ML

Outlier Detection – What Is It And How Can It Help In The Improvements Of Data Quality? 

Outlier Detection

Identifying outliers and errors in data is an important but time-consuming task. Depending on the context and domain, errors can be impactful in a variety of ways, some very severe. One of the issues with detecting outliers and errors is that they come in many different forms. There are syntactic errors, where a value like […]

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Rules Suggestion – What is it and how can it help in the pursuit of improving data quality?  

rules suggestion

Written by Daniel Browne, Machine Learning Engineer Defining data quality rules and collection of rules for data quality projects is often a manual time-consuming process. It often involves a subject matter expert reviewing data sources and designing quality rules to ensure the data complies with integrity, accuracy and / or regulatory standards. As data sources

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With Snowflake connectivity, SQL rule wizard and the ability to bulk assign data quality breaks, ADQ 1.4 makes end-to-end data quality management even easier.