June 2, 2023

Bigeye is sharing data reliability strategies for scale at Snowflake Summit 2023

Here's what's happening at Snowflake Summit 2023. Bigeye will take the stage with executives and customers to talk about data reliability at scale.

Kyle Kirwan

All of the data cloud world will be at Snowflake Summit in Caesars Forum in Las Vegas on June 26 through 29. This year, we’re thrilled to be a Blue Square Sponsor. Snowflake brings thousands of data professionals under one room for four jam-packed days of learning, networking, and fun.

The Bigeye team will be in attendance sharing how data reliability at scale can transform data and business teams. Stop by booth #1413 to meet the team, catch a live demo & grab some awesome swag to take home!  We’ll be presenting two talks featuring Bigeye executives and customers. They are:

How Canva Keeps Data Reliable at Scale

Who: Jaskirat Grover, Analytics Engineer at Canva, and Kyle Kirwan, CEO of Bigeye

When: Wed Jun 28, 2:00 PM - 2:45 PM PDT

Canva empowers more than 125 million people around the world to design anything and publish anywhere. Data has been at the heart of their explosive growth, helping Canva establish a leading position in the design world in just under a decade.Join Jaskirat Grover from Canva and Kyle Kirwan from Bigeye to hear how Canva’s data team ensures reliability for their mission-critical data pipelines. During this session, you’ll get a brief tour of key use cases for data at Canva, a first-hand glimpse into how Canva leverages Bigeye’s data observability platform on Snowflake, and will walk away with actionable ideas and inspiration for leveraging data observability to measure and improve the reliability of data at your organization.

Data Quality and Pipeline Reliability at Scale: Intro to Data Reliability Engineering (DRE)

Who: Kyle Kirwan, Co-founder and CEO of Bigeye

When: Tue Jun 27, 12:00 PM - 12:20 PM PDT

The best data teams run highly reliable data pipelines and deliver high quality data to their organizations. How do they manage this in the face of constantly increasing pipeline complexity and demand for data? Exceptional uptime for services like Google, Stripe, and Zoom are possible thanks to Site Reliability Engineers (SREs) working to prevent outages and ensure reliability. The world's best data teams are already borrowing and applying the same methodologies. Learn about the emerging field of Data Reliability Engineering (DRE) in this talk by Kyle Kirwan, Uber's former data operations leader and founder of Bigeye, a data observability company. You'll hear a brief history of data quality, get a tour of techniques used by data teams running planet-scale data pipelines (like Uber, AirBnB, and Netflix), and learn the seven principles of DRE that allow these teams to maintain reliability without slowing down.

We can’t wait

Our whole team is thrilled to be included in this event. Last year’s event focused on data governance, data outcomes, and the importance of collaboration. We’re excited to see what’s in store this year, for Snowflake’s biggest summit yet.

Request a meeting with our team at Snowflake Summit 2023 today!

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Monthly cost ($)
Number of resources
Time (months)
Total cost ($)
Software/Data engineer
Data analyst
Business analyst
Data/product manager
Total cost
Common needs
Data engineers
Overall data flow. Data is fresh and operating at full volume. Jobs are always running, so data outages don't impact downstream systems.
Freshness + volume
Schema change detection
Lineage monitoring
Data scientists
Specific datasets in great detail. Looking for outliers, duplication, and other—sometimes subtle—issues that could affect their analysis or machine learning models.
Freshness monitoringCompleteness monitoringDuplicate detectionOutlier detectionDistribution shift detectionDimensional slicing and dicing
Analytics engineers
Rapidly testing the changes they’re making within the data model. Move fast and not break things—without spending hours writing tons of pipeline tests.
Lineage monitoringETL blue/green testing
Business intelligence analysts
The business impact of data. Understand where they should spend their time digging in, and when they have a red herring caused by a data pipeline problem.
Integration with analytics toolsAnomaly detectionCustom business metricsDimensional slicing and dicing
Other stakeholders
Data reliability. Customers and stakeholders don’t want data issues to bog them down, delay deadlines, or provide inaccurate information.
Integration with analytics toolsReporting and insights

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