Virtusa’s Data Quality Checks (DQC) Framework provides streamlined data standardization and reduces the footprint of commercial tools.

Our solution is universally applicable to all data warehouses and databases and is a valuable resource for the detection and remediation of data quality issues. DQC Framework is also easy to learn and operate and begins yielding results in a short span of time.

With DQC, businesses can:

Implement data quality checks for any database with ease
Test automation and scheduling – run data checks periodically to detect any signs of regression
Conduct unit and end-to-end testing
Monitor data results and fix failures
Reduce technical debt in data pipelines

Key features

Data Quality Checks Framework modernizes the data quality checking process so companies can cost-effectively standardize data.

Automated data profiling and streamlined testing
Automated documentation and testing management capabilities
Scheduling and test orchestration in conjunction with Apache Airflow
Data results library
Displays data quality results and failures in text files or HTML page format for viewing and analysis
Expansive integration capabilities
Ability to integrate with a wide array of big data platforms and environments, including Spark, Databricks, AWS EMR (Amazon EMR), AWS Redshift, Google BigQuery, Snowflake, Slack, Airflow, Postgres, Notebooks, and more.
Pluggable and extensible

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