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How can data teams scale up by going beyond "data quality"?

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About the webinar

Andy Petrella

Andy Petrella

Founder and CPO @Kensu

Over time data teams have been stacking up data sources, pipelines, and products to answer a growing flow of user requests. Data quality solutions, usually scanning data at rest, have been adopted to maintain quality and avoid friction with the stakeholders.

While data teams can quickly deploy such platforms, they now present some limits that stop them from scaling up their activities: no information about the context, no synchronization with data usage, no continuous validation, etc. To solve this, a new category of solution that goes beyond data quality monitoring has emerged: 360 Data Observability.

Watch this replay and discover how data teams can go a step further in managing their data quality by being able to observe their data in real-time in their environment and what are the benefits of this new approach.

What you will learn

This session explored how data quality practices are augmented with 360 Data Observability. Our expert also discussed how the data teams can benefit from adopting an approach that is not limited to scanning data at rest but complemented with observations captured during the data usage, including its context, and integrated in the data application lifecycle.