> For the complete documentation index, see [llms.txt](https://documentation.astera.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://documentation.astera.com/astera-data-stack-v6/dataflows/transformations/introducing-transformations.md). # Introducing Transformations Transformations are used to perform a variety of operations on data as it moves through the dataflow pipeline. Astera Data Stack provides a full complement of built-in transformations enabling you to build sophisticated data maps. Astera Data Stack transformations are divided into two types— record-level and set-level. ## **Record-level Transformations** Record-level transformations are used to create derived values by applying a *Lookup*, *Function*, or *Expression* to fields from a single record. Examples of record-level transformations include *Lookups*, *Expressions*, and *Function* transformations. In Astera, data records flow between set transformations. Record-level transformations are used to transform or augment individual fields during these movements. A record-level transformation can be connected to only one set transformation. For instance, a *Lookup* or *Expression* cannot receive input from two different set transformations. ## **Set-level Transformations** Set-level transformations, on the other hand, operate on a group of records and may result in the Joining, Reordering, Eliminating, or aggregating of records. Examples of set transformations include *Join*, *Sort*, *Route*, *Distinct*, etc. *Data Sources* and *Destinations* are also considered set transformations. Other than transformations that enable combining multiple data sources—such as *Join*, *Merge*, and *Union*—transformations can receive input from only one set transformation. Transformations, however, can receive input from any number of record-level transformations as long as all these record-level transformations receive input from the same transformation. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://documentation.astera.com/astera-data-stack-v6/dataflows/transformations/introducing-transformations.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.