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by mona_rakibe
1797 days ago
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Telmai (https://www.telm.ai/) is a real-time data quality monitoring platform that can automatically detect and investigate data quality issues as data is getting ingested. Our tool uses a statistical and ML engine that helps data product owners understand data anomalies and intuitively define correct versus incorrect data. These definitions are then used to proactively monitor and alert on data quality problems. We have decades of experience with enterprise data and find that this approach towards data quality addresses a huge gap in data platforms. Detecting and investigating data quality issues is extremely tedious, time-consuming and expensive. Using Telmai, companies like Dun & Bradstreet and Myers-Holum are able to find and resolve such issues across millions of records in minutes. Ask us anything! |
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Looks interesting! I worked on https://github.com/capitalone/DataProfiler
We are looking to monitor correlation changes over time, see if sensitive data gets entered, track schema changes, etc and see the impact of down stream modeling, etc
I'm curious how heavy the input is? because usually these systems take a lot of effort to setup. Any idea?