FirstEigen, the Autonomous Data Validation Company, announced the general availability of DataBuck for Snowflake and Azure Data Lake.
“Current data monitoring and validation tools and processes fare very poorly under conditions like Cloud/Lake use, high volume of data, and new sources or changing structures of data, among others. That’s where DataBuck comes into the picture,” says Angsuman Dutta, CTO and co-founder of FirstEigen.
Dutta says DataBuck will enable data owners to flag inaccurate records as soon as data lands in snowflake tables. It scans each data asset in the targeted Snowflake and Azure Data Lake platform. Assets are rescanned every time the data asset is refreshed or whenever a scheduler invokes DataBuck. FirstEigen assures no data is moved to DataBuck.
With DataBuck, data owners do not need to write data validation rules or engage the data engineers to perform any tasks. DataBuck uses machine learning algorithms to generate an 11-vector data fingerprint to identify records with issues.
Another impressive feature is that the Data Fingerprint approach reduces false positives. For a Fortune 500 industrial company, DataBuck reduced false alerts related to data quality issues in the Internet of Things (IoT) sensor data by 85%. This helped the company save over $1.2 million.
DataBuck also autonomously creates data health metrics specific for each data asset. The well-accepted and standardized metrics are customized for every data set, individually leveraging AI/ML algorithms, and published in the Alation data catalog using Alation’s Open Data Catalog Framework.
Health metrics are computed based on quality dimensions for each column in the data asset and monitored over time to detect unacceptable data risks. Health metrics are translated to a data trust score.
In addition, DataBuck continuously monitors the health metrics and trust score and alerts users when the trust score becomes unacceptable. It features a one-click integration with Snowflake, Azure Data Lake, and Alation. FirstEigen stressed that no data moves out of Snowflake or Azure Data Lake, and it is focused on errors that matter.
FirstEigen is the creator of award-winning software DataBuck which detects data quality errors without coding by leveraging AI/ML. Machine Learning powers data quality testing and data matching to automatically set thousands of automated data validation checks and their thresholds.
Those who want to learn more about FirstEigen, as well as the benefits of Databuck, may visit the website and its social channels for more information.
Media Contact
Company Name: FirstEigen
Contact Person: Angsuman Dutta
Email: Send Email
Phone: 6304141231
Country: United States
Website: https://firsteigen.com/