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  2. Pentaho - Wikipedia

    en.wikipedia.org/wiki/Pentaho

    Pentaho for Big Data: EE, CE: PDI plug-in: N/A: Pentaho for Big Data is a data integration tool based on Pentaho Data Integration. [2] It allows executing ETL jobs in and out of big data environments such as Apache Hadoop or Hadoop distributions such as Amazon, Cloudera, EMC Greenplum, MapR, and Hortonworks. [3]

  3. Database catalog - Wikipedia

    en.wikipedia.org/wiki/Database_catalog

    A database catalog of a database instance consists of metadata in which definitions of database objects such as base tables, views (virtual tables), synonyms, value ranges, indexes, users, and user groups are stored. [1] [2] It is an architecture product that documents the database's content and data quality. [3]

  4. Alation - Wikipedia

    en.wikipedia.org/wiki/Alation

    Alation is an enterprise software company based in Silicon Valley.. Alation Data Catalog is a data catalog that serves enterprises in organizing and consolidating their data. . Alation launched its data catalog as their first product in 2015 to give data consumers an easy way to search for enterprise data with natural langua

  5. KNIME - Wikipedia

    en.wikipedia.org/wiki/KNIME

    KNIME (/ n aɪ m / ⓘ), the Konstanz Information Miner, [2] is a free and open-source data analytics, reporting and integration platform.KNIME integrates various components for machine learning and data mining through its modular data pipelining "Building Blocks of Analytics" concept.

  6. Data Catalog Vocabulary - Wikipedia

    en.wikipedia.org/wiki/Data_Catalog_Vocabulary

    Data Catalog Vocabulary (DCAT) is an RDF vocabulary designed to facilitate interoperability between data catalogs published on the Web.By using DCAT to describe datasets in catalogs, publishers increase discoverability and enable applications to consume metadata from multiple catalogs.

  7. DataOps - Wikipedia

    en.wikipedia.org/wiki/Dataops

    DataOps is a set of practices, processes and technologies that combines an integrated and process-oriented perspective on data with automation and methods from agile software engineering to improve quality, speed, and collaboration and promote a culture of continuous improvement in the area of data analytics. [1]

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  9. Data warehouse automation - Wikipedia

    en.wikipedia.org/wiki/Data_warehouse_automation

    Data warehouse automation (DWA) refers to the process of accelerating and automating the data warehouse development cycles, while assuring quality and consistency. DWA is believed to provide automation of the entire lifecycle of a data warehouse, from source system analysis to testing to documentation .

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