- 08 Sep 2021
- 1 Minute to read
Welcome to Panoply Documentation
- Updated on 08 Sep 2021
- 1 Minute to read
Panoply is a data management platform that makes it easy to connect and manage data from multiple sources. It stores the collected data in either Google BigQuery or Amazon Redshift, and integrates with tools such as Metabase, Tableau, Data Bricks, Looker, Jupyter Notebook, RStudio and QlickView. Panoply also provides advanced settings for users to control how the data is collected. Additionally, it uses the latest security measures to protect customer data and offers IP whitelisting for access control.
Welcome to Panoply, we're glad you're here. The documentation contained in these pages will help you get started collecting and managing your data from all of your data sources.
Connecting to your Data Sources
Panoply makes it easy to connect your many data sources. You can set up any major database as a data source, ingest data via file upload, or choose one of the APIs Panoply supports. For most data sources the initial setup takes only minutes, but for advanced control of the data, there are a number of advanced settings that users can modify to manage how the data is collected.
These include things like primary and incremental keys, destinations, schemas and how nested data is handled.
Your Data Warehouse
Once your data is collected, it is stored in your data warehouse, built in either Google BigQuery or Amazon Redshift.
Analyzing Your Data
As long as the tool you want to connect to Panoply uses ODBC/JDBC or has a built-in connector for Google BigQuery, Postgres or AWS Redshift, you should be able to use the same connection details for everything.
We value our customers, so we use the latest security measures. The Data Security guide explains how Panoply protects your data, our approach to access control, and details about IP whitelisting.