DoSomething.org had multiple streams of information flowing into its data warehouse from many different sources and technologies. Its data engineers had to write a lot of brittle custom code, and the company endured frequent outages or breakages. Sohaib Hasan, Director of Analytics, found that critical dashboards failed to show key information, engineers spent hours troubleshooting issues, and analysts had little confidence in the data.
DoSomething.org didn’t want to spend its time and resources on ETL. It made sense, therefore, to plug in an existing solution. Now, instead of spending 20–30% of their time maintaining existing code and fighting fires, DoSomething.org’s engineers can focus exclusively on valuable tasks.
The ability to add new connectors quickly and easily is a large motivator for bringing on new data sources. Recently, the business decided to replace its internal solution for capturing website data with Snowplow, knowing that Fivetran had a Snowplow connector. In the past, an integration like this would have taken up to a full financial quarter to complete, but with the Fivetran connector, it only took a week.
The business can now make faster, more informed decisions and scale more quickly. Fivetran has opened the doors to many data sources that the business would have avoided in the past because of the data integration difficulty. With connectors from Fivetran, the key consideration is not how long an integration will take or how difficult it will be, but how much value it will add.
About DoSomething.org: DoSomething.org is a digital platform powering offline action. It enables millions of young people in 131 countries to transform their communities through volunteer, social change and civic action campaigns.
About Fivetran: Shaped by the real-world needs of data analysts, Fivetran technology is the smartest, fastest way to replicate your applications, databases, events and files into a high-performance cloud warehouse. Fivetran connectors deploy in minutes, require zero maintenance, and automatically adjust to source changes — so your data team can stop worrying about engineering and focus on driving insights.