Verifying data in Azure Synapse involves the critical process of ensuring the accuracy, consistency, and reliability of the data stored within the Synapse environment. Leveraging its robust capabilities, users can employ various techniques to validate data integrity and quality.

Azure Synapse facilitates the implementation of data verification through features like data profiling, schema validation, and data quality rules. Data profiling allows users to analyze the structure, completeness, and uniqueness of datasets, providing insights into potential anomalies or inconsistencies. Schema validation ensures that data conforms to predefined schemas, safeguarding against errors or discrepancies.

Additionally, data quality rules enable users to establish criteria for assessing data accuracy and completeness, enabling proactive monitoring and remediation of any issues. By meticulously verifying data in Azure Synapse, organizations can uphold data integrity, enhance decision-making processes, and foster trust in their analytical insights.

Integration with Azure Synapse allows you to verify data through Secoda. An Automation consists of Triggers and Actions. Triggers activate the workflow based on defined schedules, such as hourly, daily, or custom intervals. Actions encompass various operations, including filtering and updating metadata. These actions can be stacked to create customized workflows that meet your team's requirements. Secoda enables bulk updates to metadata in Azure Synapse.

Secoda's integration with Azure Synapse allows for seamless verification of data. By serving as an index of your company's data knowledge, Secoda consolidates data catalog, lineage, documentation, and monitoring into a single data management platform. With its AI-powered data governance capabilities, Secoda ensures efficient and reliable data verification within the Azure Synapse environment.