Stitch makes extracting data from a source and loading it into a data warehouse easy. The next step is setting up an ETL pipeline to replicate data from your sources to the data warehouse. If you choose Redshift, Snowflake, or one of the other destinations Stitch supports, you can follow the setup steps in the Stitch documentation. I picked Panoply, a platform that provides a managed version of Redshift. If you don't already have a data warehouse, choose one that meets your needs. The first step was to choose or set up a data warehouse to hold the data I'd be replicating from Salesforce and Intercom. To find out, I needed to use billing data stored in Salesforce and join it with support conversation data from Intercom to create a visualization. Specifically, I was curious to see how many support conversations came from each of our pricing tiers. I used some of Stitch’s real data to build a data visualization for this post. It can connect with more than two dozen data sources, including data warehouses like Amazon Redshift and Snowflake databases like MySQL, PostgreSQL, and Microsoft SQL Server and AWS services like Aurora, Athena, and S3. Once you have data in your data warehouse you can use QuickSight for business intelligence (BI). Most businesses get more value out of their data as they integrate more data sources for our example, we'll look at data from two separate SaaS applications. Choose at least one of Stitch's integrations as a data source. If your organization already uses a data warehouse, you can sign up for Stitch and be moving data to your destination in five minutes. It can move data from dozens of data sources to several different data warehouses. Stitch is a simple, powerful ETL service for businesses of all sizes, up to and including the enterprise. You can extract data that you have stored in SaaS applications and databases and load it into the data warehouse using an ETL (extract, transform, load) tool. Most businesses take advantage of cloud data warehouses such as Amazon Redshift or Snowflake.

To analyze data from diverse sources, you need a data warehouse that consolidates all of your data in a single location. In this tutorial, we’ll show you how QuickSight can help you deliver business insights.

How do you begin combining data from SaaS applications with your internal databases to gain insight into your business? Maybe your organization has already standardized on Amazon QuickSight as your analytics tool, but you're still learning about using it with multiple data sources. Tutorial: Using Redshift and Amazon QuickSight to deliver business analytics

Redshift tutorial