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2. Qlik - Wikipedia

   en.wikipedia.org/wiki/Qlik

   Qlik Data Integration (QDI) includes tools such as Qlik Replicate for data replication, Qlik Catalog for data organization, Qlik Compose for automation of data lakes and data warehouses, and Qlik Talend Cloud for maintenance of data integrity. [3] [4] Qlik's AI program enables AI-powered analytics, natural language capabilities, and ...

3. 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

4. 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]

5. Data build tool - Wikipedia

   en.wikipedia.org/wiki/Data_build_tool

   Dbt has the goal of allowing analysts to work more like software engineers, in line with the dbt viewpoint. [11] Dbt uses YAML files to declare properties. seed is a type of reference table used in dbt for static or infrequently changed data, like for example country codes or lookup tables), which are CSV based and typically stored in a seeds ...

6. 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.

7. 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. It helps improve productivity, reduce cost ...