Making Data Validation Suck Less
“Data validation is fun!” – No one ever
Data validation. Two incredibly important words, yet one of the most painful parts of any analytics instrumentation. Whether you’re getting started with product analytics for the first time, or releasing a new feature and making updates to your current implementation, ensuring that the data you collect is accurate can be a nightmare for large organizations and small startups alike.
Today, we’re excited to release Schema, the newest addition to Taxonomy, our product add-on to help you expedite data validation and take full control over the data that is collected by Amplitude.
Instrumentation planning for automated data validation
How often have you instrumented new event data for Amplitude only to hear from someone on your team that it’s incorrect, missing values, or entirely unexpected? With major feature releases, or big taxonomy updates, doing proper validation can take a tremendous amount of time and effort. Mistakes often slip through the cracks and wind up confusing an unsuspecting member of your team with funky-looking data.
We built Schema to solve this problem.
Schema helps you better automate your data validation process by letting you build instrumentation plans within the tool. You can also upload a plan you have created outside of Amplitude. As data is collected, Schema will automatically expose the event data that is outside of your plan and notify the appropriate members of your team.
Schema automatically detects any event, event property, or event property value that you did not intend to ingest. It proactively surfaces those unwanted, unexpected events and properties so you know exactly what your team needs to address when QAing instrumentation updates.
Ingestion whitelisting for total data governance
Schema adds an additional layer of confidence, integrity and trust to the data you see in Amplitude. Having confidence in your data means you aren’t accidentally tracking sensitive information about your customers.
Schema allows you to specify exactly which events, properties, and values you want to ingest into Amplitude so you can avoid accidentally ingesting sensitive data such as personally identifiable information (PII).
Data integrity is at the core of any product analytics solution, yet making sure that what you actually collect is what you intended to collect has been a challenge that eludes some of the most diligent teams. With Schema we hope to make data validation suck a whole lot less and get you to actionable insights faster than ever.
Last Updated: 05/03/18
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