> ## Documentation Index
> Fetch the complete documentation index at: https://developer.mindbridge.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Data Catalog Entries

**Data catalog entries** are curated remote and local data sets accessible in MindBridge. These data sets can be annotated on the table and
column level and can be queried to produce a data table.

Currently, the following data sources can be used to create data catalog entries:

**MindBridge data tables**

A data catalog entry can reference an existing MindBridge data table. These catalog entries must have their `source` field set to
`DATA_TABLE`, and a valid `dataTableId` set to a data table ID. Data catalog entries can use all data tables accessible by the API as
sources.

**Connection tables**

Tables provided by the connections feature can be used in data catalog entries. These catalog entries must have their `source` field set to
`CONNECTION`, and both connectionId and tableId values set.

Data catalog entries are not actively validated for alignment with their underlying source and may need to be manually validated and
corrected if the remote source’s schema is not compatible with the schema provided by the data catalog entry.

The data catalog does not need to include all columns provided by the remote source, but the name and columnType fields of the columns must
align with the underlying source name and type respectively. Columns that are not nullable in the source may not be nullable in the data
catalog.

Failure to properly align the column schemas may result in errors when attempting to read data from the data catalog entry. Data types are
not implicitly converted, so the exact same data types must be present in the data source and the data catalog entry.

**Notice**: This endpoint is part of a feature under active development. It may be subject to change in future releases. For more
information, please contact your MindBridge account representative.