Developer at a educational organization with 51-200 employees
Real User
Top 5
Jun 16, 2026
My main use case for Stitch is to integrate retail data and connect different sources seamlessly. I mostly use it for moving data into a central warehouse, so I can easily analyze and build visualization dashboards without worrying about manual pipelines. A specific example where I used Stitch for integrating retail data involves a project with a scrap pickup and recycling service. We had user orders coming from a web app database and offline transactional data scattered across different spreadsheets. Stitch saved us a ton of time by automatically consolidating all that retail and transactional data directly into the warehouse. It made it super easy for us to track active orders and analyze patterns without doing any manual data dumping. Regarding my main use case for Stitch, the most unexpected thing was how easily it handles sudden spikes in data volume. When our order traffic jumped out of nowhere, I thought the pipeline might lag or drop rows, but it scaled perfectly without any manual tweaking. It completely saved me from spending a weekend troubleshooting broken schemas or API connections.
All of these things totally depend upon your business logic. If you want to remove duplicates or you want to implement some kind of format for postal addresses, like keeping pin codes in this format, you can customize your code accordingly and then you can get consistency in the data. Since the way everyone is moving towards AI, my suggestion will be to lean more towards natural language processing. So rather than writing proper SQL, the way Snowflake is processing or Cloudera is processing things, they should also have a chatbot or something similar where we can simply write things, it understands that particular thing and enhances that particular thing at the back end. I do remember I used to work for geographical interfaces, where we needed most of the location information. It was a petroleum extraction client. So we needed the location and everything. For that, we used libraries that were more focused on getting the basic distance between two geographical locations and everything. Those kinds of functions, if we wanted to implement them, we used to extract that particular thing from the external libraries and use it.
Stitch is primarily used for integration between multiple systems in our environment. On top of that, we have data integration and data analysis. We draw information from multiple systems, both systems that we manage ourselves, and we have a number of data partners that manage their data. We hook into their environments, use their information and our information, mix it all up, and then develop new products. Primarily, we're using it for analysis around the data that's captured around the environment. Our council is responsible for looking after a large chunk of New Zealand and monitoring air and water and sea, and managing the quality of a large number of different environmental factors. We need to keep reporting that in real-time aggregation on a monthly and yearly basis. We're looking at how climate change is affecting our environment and reporting on anything about the environment.
Senior Data Maanger at a recreational facilities/services company with 10,001+ employees
Real User
Top 10
Jan 28, 2026
My main use case for Stitch is cost optimization. During my work, we wanted to optimize costs to manage expenses, so the tool was quite helpful in that regard, and I used it frequently in my day-to-day work together with the finance team to build better financial reporting.
head of data at a healthcare company with 11-50 employees
Real User
Top 10
Jan 19, 2026
I have been using Stitch for the past two years in two different companies. My main use case for Stitch is connecting to third-party apps, extracting the data out of them, and transferring it into our data warehouse. A specific example of a third-party app I connect with is Shopify, where we are selling products. In Shopify, we have all the sales database, and we connect to that database through Stitch to our BigQuery in order to perform analysis on our Shopify data. We work with many apps connected to our data warehouse through Stitch. In addition to Shopify, we have all the Facebook data, metadata, and TikTok data.
Cloud Data Architect at a comms service provider with 10,001+ employees
Real User
Top 10
Dec 2, 2025
I have been using Stitch for the last five years. My main use case for Stitch is to ingest SFDC data and also Google Analytics, Facebook Ads, and GA4. I use Stitch as a data ingestion tool for SFDC, and I load the data into Redshift. I use the Bulk and REST APIs to do the incremental loads. I also use it for Google Analytics and Facebook Ads.
Stitch is a cloud-based ETL service designed to synchronize data between a variety of sources and destinations, offering robust and scalable data integration capabilities.Stitch facilitates seamless data integration, providing users with real-time data movement across their tech stack. Its flexible architecture allows easy connectivity between diverse systems and ensures data consistency. With its user-friendly setup, Stitch empowers data teams to efficiently manage complex data workflows,...
My main use case for Stitch is to integrate retail data and connect different sources seamlessly. I mostly use it for moving data into a central warehouse, so I can easily analyze and build visualization dashboards without worrying about manual pipelines. A specific example where I used Stitch for integrating retail data involves a project with a scrap pickup and recycling service. We had user orders coming from a web app database and offline transactional data scattered across different spreadsheets. Stitch saved us a ton of time by automatically consolidating all that retail and transactional data directly into the warehouse. It made it super easy for us to track active orders and analyze patterns without doing any manual data dumping. Regarding my main use case for Stitch, the most unexpected thing was how easily it handles sudden spikes in data volume. When our order traffic jumped out of nowhere, I thought the pipeline might lag or drop rows, but it scaled perfectly without any manual tweaking. It completely saved me from spending a weekend troubleshooting broken schemas or API connections.
All of these things totally depend upon your business logic. If you want to remove duplicates or you want to implement some kind of format for postal addresses, like keeping pin codes in this format, you can customize your code accordingly and then you can get consistency in the data. Since the way everyone is moving towards AI, my suggestion will be to lean more towards natural language processing. So rather than writing proper SQL, the way Snowflake is processing or Cloudera is processing things, they should also have a chatbot or something similar where we can simply write things, it understands that particular thing and enhances that particular thing at the back end. I do remember I used to work for geographical interfaces, where we needed most of the location information. It was a petroleum extraction client. So we needed the location and everything. For that, we used libraries that were more focused on getting the basic distance between two geographical locations and everything. Those kinds of functions, if we wanted to implement them, we used to extract that particular thing from the external libraries and use it.
Stitch is primarily used for integration between multiple systems in our environment. On top of that, we have data integration and data analysis. We draw information from multiple systems, both systems that we manage ourselves, and we have a number of data partners that manage their data. We hook into their environments, use their information and our information, mix it all up, and then develop new products. Primarily, we're using it for analysis around the data that's captured around the environment. Our council is responsible for looking after a large chunk of New Zealand and monitoring air and water and sea, and managing the quality of a large number of different environmental factors. We need to keep reporting that in real-time aggregation on a monthly and yearly basis. We're looking at how climate change is affecting our environment and reporting on anything about the environment.
My main use case for Stitch is cost optimization. During my work, we wanted to optimize costs to manage expenses, so the tool was quite helpful in that regard, and I used it frequently in my day-to-day work together with the finance team to build better financial reporting.
I have been using Stitch for the past two years in two different companies. My main use case for Stitch is connecting to third-party apps, extracting the data out of them, and transferring it into our data warehouse. A specific example of a third-party app I connect with is Shopify, where we are selling products. In Shopify, we have all the sales database, and we connect to that database through Stitch to our BigQuery in order to perform analysis on our Shopify data. We work with many apps connected to our data warehouse through Stitch. In addition to Shopify, we have all the Facebook data, metadata, and TikTok data.
I have been using Stitch for the last five years. My main use case for Stitch is to ingest SFDC data and also Google Analytics, Facebook Ads, and GA4. I use Stitch as a data ingestion tool for SFDC, and I load the data into Redshift. I use the Bulk and REST APIs to do the incremental loads. I also use it for Google Analytics and Facebook Ads.
Our primary use case for Stitch is tax and targets extraction. I am not familiar with any other feature of Stitch.