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Bad data costs companies a tremendous amount of money (impacting over 26% of their revenue, according to a recent survey by Wakefield Research), as well as engineering hours, with data engineers spending upwards of 40 percent of their time – or 120 hours per week – firefighting data quality issues.
In today's data-driven world, organizations face increasing data governance challenges in managing and utilizing their data assets effectively. With the sheer volume of data being generated, it is essential to maintain data health by ensuring that data is accurate, accessible, and secure - but it isn’t always easy.
Overview of the data challenges faced by organizations when scaling data quality initiatives
How to overcome common data governance challenges, like lack of adoption and documentation sprawl
How data catalogs and data observability platforms work together to deliver more trustworthy and discoverable data
The impact of maximizing data health and discovery in today’s economic climate.
Data Architect, Monte Carlo
Data Engineering Manager, Castor
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