James Densmore

The modern data stack is empowering data teams to work in ways that were unimaginable 5-10 years ago. From data engineers building efficient data pipelines, to analytics engineers adopting software engineering best practices, open source makes it possible. James will discuss how we got here, and how open source fits technically and strategically on data teams today.

Keynote

Keynote Speaker

Alex Dean

We believe that in order to build a scalable open source data stack, you need a powerful behavioural data engine to collect, enrich and deliver behavioral event data to event streams, data warehouses and data lakes. I’ll discuss what the possibilities are when you are able to collect behavioral data from all of your platforms and channels, enrich it and deliver it to the places you need it. 

Behavioral: Snowplow

Co-Founder and CEO

Max Beauchemin

Now that you have a modern data stack to handle storage and computation, it’s time to choose a business intelligence platform to enable your organization to create and socialize visual insights from your data. In this talk, I’ll discuss my frustrations with proprietary BI platforms and what led me to help create Apache Superset. I’ll make the case for why the future of business intelligence is open source and end with a demo of Superset in action.

Analyze: Superset

Founder and CEO

Emilie Schario 

The modern data stack has evolved in a way that gives data teams the power to create the right solution for their needs. In this round table with all our speakers, we explore this evolution and the role open source is playing.

Round Table

Senior Manager, Data and BI / Roundtable Referee

Taylor A Murphy, PhD

Before you can dive into your data and uncover insights for your organization, you’ll face a challenge every data professional has encountered: data movement. Instead of writing custom code to run an extract and load job, wouldn’t it be better if there were other data professionals you could work with to solve this problem? We think so! In this session we’ll show how a community-driven, open source approach is the best way to build the foundation, and future, of any data stack.

ELT: Meltano

Head of Product and Data

Julia Schottenstein

Learn about what it means to be an analytics engineer. dbt is a transformation workflow that lets teams quickly and collaboratively deploy analytics code following software engineering best practices like modularity, portability, CI/CD, and documentation. Now anyone who knows SQL can build production-grade data pipelines. We’ll spend time talking about the workflows dbt enables and give a short demo of how the platform works.

Transform: dbt

Product Manager

Nick Schrock

You’ve got all the parts of your data stack set up -- now you have to make sure they work together. How do you make sure that upstream ingest jobs complete in time for your warehouse transforms to run? How do you integrate external tools with the Python notebooks that build your ML models? What happens when something breaks, and how do you find out? We’ll show you how an orchestrator lets you tame the dependencies between your tools and gives you visibility into your entire data platform.

Orchestration: Dagster

Brian Leonard

You have invested in your stack and now the warehouse has the data and insights to drive your business. See how Grouparoo can put that data to work in the tools your business uses like Salesforce, Mailchimp, and Zendesk.

Speakers