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  • Validate Your Cloud Data with Confidence

Overview

Explore the best practices, validation techniques, and automation strategies for ensuring complete and accurate data across cloud-native pipelines using ETL and ELT models.

As data becomes central to enterprise strategy, inaccurate or inconsistent information can derail key decisions. Traditional testing can’t keep up with cloud-native data warehouses’ speed, scale, and complexity. Redshift, BigQuery, and Azure Synapse demand a more modern, automated approach to ensure data trust.

 

This whitepaper offers a comprehensive guide to help you

 
Understand how ETL and ELT differ in cloud-native environments.

Understand how ETL and ELT differ in cloud-native environments.

Validate BI reports, dashboards, and data pipelines with complete accuracy.

Validate BI reports, dashboards, and data pipelines with complete accuracy.

Automate testing to support continuous data refresh and transformation cycles.

Automate testing to support continuous data refresh and transformation cycles.

Apply best practices for version control, test coverage, and governance.

Apply best practices for version control, test coverage, and governance.

Ensure clean, complete, and governed data that drives confident business decisions

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