Datagaps DataOps Suite 4.0.0 introduces a groundbreaking feature—GIT Integration. This empowers your Data team by enabling CI/CD for DataOps testing, seamlessly integrating with GIT providers such as Azure Repos and Bitbucket.
DataOps Suite Feature Updates – Version 2023.4.0.0
1. Enable CI/CD for your DataOps testing with GIT integration
DataOps Suite supports various GIT providers like Azure Repos and Bitbucket to store, organize, manage, and track the dataflows of different versions, making it easier to roll back to previous versions if necessary. They provide a centralized repository to manage the dataflows in one place and make it easy for multiple team members to collaborate on maintaining the dataflows.
GIT Integration empowers the Data team to manage their ETL/ELT code, BI reports/workbooks and test cases in a single GIT repository.
2. Improved Testing Capabilities for Tableau & Power BI Reports
Tableau Upgrade compares the views and worksheets in the newer version with the same views and the worksheets in the older version in the same or different Tableau environments to ensure that no data or formatting has been lost.
Power BI Regression performs a regression testing of the Power BI dashboards by comparing the baseline version of the dashboard (PDF) with the live version. This comparison can be done for ‘text’ which highlights the changes in text even if the text is shifted by a little and ‘appearance’ which performs the pixel-to-pixel comparison and highlights text, chart, etc.,
Power BI Upgrade compares the PDF report in the newer version with the same PDF report in the older version in the same or different Power BI environments to ensure that no data or formatting has been lost.
By automating the regression and migration testing, these components can save organizations time and effort, and help them to ensure that their dashboards and reports are trustworthy and working as expected.
3. “Data Observability” Enhancements
DataOps Suite introduces two innovative detection techniques—Fixed and Delta deviation—for identifying data anomalies.
Fixed deviation is a simple technique where we can set a fixed threshold, and if any data point deviates from the fixed threshold, it is flagged as an anomaly.
Delta deviation is a sophisticated technique that compares each data point to the previous one. If the change in the value of the data point is more than a certain amount, then it is flagged as an anomaly.
Both fixed and delta deviation are valuable tools that can be used to improve the quality, accuracy, and efficiency of data ingestion projects.
4. Collaboration with Microsoft Teams
By integrating DataOps Suite with Microsoft Teams, team members can receive notifications about pipeline or data quality rule execution status, errors, and other important notification events directly in Microsoft Teams based on the configured Teams template. This can help to improve communication and collaboration between team members, and ensure that everyone is on the same page.