Do you have a dastardly dark database teaming with terrible data quality?  Are the data sets around you a mystery box full of potential errors?  Is your data an enigma, wrapped in a pitch-black box, riddled with data irregularities?

Are you a member of a stressed-out, overworked data team that directly provides insight to customers while building/running data systems that produce embarrassing data errors regularly?  Are you aware that a survey of 700 data engineers by DataKitchen & data.world in 2022 found that 52% of Data Engineers said errors are a significant source of burnout?

Do you have embarrassing production data errors your customer found (or not found)?  Data errors cause your customers not to trust the data, are hard to find, take time to identify, and waste your time on re-work. Data errors can cause compliance risk and have an opportunity cost for the business because of the downtime during errors.

Do you need more time or business to understand the data enough to create data tests?   Data engineers deal with hundreds of data sets and diverse customer needs.  They have backlogs on their daily task lists.   So they don’t have time or energy to learn about each data set or customer to create robust production data tests.   They need help creating tests that fit their data and customers’ needs.

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.

Webinar – June 28, 2023: 12 pm EST (4 PM GMT)

SIGN UP NOW:  https://info.datakitchen.io/automated-test-generation

 

Monitor every Data Journey in an enterprise, from source to customer value, in development and production.

Simple, Fast Data Quality Test Generation and Execution. Your Data Journey starts with verifying that you can trust your data.

Orchestrate and automate your data toolchain to deliver insight with few errors and a high rate of change.

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