> For the complete documentation index, see [llms.txt](https://docs.predicthq.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.predicthq.com/integrations.md).

# Integrations

- [Integration guides](https://docs.predicthq.com/integrations/integration-guides.md)
- [Standard integration pattern](https://docs.predicthq.com/integrations/integration-guides/standard-integration-pattern.md)
- [Internal grounding: retrieval inside your environment](https://docs.predicthq.com/integrations/integration-guides/internal-grounding.md): Reference architecture for internal grounding: retrieving verified PredictHQ event context inside your own environment at answer time, so your AI systems respond from facts they can cite.
- [Keep data updated via API](https://docs.predicthq.com/integrations/integration-guides/keep-data-updated-via-api.md): Event information changes frequently. For example, a date changes, an event gets cancelled or ranking is updated. It’s important to keep your data set up to date.
- [Loading event data into a data warehouse](https://docs.predicthq.com/integrations/integration-guides/loading-event-data-into-a-data-warehouse.md): Take PredictHQ API data and load it into a data warehouse, in this example, GCP BigQuery.
- [Integrate with Loop Links](https://docs.predicthq.com/integrations/integration-guides/integrate-with-loop-links.md): Loop Links provide an easy way for you submit missing Events and provide feedback on existing Events.
- [Third-party integrations](https://docs.predicthq.com/integrations/third-party-integrations.md)
- [Receive data via Snowflake](https://docs.predicthq.com/integrations/third-party-integrations/snowflake.md)
- [Example SQL queries for Snowflake](https://docs.predicthq.com/integrations/third-party-integrations/snowflake/example-sql-queries-for-snowflake.md)
- [Snowflake data science guide](https://docs.predicthq.com/integrations/third-party-integrations/snowflake/snowflake-data-science-guide.md): Transforming Event Data into ML-Ready Features in Snowflake
- [Snowpark method guide](https://docs.predicthq.com/integrations/third-party-integrations/snowflake/snowflake-data-science-guide/snowpark-method-guide.md): Transforming Event Data into ML-Ready Features using Snowpark and Python
- [SQL method guide](https://docs.predicthq.com/integrations/third-party-integrations/snowflake/snowflake-data-science-guide/sql-method-guide.md): Transforming Event Data into ML-Ready Features using SQL
- [Receive data via AWS Data Exchange](https://docs.predicthq.com/integrations/third-party-integrations/aws-data-exchange.md)
- [CSV/Parquet data structure for ADX](https://docs.predicthq.com/integrations/third-party-integrations/aws-data-exchange/csv-parquet-data-structure-for-adx.md): Data can be provided as NDJSON, CSV or Parquet. This document describes the CSV/Parquet data structure.
- [NDJSON data structure for ADX](https://docs.predicthq.com/integrations/third-party-integrations/aws-data-exchange/ndjson-data-structure-for-adx.md): Data can be provided as NDJSON, CSV or Parquet. This document describes the NDJSON data structure.
- [Receive data via SFTP](https://docs.predicthq.com/integrations/third-party-integrations/sftp.md)
- [Integrate with Databricks](https://docs.predicthq.com/integrations/third-party-integrations/integrate-with-databricks.md): Deploy PredictHQ's verified real-world context into Databricks via S3 or Snowflake for model training, inference-time features, and grounding AI systems.
- [Using event data in Tableau](https://docs.predicthq.com/integrations/third-party-integrations/using-event-data-in-tableau.md): Learn how to connect PredictHQ data to Tableau and build an example dashboard.
- [Using event data in Power BI](https://docs.predicthq.com/integrations/third-party-integrations/using-event-data-in-power-bi.md): Learn how to connect PredictHQ data to Power BI using multiple methods, and build an example report.
- [Connecting to PredictHQ APIs with Microsoft Excel](https://docs.predicthq.com/integrations/third-party-integrations/connecting-to-predicthq-apis-with-microsoft-excel.md): Learn how to connect PredictHQ data to Microsoft Excel using APIs.


---

# 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.predicthq.com/integrations.md?ask=<question>&goal=<endgoal>
```

`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.