How are organizations using the information from data warehouses?

Data Warehousing is an approach that can collect and manage data from multiple sources to provide the business a significant business insight. A data warehouse is specifically designed to provide management decisions.

In simple terms, a data warehouse defines a database that is maintained independently from an organization’s operational databases. Data warehouse systems enable the integration of multiple application systems. They support data processing by providing a solid platform of consolidated, historical data for analysis.

A data warehouse is a semantically consistent data save that handle as a physical execution of a decision support data model. It saves the data an enterprise required to create strategic decisions. A data warehouse is viewed as an architecture, constructed by integrating records from several heterogeneous sources to provide structured and ad hoc queries, analytical documenting, and decision making.

The construction of a data warehouse needed data cleaning, data integration, and data consolidation. The uses of a data warehouse necessitates a set of decision support technologies. This enables “knowledge workers” such as managers, analysts, and executives to need the warehouse to fastly and conveniently obtain an overview of the data, and to create sound decisions depends on data in the warehouse.

Some organizations use this data to provide business decision-making activities, including

• It can be raising user focus, which involves the analysis of user buying patterns including buying preference, buying time, budget cycles, and demand for spending.

• It can be used to repositioning products and handling product portfolios by comparing the implementation of sales by quarter, by year, and by geographic regions to fine-tune production methods.

• It can be analyzing operations and looking for sources of profit.

• It can be managing customer relationships, making environmental corrections, and managing the cost of corporate assets.

Data warehousing is beneficial from the point of view of heterogeneous database integration. Organizations generally collect several kinds of data and supports large databases from multiple, heterogeneous, autonomous, and distributed data sources.

It is hugely desirable, yet challenging, to combine such data and supports easy and effective access to it. Much effort has been used in the database market and research community toward achieving this aim.

The traditional database method to heterogeneous database integration is to construct wrappers and integrators (or mediators) on top of multiple, heterogeneous databases. When a query is posed to a user site, a metadata dictionary can be used to interpret the query into queries appropriate for the single heterogeneous sites included.

These queries are mapped and shared to local query processors. The results restored from the multiple sites are unified into a global answer set. This query-driven method needed complex data filtering and integration procedure, and competes with local sites for processing resources. It is ineffective and potentially costly for frequent queries, particularly queries needed aggregations.