Olap Server For Multi-dimensional Queries

OLAP Server supports multi dimensional query language and it can process vast queries by analyzing the queries also

. It reads data and stores in the memory cache. Basically the modern trend is multidimensional data analysis such as OLAP analysis. OLAP server evaluates large volume of historical data. Business intelligence includes OLAP cubes, data warehouse, data mining etc. Basically user can store, process, and analyze huge volume of historical data. The data are multidimensional in nature. They contain relational models.

Multidimensional structure is defined as a different relational model which uses multidimensional structures to manage data and describe the relation between the data. The structure is divided into cube and it stores and accesses data within the border of the cube. Each cell contains total data which is related to elements and its dimensions. If the data is tampered still then it is possible to access the database as is a compact type of database. Data are related to each other. In the analytical database multidimensional structure is popular because of the use of the OLAP (Online Analytical Processing). Actually analytical databases are very popular because they can answer the business queries very quickly. In this database data are viewable from the different angles which give a broader outlook of a query. This is not possible in other models.

It is claimed that an OLAP cube can process a business complex query in 0.1% of the time which an OLTP relational data takes. The important feature of the OLAP is to process complex business queries very fast. It works by aggregating huge business complex queries. It is done from the data of the fact table. It is done on specific dimensions and adding up data on these dimensions. The possibility of the aggregations is equal to the possible combination of dimensions.

In the OLAP Server all possible aggregations are mixed with the base data which contains the answers of the query. It can be answered from the data. There can be many aggregations that are calculated. Some parts may be calculated and the remaining part may be calculated on demand.

by: Carlos Quijada

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