Data warehousing is the electronic storage of a large amount of information by a business. SAVIS Data warehouse is constructed by integrating data from multiple heterogeneous sources that support analytical reporting, structured and/or ad hoc queries, and decision-making. It involves data cleaning, data integration, and data consolidations. The superiority of SAVIS Data warehouse over traditional applications:
- This is an alternative to the traditional approach. Today’s data warehouse systems follow update-driven approach rather than the traditional approach discussed earlier. In update-driven approach, the information from multiple heterogeneous sources are integrated in advance and are stored in a warehouse. This information is available for direct querying and analysis.
- Include an extraction, transportation, transformation, and loading (ETL) solution, an online analytical processing (OLAP) engine, client analysis tools, and other applications that manage the process of gathering data and delivering it to business users.
- Data warehouses usually store many months or years of data. This is to support historical analysis.