> 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/pba/9.3-analytics/data-source-wizard-cp-overview/choose-a-data-source-type.md).
# Choose a data source type
The Data Source Wizard supports several data source types for maximum flexibility. Each data source type is defined on where or how you store data. This table helps you decide which data source type is best for you.
| Explore Considerations | Choose Options | | |
| -------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| [CSV Files](/pba/9.3-analytics/data-source-wizard-cp-overview/choose-a-data-source-type/create-a-csv-data-source.md) | [SQL Queries](/pba/9.3-analytics/data-source-wizard-cp-overview/choose-a-data-source-type/create-a-sql-query-data-source.md) | [Database Table Data Sources](/pba/9.3-analytics/data-source-wizard-cp-overview/choose-a-data-source-type/create-a-database-table-source.md) | |
| Summary | A file with data that is separated by commas or some other specified delimiter character.
You can save an Excel spreadsheet as a CSV file and use this file to stage a database table in the Pentaho Repository.
If the data in the CSV file changes, you have to upload the updated file through the Data Source Wizard again.
CSV files can be uploaded directly to the Pentaho Repository without a data connection.
This option creates a multidimensional model for Analyzer only and a relational model for Interactive Reports, Dashboard Designer, and Analyzer.
| An SQL query written against a relational database defines the data you want to use in Interactive Reports or Analyzer.
You can customize how columns are presented to users who are building queries against the new data source; for example, you define column names and select options that indicate how data is aggregated (sum, min., max., etc.), and more.
This option creates a multidimensional model for Analyzer only and a relational model for Interactive Reports, Dashboard reports, and Analyzer.
| Database Table data sources allow you to create relational database tables containing the data you want to use in Interactive Reports or Analyzer.
This data source type supports a broad range of use cases including relational reporting directly against an operational data store (ODS) or creating a data source for multidimensional analysis against a star schema.
|
| Expertise | Knowledge of basic database structures. | Knowledge of basic database structures and SQL. | Knowledge of relational and/or multidimensional database structures. |
| Time | Approximately 10 minutes | Approximately 20 minutes | Approximately 30 minutes to 1 hour |
| Best Practices | This data source makes it easier to evaluate or create development prototypes. | This data source type works well when you are evaluating or creating development prototypes. | To use Database Table data sources for evaluating or creating development prototypes, limit the data in the tables to sample data that is representative of your production data. |
---
# 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 dynamically by asking a question.
Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:
```
GET https://docs.pentaho.com/pba/9.3-analytics/data-source-wizard-cp-overview/choose-a-data-source-type.md?ask=&goal=
```
`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.
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.