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Execution-MiH Encyclopedia →
Enterprise Intelligence
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SECTION - Data Analysis/OLAP |
Data Analysis/OLAP is most fundamental way to make sense out of
your data. It involves looking at the data from all possible angles,
slicing & dicing on various dimensions, drilling up/down, applying
filters, exception highlighting, graphs and other presentation tools,
doing time trending analysis. Whether you are doing a pivot on excel
or creating advanced views in a up-market OLAP tool, most of the
usage of data in today’s world falls within the realm of Data
Analysis/OLAP. It is essentially a post graduate course before you
go for fellowship in Data Mining.
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Chapters
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This chapter provides the back-ground to the concept of OLAP and how it fits into the overall BI frame-work.
Topics in this chapter : OLAP in Business Intelligence- What is OLAP? →
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This chapter covers the likes of drill down, exception, max-min analysis. The list is long and will be enhanced on ongoing basis
Topics in this chapter : Drill (horizontal) and Cross (horizontal) Navigation and Analysis → Time Trending Data Analysis → Exception Analysis → Data Min-Max Analysis → Data Aggregation Analysis → Data Filtration Analysis → Pivoting, and Slicing & Dicing Analysis →
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This chapter provides the advanced analysis capabilities within OLAP, which provides the building blocks for BI- End-User tools to fulfill contextual analysis requirements.
Topics in this chapter : OLAP what if Analysis → OLAP Data Allocation Analysis → OLAP Goal-Seek Data Analysis →
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The subject of hierarchies is relevant to both OLAP and Enterprise Intelligence Delivery - Data Warehousing/Marting. Modeling of data is done, both in DW and OLAP, keeping the hierarchies in mind. However, OLAP is the platform where the hierarchies are manifested in their final shape for the purpose of analysis.
Topics in this chapter : OLAP and Data Warehouse Dimensional Model Hierarchy → Dimensional Model Simple Hierarchy → Dimensional non Strict Hierarchy → Multiple Path Hierarchy → Parallel Dimensional Hierarchy →
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Additivity and correct aggregation methods application is fundamental to the success of Business Intelligence. The most common mistakes the modelers and designers make is on - Setting the Right Hierarchies AND Establishing Right Additivity and aggregation rules. You need to go through the chapter of business dimensional hierarchies, before you go through this chapter.
Topics in this chapter : Additivity of Measures-Facts → Non-Additive Measures-Facts → Semi-Additive Measures-Facts →
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All Sections in " Enterprise Intelligence ."
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