Anomalo Releases Pulse — A Unified Dashboard to Capture the Data Quality Health of the Entire Enterprise

Anomalo, the complete data quality platform company, today introduced the Pulse dashboard that provides a comprehensive view of data quality in an organization and aggregates all the data quality vitals in one place. For the first time, executives have unprecedented visibility of the health of their data quality across the entire enterprise.

Marketing Technology News: MarTech Interview with Tisson Mathew, Founder & CEO at SkyPoint Cloud

Buzzfeed VP and Head of Data Science and Analytics Gilad Lotan said: “This feature has been incredibly helpful for our team! Before the Pulse dashboard, it was a laborious and time intensive task to monitor the health of our tables and checks. This made it difficult to identify where clean-up opportunities might be. Since it launched, our teams have been able to clean things up swiftly and quickly grasp the scope of data issues that surface.”

Few organizations have the tools to measure improvements in data quality and it is never clear how good is good enough. No data is perfect. Data changes over time and is inherently chaotic. Striving for a state of data perfection is both intractable and impractical. Having data quality KPIs and setting goals against them is essential to solving the data quality problem.

“As customers deploy Anomalo, they want to understand if data quality is improving over time and if they’re doing a better job with the health of their data. Pulse answers that question,“ said Elliot Shmukler, co-founder and CEO of Anomalo.

Marketing Technology News: The Outlook on Growing Trends in Digital Marketing that will Rapidly Grow in 2022

Anomalo’s Pulse dashboard provides data owners with the metrics and KPIs to capture the state of data quality performance over time and allows them to understand:

• Data quality coverage — understand how much of the enterprise data is actually monitored for data quality issues, define the gold standard and pinpoint blind spots
• Data arrival times — identify tables whose data doesn’t arrive on time or meet SLAs
• Data quality trends — track improvements in data quality week to week by visualizing the number of issues discovered and resolved by the data team
• Problem areas — use the ranked list of problem areas to prioritize and define the next set of data quality goals

Pulse also provides a deep dive into each of these statistics making it clear exactly what next steps should be prioritized to improve data quality in an organization.

Marketing Technology News: Readymade e-commerce mobile app product named GoCommerce, launched by Confianz Global headquartered…