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Software Engineering Daily · Feb 17, 2022 · 50 min

Data Quality Using Anomalo with Jeremy Stanley

When writing code, test driven development is a common accepted methodology to ensure the development of high quality software. Your organization’s data, on the other hand, is an entirely different challenge. Data can be missing due to human error, a failure with a 3rd party provider, a botched release, or dozens of other issues. When not missing, data can still become corrupted or start exhibiting a trend in the wrong direction that isn’t obvious to notice. Anomalo is a complete data quality platform. It can monitor your enterprise data and alert you to problems that are automatically detected. In this episode, I interview Jeremy Stanley about the ways in which teams are using the platform to monitor and improve their data quality. Sponsorship inquiries : sponsor@softwareengineeringdaily.com MAGIC MIND: Go to magicmind.co MPARTICLE: Visit mparticle.com DOPPLER: Sign up via doppler.com/sedaily. STRONG DM: Sign up at strongdm.com/sedaily.

0:00-50:14

transcript

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show notes

When writing code, test driven development is a common accepted methodology to ensure the development of high quality software. Your organization’s data, on the other hand, is an entirely different challenge. Data can be missing due to human error, a failure with a 3rd party provider, a botched release, or dozens of other issues. When not missing, data can still become corrupted or start exhibiting a trend in the wrong direction that isn’t obvious to notice.

Anomalo is a complete data quality platform. It can monitor your enterprise data and alert you to problems that are automatically detected. In this episode, I interview Jeremy Stanley about the ways in which teams are using the platform to monitor and improve their data quality.

Sponsorship inquiries : sponsor@softwareengineeringdaily.com


MAGIC MIND: Go to magicmind.co

MPARTICLE: Visit mparticle.com

DOPPLER:  Sign up via doppler.com/sedaily.

STRONG DM: Sign up at  strongdm.com/sedaily.

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