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Anomalo to Speak About How Unsupervised Machine Learning Can Scale Data Quality Monitoring in Databricks at DATA+AI Summit 2022

PALO ALTO, Calif., June 27, 2022 — Anomalo, the complete data quality platform company, today announced that it has a session titled “How Unsupervised Machine Learning Can Scale Data Quality Monitoring in Databricks” at the DATA+AI Summit 2022, Databricks’ event that kicks off today in San Francisco:

Technologies like Databricks Delta Lake and Databricks SQL enable enterprises to store and query their data. But existing, manually-configured rule and metric approaches to monitoring the quality of this data are tedious to set up and maintain, fail to catch unexpected issues, and generate false positive alerts that lead to alert fatigue.

On Thursday at 11:30 a.m., Jeremy Stanley, co-founder and CTO of Anomalo, will describe a set of unsupervised machine learning algorithms for monitoring data quality at scale in Databricks. He will cover how the algorithms work, their strengths and weaknesses relative to a rules based approach and how they are tested and calibrated. Attendees will gain an understanding of unsupervised data quality monitoring and how to begin monitoring data using Anomalo through Databricks. Anomalo is also providing a free trial exclusively to Databricks customers so that they can start monitoring their tables immediately to detect and root-cause data quality issues.

Anomalo will showcase its data quality platform in booth #305 at the DATA+AI Summit 2022.

In May of this year, Anomalo announced that it is integrated with Databricks and makes it even easier for shared customers to use Databricks and Anomalo together:

Earlier this month, Anomalo announced that it is available on Databricks Partner Connect so enterprises can instantly begin monitoring the quality of their data:

“Whether you’re using your Databricks Lakehouse for analytics or machine learning and AI, your results are only as good as the quality of the underlying data. So, we’re excited to partner with Databricks to give their customers a great tool for automatically detecting and understanding the root-causes of data issues – thus preventing such issues from leading to incorrect BI dashboards or broken machine learning models,” said Elliot Shmukler, co-founder and CEO of Anomalo.

About Anomalo

Anomalo helps enterprises build confidence in the data they use to make decisions and build products. Enterprises can simply connect Anomalo’s complete data quality platform to their data warehouse and begin monitoring their data in less than 5 minutes, all with minimal configuration and without a single line of code. Then, they can automatically detect and understand the root-cause of data issues, before anyone else. Anomalo is backed by Norwest Venture Partners, Foundation Capital, Two Sigma Ventures, Village Global and First Round Capital. For more information, visit or follow @anomalo_hq.


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