No more broken pipelines

Defining data tasks in our easy to use user interface is a way for your data teams to rapidly innovate.  Whereas, defining important data tasks in code allows your teams to test all their changes and be sure any changes are fully functional before release to production.

PipelineML is the Matatika technology that enables data teams to use either approach or a combination of both.

Learn more about orchestrating data actions as code

Save time, put your project on autopilot

Using the Matatika Lab, scheduling hourly, daily, weekly, or any schedule you can imagine is a piece of cake.  Data teams can also start pipelines manually and watch as the data flows into the data warehouse.

Pipelines can be configured to follow other pipelines and configured with retry actions.  Creating a powerful capability to get your data work done without fuss.

Resolve issues quickly

One place to investigate and debug issues helps you rapidly resolve any issues.  The Matatika Lab takes care of monitoring and alerting your data teams if an issue occurs and all the information about any issues are collected and immediately available.

Being able to reproduce the environment with an exact copy locally means that you can get from issue to fix faster than ever.