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Data warehouse

   Posted On :  15.12.2016 07:41 am

Data warehouse is data management and data analysis. Goal: is to integrate enterprise wide corporate data into a single reository from which users can easily run queries

Data warehouse


     Data warehouse is data management and data analysis


     Goal: is to integrate enterprise wide corporate data into a single reository from which users can easily run queries




   The major benefit of data warehousing are high returns on investment.


   Increased productivity of corporate decision-makers




   Underestimation of resources for data loading


   Hidden problems with source systems


   Required data not captured


   Increased end-user demands


   Data homogenization


   High demand for resources


   Data ownership


   High maintenance


   Long-duration projects


   Complexity of integration



Main components


          Operational data sources - - > for the DW is supplied from mainframe operational data held in first generation hierarchical and network databases, departmental data held in proprietary file systems, private data held on workstaions and private serves and external systems such as the Internet, commercially available DB, or DB assoicated with and organization‘s suppliers or customers.


          Operational datastore(ODS) - - >  is a repository of current and integrated operational data used for analysis. It is often structured and supplied with data in the same way as the data warehouse, but may in fact simply act as a staging area for data to be moved into the warehouse.


          query manager - - > also called backend component, it performs all the operations associated with the management of user queries. The operations performed by this component include directing queries to the appropriate tables and scheduling the execution of queries


          end-user access tools - - > can be categorized into five main groups: data reporting and query tools, application development tools, executive information system (EIS) tools, online analytical processing (OLAP) tools, and data mining tools.


          Data flow


          Inflow- The processes associated with the extraction, cleansing, and loading of the data from the source systems into the data warehouse.


          upflow- The process associated with adding value to the data in the warehouse through summarizing, packaging , packaging, and distribution of the data.


          downflow- The processes associated with archiving and backing-up of data in the warehouse.


          Tools and Technologies


The critical steps in the construction of a data warehouse:








after the critical steps, loading the results into target system can be carried out either by separate products, or by a single, categories:


          code generators


          database data replication tools


          dynamic transformation engines


For the various types of meta-data and the day-to-day operations of the data warehouse, the administration and management tools must be capable of supporting those tasks:



            Monitoring data loading from multiple sources


            Data quality and integrity checks


            Managing and updating meta-data


            Monitoring database performance to ensure efficient query response times and resource utilization


            Auditing data warehouse usage to provide user chargeback information


            Replicating, subsetting, and distributing data


            Maintaining effient data storage management


            Purging data;


            Archiving and backing-up data


            Implementing recovery following failure


Tags : Business Science - Information Management - Database Management Systems
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