Watch Telmai in action!
Dive into Telmai’s blog post ‘Watch Telmai in Action’ for a short demo on how Telmai works. Learn how it connects to any step in the data pipeline, automatically learns about your dataset, and alerts users about unexpected changes in data.
This is a short demo on how Telmai works
- Connect to any steps in the data pipeline like source system, raw data source (S3, Blob, GCS), DW (BigQuery, Snowflake, Redshift ), or streaming source like Kafka/pub-sub. Telmai works best for your spark based pipelines 🙂
- Telmai will automatically learn all about your data-set like its schema, volume, value distributions, completeness/uniqueness of values, expected ranges, expected values, etc., and present it to users. Users can then identify outliers and provide input to our system using our Human in the loop approach.
- Telmai will automatically start monitoring the incoming data for any drifts in the data metrics over time-time. Users will automatically get alerted if there is an unexpected change in data.
Data owners can then proactively review these drifts before a downstream impact.
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