# Data Transformation

Generally, businesses want to transform data to for the following reasons:

* make it compatible with other data
* move it to another system
* join it with other data
* aggregate information in the data


As organizations bring in data from various sources, data transformation is used to unify the data into a single database. Here are some example use cases:

* You are moving your data to a new data store; for example, you are moving to a cloud data warehouse and you need to change the data types.
* You want to join unstructured data or streaming data with structured data so you can analyze the data together.
* You want to add information to your data to enrich it, such as performing lookups, adding geolocation data, or adding timestamps.
* You want to perform aggregations, such as comparing sales data from different regions or totaling sales from different regions.
* You want to mask data to protect privacy. Filter functions allow you to mask sensitive data as you bring it from one data source into another.


This section contains the following topics:

* [Merging Data](/products/customer-data-platform/data-workbench/queries/merging-data)
* [About Filter Functions](/products/customer-data-platform/integration-hub/batch/import/filter/about-filter-functions)
* [Data Science and SQL Tools](/tools/cli-and-sdks/data-science-and-sql-tools)