Feature launch: Transformations for real-time schema fixes | RudderStack

By neub9
3 Min Read

Poor quality data can lead to significant issues across your organization. It can cause problems such as broken dashboards before important meetings, compromised customer experiences due to incorrect data, and even strategic missteps based on inaccurate analysis. If you can’t trust your data, you can’t operate as a data-driven company.

To address this issue, our Tracking Plans feature allows you to identify violations and remove poor quality data before it propagates downstream. However, simply removing bad data isn’t enough. Without effective remediation, your dataset remains incomplete, limiting your ability to deliver exceptional customer experiences.

Therefore, we’re excited to announce the introduction of real-time schema fixes with our Transformations feature. This allows you to correct poor quality data while maintaining an efficient workflow, ensuring greater data quality for your business’ success.

Fixing bad data has its challenges. Traditional methods involve complex and time-consuming processes, from redeploying websites and apps to dealing with numerous edge cases. With RudderStack’s Transformations, you can solve these issues in real time when they occur, preventing the need for lengthy development cycles or the integration of additional systems.

Our Transformations feature also allows you to manipulate and enrich your event payloads in real time, ensuring that your data remains accurate and consistent. By using JavaScript or Python, you can customize your fixes for each destination, providing a global, real-time solution for poor quality data.

Using Transformations, you can quickly address errors, from changing property and trait names to converting data types, reforming payload structures, and even sending diagnostics to downstream systems when needed. These abilities ensure that your data remains high-quality and valuable to your business.

If you’re ready to take control of your data quality, explore our Transformations feature and the rest of our Data Quality toolkit by checking out our documentation. Additionally, you can request a demo with our team or sign up for our webinar featuring data quality expert Chad Sanderson, so that you can explore new avenues for ensuring data quality from the source.

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