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Metadata for Data Warehousing
Metadata refers to information about data that provides context and meaning to help users understand and use the data. In data warehousing, metadata is crucial for the efficient and effective use of the data stored in the data warehouse.
Metadata in data warehousing typically includes information such as the source of the data, the data structure, the data format, the data quality, and the relationships between different data elements. This information helps users to understand the data and its context, and to make informed decisions about how to use the data in data mining and warehousing.
Metadata can be classified into three main categories: technical metadata, business metadata, and operational metadata. Technical metadata includes information about the structure and characteristics of the data, such as data types, column names, and table names. Business metadata includes information about the meaning and context of the data, such as business rules, definitions, and relationships between data elements. Operational metadata includes information about the usage and performance of the data, such as query logs and data access patterns.
Effective management of metadata is essential for successful data warehousing and mining. By providing context and meaning to the data, metadata helps users to understand and use the data more effectively, which can lead to better decision-making and improved business outcomes.
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