Components of a Data Warehouse

• Database Servers: Operational data accumulated during standard business must be extracted and stored into a database. Most companies use a relational database stored on a mainframe server. Oracle, Sybase, SQL server and DB2 are just a few of the database systems available.
• Queries/Reports: Querying is a broad term that encompasses all the activities of requesting data from a data warehouse for analysis. Reports are then generated to display the results for the specified query. Querying, obviously, is the whole point of using the data warehouse.
• OLAP/ Multi-dimensional analysis: Relational databases store data in a two dimensional format; tables of data represented by rows and columns. Multi-dimensional analysis, commonly referred to as On-Line Analytical Processing (OLAP), offer an extension to the relational model to provide a multi-dimensional view of the data. These tools allow users to drill down from summary data sets into the specific data underlying the summaries. Statistical analysis tools provide summary information and help determine the degree of relationship between two factors.
• Data Mining: Data mining is the process of analyzing business data in the data warehouse to find unknown patterns or rules of information that you can use to tailor business operations. Data mining predicts future trends and behaviors, allowing businesses to make proactive, knowledge driven decisions.