The DevOps for Data Challenge:

Issues Moving Validation
Into DataOps CI/CD Pipelines

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DevOps for Data (DataOps) is a discipline that combines agile development, DevOps practices, and data management to accelerate and improve data analytics. 

The biggest challenges in implementing DataOps typically fall into several key areas:

  • Data Quality and Integrity.
    Inconsistent, incomplete, or outdated data undermines trust and analytics accuracy.
  • Lack of Automation.
    Manual testing, deployment, and orchestration slow down delivery cycles.
  • Siloed Teams and Tools.
    Data engineers, analysts, QA teams, and DevOps often work in isolation. Tooling for ETL testing, monitoring, and release management is fragmented and lacks interoperability.
  • Scalability of Processes.
    As data volumes grow, pipelines become harder to monitor, test, and scale.
  • Security, Compliance & Governance.
    Automating data workflows while ensuring compliance with GDPR, HIPAA, and other relevant regulations is a complex task.
  • Tool Integration and Ecosystem Complexity.
    Integrating ETL tools, CI/CD platforms, cloud environments, and test frameworks presents a significant technical challenge. 
  • Monitoring and Observability.
    Many organizations lack visibility into the performance and health of their data pipelines. Without robust monitoring, root-cause analysis becomes a reactive rather than proactive process.

The Solution: QuerySurge DevOps for Data

QuerySurge is the leading AI-powered data quality platform that continuously automates the validation of data across your entire ecosystem.

With QuerySurge DevOps for Data, your teams can seamlessly integrate continuous data testing into your DataOps workflow.

Through robust APIs, QuerySurge enables the dynamic creation and updating of tests and data stores, eliminating the need for manual UI steps. This level of automation brings agility and consistency to your data testing processes.

Key Features​

Seamless Integration​

QuerySurge DevOps for Data works smoothly with your existing tools, including:

  • Data integration and ETL platforms
  • CI/CD and automated build/delivery tools
  • Test management systems

Start Streamlining Your Data Testing Today​

Unlock the full power of DevOps for data.

Learn more about QuerySurge’s DevOps for Data »

FAQ: Issues Moving Validation Into DataOps CI/CD Pipelines

Why should data testing be part of CI/CD?

Data changes can break pipelines, reports, and downstream decisions just like code changes can break applications. Automated data testing helps teams integrate data validation into CI/CD, catching issues earlier in the release process.

What does it mean to move testing into a CI/CD pipeline?

It means running validation as part of the build, integration, and deployment workflows, rather than waiting until after release.

Why is manual data testing not enough for CI/CD?

Manual testing is too slow and inconsistent for modern release cycles. Automated validation can keep pace with frequent changes and continuous delivery.

How does QuerySurge support CI/CD for data pipelines?

QuerySurge enables automated validation that can be triggered within pipeline workflows. This helps teams test data movement, transformations, and outputs as changes are introduced.

How do teams catch data defects before deployment?

They shift testing earlier and run it continuously during development and release workflows.

Can QuerySurge validate ETL and ELT changes in CI/CD?

Yes. QuerySurge helps validate ETL and ELT changes by testing source-to-target data, transformation logic, and expected outcomes throughout the delivery lifecycle.

How does CI/CD data testing reduce release risk?

It reduces the risk that bad data, broken mappings, or transformation defects enter production unnoticed. It helps teams add a stronger control point before release.

How do teams automate data validation in DevOps and DataOps workflows?

They integrate validation into orchestration and deployment processes, so tests run automatically whenever changes occur.

What types of tests should run in a CI/CD pipeline for data?

Teams typically need to validate completeness, accuracy, consistency, mappings, and transformation results.

How does QuerySurge fit into DevOps for Data?

QuerySurge extends DevOps practices into the data layer by automating testing and validation across data pipelines. It helps organizations move faster without sacrificing data integrity.

Can QuerySurge support API-driven automation in CI/CD?

Yes. QuerySurge supports API-based automation through its extensive APIs and Swagger documentation, which helps teams trigger validation and integrate testing into modern CI/CD workflows more efficiently.

How does CI/CD testing improve trust in analytics and reporting?

Trust improves when teams know data changes were validated before release.

What role does automation play in CI/CD data testing?

Automation is what makes continuous testing possible. It reduces manual effort by running repeatable validation across recurring releases and data pipeline changes.

How does QuerySurge help move testing into the CI/CD pipeline?

QuerySurge helps organizations embed automated data validation into delivery workflows, so testing happens earlier, more often, and with greater consistency. That helps teams reduce risk while speeding up release cycles.

What ROI can organizations expect from CI/CD-based data testing?

Organizations can reduce manual testing time, catch issues earlier, lower release risk, and improve confidence in data changes.