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GigaOm Radar for Data Observability

Curious about how the various data observability vendors compare? Not sure what data observability capabilities are a must-have or nice-to-have?

Look no further than GigaOm’s first-ever Data Observability Radar Report, released just last month. In this comprehensive guide, GigaOm analyst Andrew Brust walks through what a best-of-breed data observability platform looks like, highlighting critical features and functionalities, areas of investment and innovation, and which data observability vendors reign supreme.

In this report, Andrew ranks solutions including Monte Carlo, Anomalo, and Soda based on a set of key criteria every company should use to measure the performance, scalability, and impact of their data observability platforms.

Criteria include: 

  • Ease-of-use and configurability

  • Advanced data quality management

  • AIOps innovation

  • Data pipeline support

  • Automatic schema change monitoring

  • Much more

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Although data observability is a new category of tools, it’s already driving an immense impact for companies looking to reduce the time, resources, and risk associated with unreliable data. Data Observability platforms monitor and alert across five key pillars of data health to mitigate data quality issues and help companies trust their data at each stage of the data life cycle. To learn more, visit .