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Managing OLAP Cube Data

Data Storage and Access

Organizations usually have databases and data stores that maintain repeated and frequent business transaction data. This provides simple yet detailed storage and retrieval of specific data events. However, these data storage systems are not well suited for analytical summaries and queries that are typically generated by decision makers. For decision makers to reveal hidden trends, inconsistencies, and risks in a business, they must be able to maintain a certain degree of momentum when querying the data. An answer to one question usually leads to additional questions and review of the data. Simple data stores do not generally suffice.

The data warehouse is a structure better suited for this type of querying. In a data warehouse, data is maintained and organized so that complicated queries and summaries can be run. OLAP further organizes and summarizes specific categories and subsets of data from the data warehouse. One particular kind of data structure derived from a data warehouse is the cube. A cube is a set of data that is organized and structured in a hierarchical, multidimensional arrangement. Such an arrangement results in a robust and detailed level of data storage with efficient and fast query returns. Stored, precalculated summarizations called aggregations can be added to the cube to improve cube access performance.

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