> For the complete documentation index, see [llms.txt](https://docs.pentaho.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.pentaho.com/pdia-data-integration/readme.md). # Pentaho Data Integration 11.0 Pentaho Data Integration (PDI) provides the Extract, Transform, and Load (ETL) capabilities that facilitate the process of capturing, cleansing, and storing data using a uniform and consistent format that is accessible and relevant to end users and IoT technologies. If you or your administrator has not already installed PDI on your system, see the [Install Pentaho Data Integration and Analytics](https://docs.pentaho.com/install/) document for details. Get started with Pentaho Data Integration (PDI) by learning core ETL concepts, data types, client setup, and project organization. * [Basic concepts of ETL in PDI](/pdia-data-integration/basic-concepts-of-pdi.md) PDI uses a workflow metaphor as building blocks for transforming your data and other tasks. Workflows are built using steps or entries as you create transformations and jobs. Each step or entry is joined by a hop which passes the flow of data from one item to the next. * [Understanding PDI data types and field metadata](/pdia-data-integration/understanding-pdi-data-types-and-field-metadata.md) As a best practice for producing consistent, predictable outcomes when working with your data in PDI, you must consider how the Pentaho engine processes different data types and field metadata in transformations and jobs. * [Starting the PDI client](/pdia-data-integration/start-the-pdi-client.md) After you have installed Pentaho Data Integration (PDI), you can use the PDI client (also known as Spoon) desktop application to start building transformations of your data. * [Use the PDI client perspectives](/pdia-data-integration/use-the-pdi-client-perspectives.md) Pentaho Data Integration (PDI) empowers you with tools that include ETL and scheduling in one unified environment — the PDI client interface. This integrated environment enables you to work in close cooperation with business users to build business intelligence solutions more quickly and efficiently. --- # 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://docs.pentaho.com/pdia-data-integration/readme.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.