Indexing which includes covering indexes is done by default with the ability to override on a per table basis. hashed, binary values for better performance. The model generated by the tool corresponded well to. A few simple table classifications help to optimize the code that is generated and includes i.e. target tables of the data model, rather than what kind of tables and what source table they consist of. TX2012 is also build to scale and perform, thus it includes support for a wide range of loading strategies such as source- and target based incremental load, just as table partitioning and data compression is a five minute operation to implement. Although the Meta data driven engine in tX2012 is powerful enough to also support other models such as Inmon and Data Vault, tX2012 has an emphasis on the star schema model, also known as Kimball dimensional modeling which means that features such as surrogate keys, slowly changing dimensions, aggregations and almost everything else from the 34 subsystems of ETL are supported. The star schema model is the most widely used data model for data warehousing, and the de facto standard for business focused reporting. Data warehouses can be modeled in a relational or dimensional form of which the latter is the most common. Data is collected over time and stores historical events that are often not persisted in the source systems and is also commonly referred to as the single version of the truth, making the data warehouse an important asset for the organization. The overall purpose of a data warehouse is to integrate corporate data from various internal- and external data sources.
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