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  2. Category:Extract, transform, load tools - Wikipedia

    en.wikipedia.org/wiki/Category:Extract...

    Extract, transform, load tools are software packages that facilitate the performing of ETL tasks. Pages in category "Extract, transform, load tools" The following 35 pages are in this category, out of 35 total.

  3. Extract, transform, load - Wikipedia

    en.wikipedia.org/wiki/Extract,_transform,_load

    For instance, the new application might use another database vendor and most likely a very different database schema. ETL can be used to transform the data into a format suitable for the new application to use. An example would be an expense and cost recovery system such as used by accountants, consultants, and law firms.

  4. Configuration management database - Wikipedia

    en.wikipedia.org/wiki/Configuration_management...

    Federation is usually distinguished from ETL (extract, transform, load) solutions in which data is copied into the CMDB. CMDBs can be used for many things, including but not limited to: business intelligence, software and hardware builds, inventory, [ 4 ] impact analysis for change management, [ 5 ] and incident management .

  5. Pervasive Software - Wikipedia

    en.wikipedia.org/wiki/Pervasive_Software

    Pervasive Software was a company that developed software including database management systems and extract, transform and load tools. Pervasive Data Integrator and Pervasive Data Profiler are integration products, and the Pervasive PSQL relational database management system is its primary data storage product.

  6. Slowly changing dimension - Wikipedia

    en.wikipedia.org/wiki/Slowly_changing_dimension

    The ETL team must update/overwrite the type 1 mini-dimension reference whenever the current mini-dimension changes over time. If the outrigger approach does not deliver satisfactory query performance, then the mini-dimension attributes could be physically embedded (and updated) in the base dimension.

  7. Change data capture - Wikipedia

    en.wikipedia.org/wiki/Change_data_capture

    Change data capture both increases in complexity and reduces in value if the source system saves metadata changes when the data itself is not modified. For example, some Data models track the user who last looked at but did not change the data in the same structure as the data. This results in noise in the Change Data Capture.

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