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Data QualityQuestion 06 of 8

How to reduce and avoid data debt?

tpTrackingplan answers

The antidote to control or even avoid data debt lies in clean analytics tracking. Clean analytics tracking involves actively measuring the metrics that are relevant to your business, auditing data sources, and ensuring correct analytics implementations.

To get rid of your data debt and build trust in your information, the logic behind your analytics tracking needs to be checked out. That means creating a single source of data truth to be provided with a roadmap for every member involved in the data collection process to ensure the data of your digital analytics, acquisition, pixels, and campaigns are accurately collected, responsibly managed, and integrated efficiently across teams and platforms.

Trackingplan is a fully automated data QA and observability solution for your digital analytics created to ensure your data never breaks and always arrives to your specifications by automatically documenting all the data that your apps and websites are sending to third-party integrations like Google Analytics, Segment, or MixPanel.

This creates a single source of truth where all teams involved in first-party data collection can collaborate, and automatically receive notifications when things change or break to easily debug any problem by being provided with the root cause of the problems affecting your data integrity, even before they go into production.

You can try it out yourself or ask for a demo.

More in Data Quality

Category page →
  1. ?What Is Digital Analytics and How It Drives Growth
  2. ?What defines high-quality data?
  3. ?What are the business risks of poor data quality?
  4. ?What is data debt?
  5. ?What are the causes of data debt?
  6. ?Data Integrity vs. Data Quality: Are they the same?
  7. ?What’s worse: data debt or technical debt?

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