There are countless sources of data that are publicly available for use. Unfortunately, combining those sources and making them useful in aggregate is a time consuming and challenging process. The team at Enigma builds a knowledge graph for use in your own data projects. In this episode Chris Groskopf explains the platform they have built to consume large varieties and volumes of public data for constructing a graph for serving to their customers. He discusses the challenges they are facing to scale the platform and engineering processes, as well as the workflow that they have established to enable testing of their ETL jobs. This is a great episode to listen to for ideas on how to organize a data engineering organization.

Your Data Scientist finished a new Machine Learning model, so he sends you his python script and wishes you good luck. Now you have to figure out where to put it and plead with DevOps to deploy it. Not to mention write the API to consume the model’s results.

Wouldn’t it make your job easier if the Data Science team could build, train, deploy and monitor their models independently? Metis Machine agrees.

Meet Skafos, the machine learning platform that enables teams of data scientists to drastically speed up the time to market by providing tools and workflows that are familiar and easy. Serverless ML production deployment is as simple as “git push”. Skafos orchestrates your jobs seamlessly, guaranteeing they will run.

Skafos handles the tedious and time-consuming work of applying Machine Learning at scale so you can focus on what you do best.

The team here at Metis Machine shipped a proof-of-concept integration between our powerful machine learning platform Skafos, and the business intelligence software Tableau. BI teams can now invoke custom-built machine learning models built by in-house science teams.

Does that sound awesome? It is.

Join Metis Machine’s free webinar to walk through the architecture of this extension, demonstrate its capabilities in real time, and lay out a use case for empowering your BI team to modify machine learning models independently and immediately see the results, right from Tableau. You have to see it to believe it. So join us on October 11th at 2 PM ET (11 AM PT) and see what

Skafos + Tableau can do.

To register, go to metismachine.com/webinars

Your data platform needs to be scalable, fault tolerant, and performant, which means that you need the same from your cloud provider. Linode has been powering production systems for over 17 years, and now they’ve launched a fully managed Kubernetes platform. With the combined power of the Kubernetes engine for flexible and scalable deployments, and features like dedicated CPU instances, GPU instances, and object storage you’ve got everything you need to build a bulletproof data pipeline. If you go to dataengineeringpodcast.com/linode today you’ll even get a $60 credit to use on building your own cluster, or object storage, or reliable backups, or… And while you’re there don’t forget to thank them for being a long-time supporter of the Data Engineering Podcast!