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Data Observability Driven Development

Data quality management needs a paradigm shift
for data teams to scale up and trust what they deliver.

Why DODD?

We believe that Data Observability should be done from within the applications instead of outside. The Data Observability Driven Development method allows data teams and data usage to scale by enabling:

  • Continuous validation
  • Contextual observability
  • Avoid duplication of work
  • Iterative implementation
  • Friendly exploration
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How does it work?

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The Data Observability Driven Development method implements best practices following this cycle:

  • From within the code, log context and runtime information
  • Define quality control rules
  • Validate rules before and continuously in production
  • Review or refactor your delivery upon triggered rules

What are the benefits?

With the Data Observability Driven Development method, data teams can now work serenely and data usage can scale efficiently as:
  • Data observability is synchronized with data usage
  • Stronger accountability from data teams
  • Faster troubleshooting and maintenance
  • Fewer bugs due to higher quality of code
  • Lower resource usage due to optimal monitoring
  • Accurate self-documentation
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Discover our platform

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Our data observability platform tracks and measures in real-time your data usage performance across systems, projects, and applications.

It enriches your data management ecosystem by sharing schemas, lineages, and quality information with data glossaries, catalogs, and incident management systems.

Our use cases

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Less documentation.
Stronger governance
& productivity.

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Protect sensitive and private data

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Create a protective shell around your data applications

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Accelerate your time to market

Trust what you deliver.