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Transformation programs are automatically created in SQL, XSLT, Java, or C++. These kinds of graphical tools are found in most ETL (extract, transform, and load) tools as the primary means of entering data maps to support data movement. Examples include SAP BODS and Informatica PowerCenter.
Tool Supported data models (conceptual, logical, physical) Supported notations Forward engineering Reverse engineering Model/database comparison and synchronization
ETL software typically automates the entire process and can be run manually or on recurring schedules either as single jobs or aggregated into a batch of jobs. A properly designed ETL system extracts data from source systems and enforces data type and data validity standards and ensures it conforms structurally to the requirements of the output.
Code generation is the process of generating executable code (e.g. SQL, Python, R, or other executable instructions) that will transform the data based on the desired and defined data mapping rules. [4] Typically, the data transformation technologies generate this code [5] based on the definitions or metadata defined by the developers.
Flow Software Flow Software Ltd 2.3.0 2010-05 Free Community Edition, and Enterprise licenses No Proprietary: Fuse – Enterprise Camel Red Hat: 7.0 2018 Yes based on Apache Software License: IBM Integration Bus (formerly WebSphere Message Broker) IBM: 10.0 2015-03 [2] Varies between approximately 100 and 850 per Value Unit [3] No Proprietary
Pentaho started out as business intelligence (BI) software developed by the Pentaho Corporation in 2004. It comprises Pentaho Data Integration (PDI) and Pentaho Business Analytics (PBA)]. These provide data integration, OLAP services, reporting, information dashboards, data mining and extract, transform, load (ETL) capabilities.
Data integration, by contrast, is a permanent part of the IT architecture, and is responsible for the way data flows between the various applications and data stores—and is a process rather than a project activity. Standard ETL technologies designed to supply data from operational systems to data warehouses would fit within the latter ...
Data wrangling, sometimes referred to as data munging, is the process of transforming and mapping data from one "raw" data form into another format with the intent of making it more appropriate and valuable for a variety of downstream purposes such as analytics.