Improving data quality in your organization means having a plan to deal with different types of data issues. Many tools on the market only focus on “late” data by providing observability into pipelines. Anomalo does this well but also provides insight into deeper problems that occur inside your data. 

• Late data – did my pipeline fail? 
• Wrong data – did a code change inadvertently cause duplicates in my data? 

• Weird data – did a new value appear in my data, which is correct, but changes the way I need to analyze it and use it to make decisions? 

In this session, you will see a walkthrough of Anomalo and how it can be used to cover all three of these cases.

Website: https://www.anomalo.com/