Agenda

Join CEOs across the data stack as they open our 1.5 days together.

For teams with robust, fully built-out modern data stacks, what’s next? In this session, we’ll hear from leaders who have built and scaled their stacks and are now tackling next-gen tasks. From ML operations to instant movement of massive amounts of data around the world, we’ll learn how folks with mature data stacks are pushing the boundaries of what their companies and teams can do with data.

Moving from an older, legacy stack to a modern one isn’t something that happens overnight - and bringing your internal stakeholders as well as your team along is often one of the trickiest parts of this transition. At this session, we’ll talk with folks who are making the transition from legacy systems to the latest and greatest modern data stacks. They’ll offer advice for how they got started, what their biggest hurdles were and what they wish they had known at the start. And, we’ll dig into not just the technical challenges with transitioning but the cultural and mindshift changes needed to bring everyone along.

One of the hottest topics in the data space is “data fabric,” but what is it — and what makes it different from “data mesh” or any other buzz term? Is it actually achievable? What does it mean for data governance? In this session, you’ll get an honest take on this term, including what it promises to deliver and whether the promises can be kept.

It feels like every month there’s a new tool, system or program that is going to transform the way we use data. Keeping up with all these trends and changes feels overwhelming — and how can one separate the real innovations from the overpromising, far-too-niche players? At this session, we’ll have a healthy debate about all the changes to the MDS of late, the latest MDS tools and trends, and the best ways to keep up with the changes.

Once you’ve proven the power of data and your data team at your company, the next question is, “How can I get more?” But that request doesn’t always lead to more resources — especially at early-stage companies. In this session, you’ll hear from data professionals who have learned to do more with less; specifically, we’ll focus on how teams can move from request backlogs to proactive data teams. You’ll learn what they wish they had done differently as they scaled, and which tools, programs and resources they relied on.

dbt continues to gain traction and popularity, and for good reason. At this session, we’ll bring together dbt power users to hear how and why they got into dbt, as well as some of their best practices for getting started and ramping up. Whether you are a dbt pro or just dipping your toes in, this session will ensure that you’re set up for success and using best practices moving forward.

Following a day packed with all things data fabric, transformations and next-gen use cases, learn about the future of Fivetran and how it fits into the broader picture. Join Fivetran VP of Product Fraser Harris as he walks us through how Fivetran as a platform will keep up with the needs of data teams and respond to the demands of the data industry. He’ll also discuss the Fivetran product philosophy and how we’re changing what it means to move data.

The modern data stack (MDS) as a concept hasn’t been around that long, but folks across Twitter and LinkedIn have already started calling it a thing of the past. We’ll close out our day by debating the elephant in the room: What is the modern data stack, really? Is it just a set of tools? An approach to data? Do we need a new phrase? Should we lean into the concept even more — or retire it altogether? Join us for a spirited debate.

Join us to celebrate closing out day one with food, drinks and enticing activations - you won’t want to miss it!

The pace of innovation continues unabated — especially across the global supply chain, where logistics challenges have made data and a data-driven mindset critical to ensuring the efficient flow of goods around the world. In this session, you’ll hear from leaders across manufacturing, retail, transportation and logistics about how the intersection of shrewd business leadership and a modern data stack will drive massive innovation amidst a turbulent market.

In the history of data engineering, there have always been two dichotomous approaches: write custom code (typically in Python) or use a no-or low-code tool such as Fivetran. These worlds are now merging and for good reason. Data teams have massive scope and responsibilities today, and they want to focus their limited resources on the most critical problems that require human ingenuity — and frankly are a lot more fun. Join this session to learn why companies today are outsourcing connections and dataflows to vendors like Fivetran to manage the hundreds of API endpoints while maintaining control and viability with a tool like Prefect.

Fivetran integrates with dbt Core to power our transformations in your preferred cloud destination. dbt Core, by dbt Labs, is an open-source transformation tool that enables you to perform sophisticated data transformations in your destination using simple SQL statements.
During our hands-on lab, we’ll walk you through setting up transformations and show you how to:
- Integrate dbt Core with Fivetran
- Use version control and other advanced features with your transformations
- Run your first job using Fivetran pre-built data models to model your data In order to participate in this lab, you must have a Fivetran account and complete prework (which will be sent to you when you register). Sign up for a 14-day free trial here. Please note: pre-work may take up to 2 hours to complete, so plan accordingly. Requirements and details will be shared ahead of time.

Stop in and talk with MDS experts on topics including data movement, transformation, governance, security and ecosystem integration. We can help you troubleshoot issues, ask for advice or just discuss trends with our team of experts.

Learn how replication methods have changed to evolve with data warehouse advancements and best practices for replicating data to the cloud, especially for high volume data. We’ll walk through the different replication techniques, when teams use them and why, and how to identify when you might need to change your replication strategy. 

The modern data stack has been long known by its parts: automated data movement, data governance, BI, reverse ETL, AI/ML and more. But as the stack has matured, more have joined in. At this session, hear from leaders at hot startup companies as they offer quick-fire takes on how they are changing the face of the modern data stack even further.

Your data is yours to protect. Whether you’re moving into the cloud or built there to start, you'll need to ensure your cloud infrastructure is secure and compliant. Learn from Fivetran's security team about best practices for cloud SaaS security for every use case from multi-cloud to PCI compliance.

Handling updated schemas — if it isn’t automated during data movement — is responsible for creating some of the most time-consuming work for downstream teams. A new trend is to look to developers who keep changing schemas as they update the products to see if the problem can be addressed at its source. In this discussion, we’ll dive into this trend and all things schemas-related.

Real time means a lot of things to different businesses. At this session, join the conversation about the reality of real-time data including how to define it, how to accomplish it and what it can do for your business — including a hearty debate on whether the cost of real-time data is worth the impact on your business. 

Getting more of your teams — think Marketing, Sales and Finance — access to the data they need without creating bottlenecks or compromising on compliance is the promise of data democratization. We’ll break down what data democratization means and discuss the step-by-step process organizations are implementing to achieve this vision and the benefits it is already having on their bottom line. 

Cloud functions, file connectors and now Lite connectors. Sit with our Product team as they walk you through the different connectors, how they work and how you can automate any data source you need. Plus, give feedback on the connectors themselves in this conversational connector-centric session.

Getting started is often the most challenging part when building (Machine Learning) ML projects. How should you structure your repository? Which standards should you follow? This session will discuss best practices for structuring data science projects to ensure they are readable, testable, well-documented, and reproducible.

At this session, we’ll cover the top trends in ELT and the modern data stack. We’ll have honest takes on the latest fundings, mergers and acquisitions — and just all around have a healthy, engrossing debate on the latest news hitting the MDS community from key figures within it. 

Beyond the value of your data, what is it worth? Data products represent net new revenue with hardly any incremental costs. In this session, hear from experts on the new trend of “data sharing,” debate what it means and how teams are taking steps towards making this new trend a reality.