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Extract, transform, load (ETL) is a three-phase computing process where data is extracted from an input source, transformed (including cleaning), and loaded into an output data container. The data can be collected from one or more sources and it can also be output to one or more destinations.
Figure 1: Simple schematic for a data warehouse. The Extract, transform, load (ETL) process extracts information from the source databases, transforms it and then loads it into the data warehouse. Figure 2: Simple schematic for a data-integration solution. A system designer constructs a mediated schema against which users can run queries.
Oracle Data Integrator (ODI) is an extract, load, transform (ELT) tool (in contrast with the ETL common approach) produced by Oracle that offers a graphical environment to build, manage and maintain data integration processes in business intelligence systems.
Oracle Warehouse Builder was built from the ground up in Oracle, it was first released in January 2000 (release 2.0.4). The 3i release significantly enhanced the ETL mapping designer, then 9i in 2003 introduced the mapping debugger, process flow editing, integrated match/merging and name/address cleansing, multi-table insert, scripting, RAC certification to name a few.
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 ...
This process can follow the linear set of steps as described in the data transformation process above. Batch data transformation is the cornerstone of virtually all data integration technologies such as data warehousing, data migration and application integration. [1] When data must be transformed and delivered with low latency, the term ...
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