What is a Data Warehouse? Explain its Architecture.

A data warehouse is a relational database that is designed for query and analysis rather than for transaction processing. It usually contains historical data derived from transaction data, but can include data from other sources. Data warehouses separate analysis workload from transaction workload and enable an organization to consolidate data from several sources. This helps in:

  • Maintaining historical records
  • Analyzing the data to gain a better understanding of the business and to improve the business.

In addition to a relational database, a data warehouse environment can include an extraction, transportation, transformation, and loading (ETL) solution, statistical analysis, reporting, data mining capabilities, client analysis tools, and other applications that manage the process of gathering data, transforming it into useful, actionable information, and delivering it to business users.

Data Warehouse Architecture: Basic

Figure 1-2 shows a simple architecture for a data warehouse. End users directly access data derived from several source systems through the data warehouse.

Figure 1-2 Architecture of a Data Warehouse

Description of Figure 1-2 follows
Description of “Figure 1-2 Architecture of a Data Warehouse”

In Figure 1-2, the metadata and raw data of a traditional OLTP system is present, as is an additional type of data, summary data. Summaries are very valuable in data warehouses because they pre-compute long operations in advance. For example, a typical data warehouse query is to retrieve something such as August sales. A summary in an Oracle database is called a materialized view.

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