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April 19th, 2023

11:30AM - 4:00PM ET

VIRTUAL EVENT

Data Reliability Engineering Conference 2023

01 - Overview

One jam-packed day of data reliability engineering - trends, tools, and teams

First held in December 2021, DRE Con is the only conference to focus solely on data reliability engineering - the tools, processes, and people that make up the DRE ecosystem.

Join us virtually on April 19, 2023 for hands-on workshops, live Q&A, and presentations from standouts in the data space. What brings it all together? The willingness to dive straight into the most complex data reliability challenges of today and tomorrow.

02 - Speakers

Learn from the best in
data engineering

Demetrios
Brinkmann

Organizer

MLOps Community

Adi
Polak

VP of developer experience

Treeverse, the company behind lakeFS

Afua
Bruce

Founder

ANB Advisory Group

Chad
Sanderson

Founder and chief operator

Data Quality Camp

Ellora
Praharaj

Director of reliability engineering

Stack Overflow

Susan
Jensen

Analytics engineer

Great Expectations

Shinji
Kim

CEO

Select Star

Egor
Gryaznov

CTO and co-founder

Bigeye

Colin
Reid

Lead engineer: Data & intelligence

Trumid

Kyle
Kirwan

CEO, co-founder

Bigeye

Joe
Reis

best-selling author, data engineer and architect

Fundamentals of Data Engineering

03 - Schedule

Program for the
DRE conference

3:30 PM UTC

Kickoff: Welcome to Data Reliability Engineering

Speakers

Egor Gryaznov

Kyle Kirwan

Demetrios Brinkmann

Our emcee and Bigeye's co-founders kick off DRE Con 2023!

4:00 PM UTC

Data contracts: Accountable data quality

Speaker

Chad Sanderson

Founder and chief operator

Data Quality Camp

Modern data teams are struggling. This talk will walk teams through some of the root causes of data quality issues, and dive into what mature data ownership looks like.

4:30 PM UTC

Open source tools for data reliability engineering

Speaker

Adi Polak

VP of developer experience

Treeverse, the company behind lakeFS

How can you simplify the management of a data lake by enabling GIT-like operations? Experimenting, reproducing data, and guaranteeing data quality can be simple, with open source tooling. This talk will cover some great tools and methodologies for doing just that..

5:00 PM UTC

Reimagining risk and reliability

Speaker

Afua Bruce

Founder

ANB Advisory Group

How do we reimagine risk and reliability with best practices for user/customer/community engagement? This talk will explore lessons Afua Bruce has gleaned over the course of her extraordinary career, and how those can apply to better risk mitigation for data engineers.

5:30 PM UTC

A few ways to miserably fail with data

Speaker

Joe Reis

best-selling author, data engineer and architect

Fundamentals of Data Engineering

What are some of the common pitfalls of individuals and teams implementing tools and frameworks for data reliability? This talk explores, so you don't have to find out the hard way.

6:00 PM UTC

Data quality problems are interpersonal relationship problems

Speaker

Susan Jensen

Analytics engineer

Great Expectations

Let's rethink our data quality headaches as a symptom of a larger business problem. This talk covers some possible organizational and individual approaches to treat the root cause.

6:30 PM UTC

The unconventional path to data engineering

Speaker

Colin Reid

Lead engineer: Data & intelligence

Trumid

Colin Reid has had an unconventional path to the data industry. How do individuals without a traditional computer science or engineering background turn into data engineers? This talk explores.

7:00 PM UTC

What do gas stations and DRE have in common?

Speaker

Ellora Praharaj

Director of reliability engineering

Stack Overflow

With the explosion of data and technology, organizations need to enable their teams to self-service their data needs in order to scale. Let's look into how DRE can take cues from the gas stations of the world, and draw some important conclusions..

7:30 PM UTC

Data discovery vs. data observability: Understanding the differences for better dataOps

Speaker

Shinji Kim

CEO

Select Star

Data discovery and data observability are two critical components of the modern data stack, but they're often misunderstood and improperly scoped. In this session, we'll explore the differences, use cases for adoption, and ways in which the complementary disciplines help data teams operate more reliably.

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