Data Quality in DataOps

As the world’s leading tool for data quality, Great Expectations occupies a unique position in the DataOps ecosystem. Over the last year, thousands of data scientists, engineers, and analysts have joined the Great Expectations community, making it one of the fastest-growing data communities in the world. In addition, Great Expectations integrates with many other DataOps tools, giving our developers a unique perspective on how the ecosystem is developing.
This presentation will share examples, patterns, and emerging best practices for data quality from the Great Expectations community. The first half of the talk will focus on nuts-and-bolts engineering, including common use cases and deployment patterns for data quality.  The second half of the talk will share learnings for how data quality and DataOps are reshaping data workflows and collaboration. Together this presentation will give you a clear view of how to get started with data quality, and where the field is going as a whole.

Abe Gong, Co-Founder & CEO @ Superconductive

I solve human-centric problems with data. I build teams that ask the right questions, and data systems to get the right answers. I am deeply committed to unlocking human potential with technology.

What is DataOps Unleashed?

DataOps Unleashed is the official DataOps community.

We came together on March 17 as the emergence of DataOps, CloudOps, AIOps, MLOps, and other professionals, who gathered virtually to share the latest trends and best practices for running, managing, and monitoring data pipelines and data-intensive analytics workloads.

Sessions included talks by DataOps professionals at leading organizations, detailing how they’re establishing data predictability, increasing reliability, and reducing costs.

Join us in Winter 2022 for the next DataOps Unleashed!

What is the cost to watch the virtual sessions?

DataOps Unleashed is always free and open for all to attend and view on-demand.

Join us for sessions on:

  • Data pipelines
  • Data orchestration
  • Metadata
  • Data quality
  • Data governance
  • Data science platforms
  • AIOps and MLOps
  • CloudOps
  • Migrations
  • Observability
  • Optimization
  • Operations

Who comes to DataOps Unleashed?

DataOps professionals and experts including data administrators, data architects, data engineers, data analysts, AI/ML professionals, and data technology leadership.

If you'd like to speak at DataOps Unleashed, send a note to

New to DataOps?

DataOps is a holistic approach to the creation, deployment, monitoring, management, and optimization of data-driven applications. It describes the culture and rules of engagement that allow data teams to deliver and maintain high-quality, on-time data products, often powered by AI and machine learning, in an agile and cost-effective way.

DataOps defines how data teams work and also affects data consumers and those whose work causes new data to be created and used within the organization. Their work enables the entire organization to access data efficiently for data-driven decision-making and for the creation and delivery of data-driven applications.

Organizations with well-developed DataOps strategies, governance, and processes can expedite the delivery of data-driven workflows and results faster and better than others.


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