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Data Staging

The data staging area is a temporary location for data between the source systems and the data warehouse. This is where source data is copied to in the extract phase of ETL and is the first integration point for data coming from multiple source systems. This is also where the majority of data cleansing and

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Data Lineage Diagrams

Most data warehouse developers have experienced the challenge of answering a common question like “what data source fields are we using for this measure?” and sometimes you can even add “and what are we doing to it in the ETL process?” If you are one of the many, that either do not have complete end

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Documentation – Full Printable

- Fully automated generation of Documentation, including full version control to ensure that the generated documentation corresponds to the deployed version of the project. Comments can be added to all elements in the project. The template can be modified and the documentation comes as a hyperlinked PDF document. The documentation is valid for IT Audit

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Indexes

TX2014 supports both automatic created indexes as well as rich capabilities to add your own non clustered indexes to fine tune the load performance of your data warehouse platform. Automatic indexes are added based on table classification such as dimension/fact/large/normal and transformations done on a table, to ensure well performing code out of the box.

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Lookups

One of the most commonly features of TX2014 is the ability to look up a value across tables using a simple drag and drop interface. Lookups can be used to perform both simple tasks as fetching a single value from a related table based on one or more joined fields, but also in more complex

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Time Dimensions

The most common of all dimensions is time, since there is virtually no reporting or analysis done without the context of when. A time or calendar dimension can always be derived of source data, as any other dimension. Additionally you can also take advantage of the time table and time dimension features in TX2014 to

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Incremental Load

To improve load performance for very large tables, a feature called Target-based Incremental Load was introduced with timeXtender version 4.5. This feature controls how data is inserted, updated, and deleted between the raw and valid table instances. The Target-based Incremental Load feature is especially useful in scenarios where the source system cannot reliably identify new

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Slowly Changing Dimensions

Slowly changing dimensions type 1 and 2 is a key to Kimball style dimensional modeling and is of course supported in TX2014 with an easy to use interface, that allows implementation within minutes – without any SQL knowledge required. The TX2014 implementation further includes the use of hashed values for better performance on large dimensions.

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