Data quality monitoring is a process that manages and ensures a high-standard data within an organisation. 

Performed through strategies like automation and full-stack monitoring, companies set their own data quality metrics and KPIs to measure and evaluate it.  

In this episode of the EM360 Podcast, Analyst Christina Stathopoulos speaks to Jeremy Stanley, CTO and Co-founder of Anomalo, to discuss:

• Data quality monitoring in a data reliant market
• Using unsupervised ML
• Changes in the last 5 years