Chapter: Data Warehousing and Data Mining : Business Analysis

OLAP and Need

It uses database tables (fact and dimension tables) to enable multidimensional viewing, analysis and querying of large amounts of data.

OLAP

OLAP stands for Online Analytical Processing.

It uses database tables (fact and dimension tables) to enable multidimensional viewing, analysis and querying of large amounts of data.

E.g. OLAP technology could provide management with fast answers to complex queries on their operational data or enable them to analyze their company’s historical data for trends and patterns.

Online Analytical Processing (OLAP) applications and tools are those that are designed to ask ―complex queries of large multidimensional collections of data.‖ Due to that OLAP is accompanied with data warehousing.

Need

The key driver of OLAP is the multidimensional nature of the business problem.

These problems are characterized by retrieving a very large number of records that can reach gigabytes and terabytes and summarizing this data into a form information that can by used by business analysts.

One of the limitations that SQL has, it cannot represent these complex problems.

A query will be translated in to several SQL statements. These SQL statements will involve multiple joins, intermediate tables, sorting, aggregations and a huge temporary memory to store these tables.

These procedures required a lot of computation which will require a long time in computing.

The second limitation of SQL is its inability to use mathematical models in these SQL statements. If an analyst, could create these complex statements using SQL statements, still there will be a large number of computation and huge memory needed.

Therefore the use of OLAP is preferable to solve this kind of problem.

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Data Warehousing and Data Mining : Business Analysis : OLAP and Need |