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Data Observability vs. Data Monitoring; What’s the Difference?

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Solutions Review – By Petr Travkin

Data Observability vs. Data Monitoring; What’s the Difference?

Data is the currency of the modern world. And Consistent collection and interpreting of quality, trustworthy, and up-to-date customer information can mean the difference between winning and losing in business today. But, with around 2.5 quintillion bytes of data collected by organizations every day, sifting through this unimaginable ocean can be challenging – not to mention overwhelming. Moreover, poor data quality, or data that is partial or incorrect, can result in wasted time and resources.

For companies that recently migrated to the cloud, have complex data stacks, or constantly experience data quality issues, it is time they implemented a data observability strategy.

What is Data Observability? Data observability is a DataOps process that helps data teams ensure high data quality, giving them the transparency to identify issues and the control to resolve them at the point of occurrence rather than further downstream when damage is irreversible. Observability tools and procedures enable data experts to detect, resolve and prevent data anomalies. From a broader IT context, observability is a company’s ability to understand and manage the performance of all of its systems, servers and applications.

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