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Data Quality & Observability

Data Quality & Observability

If the data is the lifeblood of analytics and AI, then it's imperative that organizations manage the quality of their data, in particular the accuracy, completeness, and consistency of data and that it is fit for purpose and meets user expectations. 

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Report

Deep Dive on Data Quality Automation: Three Tools to Consider

May 13, 2022 Traditional techniques for ensuring data quality break at scale. Machine learning algorithms can automate aspects of the data quality workload, ensuring that the data the business users consume is reliable, no matter the quantity of data. This report profiles three tools that each take a different approach to reducing the burden of ensuring data quality and gives leaders context to better understand the strategies for data quality automation.

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Deep Dive on Data Quality Automation: Three Tools to Consider
Observability

Podcast

Kevin Petrie on the Rise of Observability

January 28, 2022 In the physical world, you can see a bridge rusting or a building facade crumbling and know you have to intervene to prevent the infrastructure from...

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