Do you have data quality issues, a complex technical environment, and a lack of visibility into production systems?

These challenges lead to poor quality analytics and frustrated end users. Getting your data reliable is a start, but many other problems arise even if your data could be better. And your customers don’t care where the problem is in your toolchain. They want to know when to get their trusted dashboard refreshed (for example).

The uncertainty of not knowing where data issues will crop up next and the tiresome game of ‘who’s to blame’ when pinpointing the failure. It’s more than just a ‘last mile’ problem in data observability. It’s about personalization for your customers. Demanding Data Consumers require a personalized level of Observability.

This webinar discusses how to make embarrassing data errors a thing of the past.
We will start with how data engineers do not understand their data and have difficulty identifying problematic data records. We will also discuss how the vast majority of data engineers are so busy that they don’t know, or have time to write, tests to write to find data errors. We will finish with a demonstration of DataKitchen’s New DataOps Testgen Product.
That missing piece that connects data system expectations and reality is a ‘Data Journey.’ It is the missing piece of our data systems.

This webinar discusses how to make embarrassing data errors a thing of the past.
We will start with how data engineers do not understand their data and have difficulty identifying problematic data records. We will also discuss how the vast majority of data engineers are so busy that they don’t know, or have time to write, tests to write to find data errors. We will finish with a demonstration of DataKitchen’s New DataOps Testgen Product.
That missing piece that connects data system expectations and reality is a ‘Data Journey.’ It is the missing piece of our data systems.