A data mart is a subset of a data warehouse that is usually oriented to a specific business line or team. Whereas data warehouses have enterprise-wide depth, data marts are often smaller sections of data warehouses segmented for specific uses. Here are some key points about data marts:
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Purpose-Oriented: Data marts are designed to meet the specific needs of a particular group of users, such as a department within a company, like sales, finance, or marketing. They contain data relevant to that group.
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Scope and Size: They are smaller in scope and size compared to data warehouses. This makes them easier to implement and manage.
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Data Sources: Data marts can draw data from a wide range of sources. They may pull data from internal systems like ERP and CRM, as well as external data sources.
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Performance: Because of their smaller size and focused nature, data marts can improve query performance. They enable users to access and analyze relevant data more quickly and efficiently than sifting through a larger data warehouse.
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Types of Data Marts: There are two main types: independent data marts, which are created without a data warehouse and rely solely on data from source systems; and dependent data marts, which are created from an existing data warehouse.
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Implementation: Implementing a data mart is generally faster and less costly than a full data warehouse because of its limited scope.
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Business Intelligence: Data marts are often used in business intelligence (BI) applications, where they provide the data for reporting and analysis tools.
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Customization: They can be customized to fit the specific needs of different user groups within an organization, providing more relevant and tailored data for analysis.
In summary, data marts are a focused and scaled-down version of data warehouses, designed to provide specific groups within an organization with the data they need for analysis and decision-making.