The DevOps for Data Challenge:

Moving Testing into your CI/CD Pipeline

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Challenges
Moving Testing into your CI/CD Pipeline

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Inconsistent, incomplete, or outdated data undermines trust and analytics accuracy.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 intelligent data testing solution purpose-built to automate the validation of Big Data, Data Warehouses, and BI reports.

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