Criteria include:
Ease-of-use and configurability
Advanced data quality management
AIOps innovation
Data pipeline support
Automatic schema change monitoring
Much more
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ABOUT DATA OBSERVABILITY
Although data observability is a new category of tools, it’s already driving an immense impact for companies looking to reduce the time, resources, and risk associated with unreliable data. Data Observability platforms monitor and alert across five key pillars of data health to mitigate data quality issues and help companies trust their data at each stage of the data life cycle. To learn more, visit www.montecarlodata.com .