Analytical view of business data

  • Authors:
  • Adam Yeh;Jonathan Tang;Youxuan Jin;Sam Skrivan

  • Affiliations:
  • Microsoft Corporation, Redmond, WA;Microsoft Corporation, Redmond, WA;Microsoft Corporation, Redmond, WA;Microsoft Corporation, Redmond, WA

  • Venue:
  • Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
  • Year:
  • 2004

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Abstract

This paper describes a logical extension to Microsoft Business Framework (MBF) called Analytical View (AV). AV consists of three components: Model Service for design time, Business Intelligence Entity (BIE) for programming model, and IntellDrill for runtime navigation between OLTP and OLAP data sources. AV feature-set fulfills enterprise application requirements for Analysis and Decision Support, complementing the transactional feature-set currently provided by MBF. Model Service automatically transforms an "object oriented model (transactional view)" to a "multi-dimensional model (analytical view)" without the traditional Extraction/Transformation/Loading (ETL) overhead and complexity. It infers dimensionality from the object layer where richer metadata is stored, eliminating the "guesswork" that a traditional data warehousing process requires when going through physical database schema. BI Entities are classes code-generated by Model Service. As an intrinsic part of the framework, BI Entities enable a consistent object oriented way of programming model with strong types and rich semantics for OLAP, similar to what MBF object persistence technology does for OLTP data. More importantly, data contained in BI Entities have a higher degree of "application awareness," such as the integrated application level security and customizability. IntelliDrill links together all the information islands in MBF using metadata. Because of the automatic transformation from transactional view to analytical view enabled by Model Service, we have the ability to understand natively what kind of drill-ability an object would have, thus making information navigation in MBF fully discover-able with built-in ontology.