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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

 

            Benefits

 

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

 

   Increased productivity of corporate decision-makers

 

            Problems

 

   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:

 

          Extraction

 

          Cleansing

 

          Transformation

 

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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