Editing Extract, transform, load (section)

=== Load ===

The load phase loads the data into the end target, which can be any data store including a simple delimited flat file or a [[data warehouse]]. Depending on the requirements of the organization, this process varies widely. Some data warehouses may overwrite existing information with cumulative information; updating extracted data is frequently done on a daily, weekly, or monthly basis. Other data warehouses (or even other parts of the same data warehouse) may add new data in a historical form at regular intervals – for example, hourly. To understand this, consider a data warehouse that is required to maintain sales records of the last year. This data warehouse overwrites any data older than a year with newer data. However, the entry of data for any one year window is made in a historical manner. The timing and scope to replace or append are strategic design choices dependent on the time available and the [[business]] needs. <!-- is this part of "load"? -->More complex systems can maintain a history and [[audit trail]] of all changes to the data loaded in the data warehouse.
As the load phase interacts with a database, the constraints defined in the database schema – as well as in triggers activated upon data load – apply (for example, uniqueness, [[referential integrity]], mandatory fields), which also contribute to the overall data quality performance of the ETL process.

* For example, a financial institution might have information on a customer in several departments and each department might have that customer's information listed in a different way. The membership department might list the customer by name, whereas the accounting department might list the customer by number. ETL can bundle all of these data elements and consolidate them into a uniform presentation, such as for storing in a database or data warehouse.
* Another way that companies use ETL is to move information to another application permanently. For instance, the new application might use another database vendor and most likely a very different database schema. ETL can be used to transform the data into a format suitable for the new application to use.
* An example would be an [[expense and cost recovery system]] such as used by [[Accounting|accountants]], [[consultant]]s, and [[law firm]]s. The data usually ends up in the [[Law practice management software|time and billing system]], although some businesses may also utilize the raw data for employee productivity reports to Human Resources (personnel dept.) or equipment usage reports to Facilities Management.