Data Warehouses and Data Mining
This article gives a detailed summary of the role of data warehouses and data mining, and their relationship to organizational databases. As you read, pay attention to how data warehouses are used to improve decision-making in organizations. Keep a summary in your notes of how an organization you are involved with could benefit from data mining and data warehousing.
Data warehouse was first coined by Bill Inmon in 1990. According to the Inmon, a data warehouse is a subject-oriented, integrated, time-variant, and non-volatile collection of data. This data helps analysts to make informed decisions in an organization.
- A data warehouse is a database that is kept separate from the organization's operational database.
- Possesses consolidated historical data, which helps the organization to analyze its business.
- Help in the integration of diversity of application systems. Why a data warehouse is separated from operational databases?
- An operational database is constructed for well-known tasks and workloads such as searching particular records. Indexing etc.
- An operational database query allows reading and modifying operations.
- An operational database maintains current data.
- Data warehouse is subject oriented because it provides information around a subject.
- Data is integrated from heterogeneous sources.
- Data collected in a data warehouse is identified with a particular time period.
- Data is non volatile.
- A data warehouse does not require transaction processing, recovery, and concurrency controls.