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Design analysis [5] should establish the scalability of an ETL system across the lifetime of its usage – including understanding the volumes of data that must be processed within service level agreements. The time available to extract from source systems may change, which may mean the same amount of data may have to be processed in less time.
With the traditional extract, transform and load (ETL) method, the load job is the last step, and the data that is loaded has already been transformed. With the alternative method extract, load and transform (ELT), the loading job is the middle step, and the transformed data is loaded in its original format for data transformation in the target ...
The transformation phase of a spatial ETL process allows a variety of functions; some of these are similar to standard ETL, but some are unique to spatial data. [3] Spatial data commonly consists of a geographic element and related attribute data; therefore spatial ETL transformations are often described as being either geometric transformations – transformation of the geographic element ...
Extract, load, transform (ELT) is an alternative to extract, transform, load (ETL) used with data lake implementations. In contrast to ETL, in ELT models the data is not transformed on entry to the data lake, but stored in its original raw format.
Sharable Content Object Reference Model (SCORM) is a collection of standards and specifications for web-based electronic educational technology (also called e-learning). It defines communications between client side content and a host system (called "the run-time environment"), which is commonly supported by a learning management system.
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Educational Evaluation and Policy Analysis is a peer-reviewed academic journal covering all aspects of educational policy analysis. It was established in 1979 and is published by SAGE Publications on behalf of the American Educational Research Association .
Within the ETL process, all key data from tasks is logged on execution. This includes start time, end time, CPU seconds used, disk reads, disk writes, and rows processed. When troubleshooting the ETL or query process, this sort of data becomes valuable. Process metadata is the fact measurement when building and using a DW/BI system.