007 ( ), soon to be a part of a future version of PerformancePoint Services for SharePoint () , ISVs are able to provide customers with a deep understanding of trends and what is happening now in their business. Through monitoring, reporting, planning, and analytics, PerformancePoint Server enables rapid scorecard and dashboard construction along with a rich set of tools for probing deeper into dimensional data. With a key performance indicator (KPI) metrics designer, dashboard client, performance map utility, decomposition tree, and analytics modeling,
BI-DW_ISVAdoptionRoadmap.docx