Data Quality

Who is the course for?

This course requires “Essentials” levels of understanding CloverDX. It's aimed at data engineers and CloverDX developers to improve how they design data pipelines, towards a more resilient and reliable operation.

What you’ll learn

You’ll be able to design transformations with a Bad-Data-first methodology – a shift from transformations that naively expect the correct data to more advanced transformations that can cope with unexpected inputs, produce meaningful actionable error reports and that won’t fail unexpectedly.
By the end of this course, you’ll be able to make data quality a natural part of your designs, without adding too much effort.

• You’ll be able to effectively use the “Validator” component to set data quality criteria and produce actionable error reports
• You’ll learn how to configure the most common components to validate data and properly report errors
• You’ll learn best practices for adding data quality measures into graphs and jobflows, including proper error handling and recovery

How it works

• This course is organized as a combination of exercises and remote live sessions (MS Teams or videoconferencing tool of your choice if applicable).
• Duration: 3 days, expected workload 2 hours a day including a 60 to 90-minute remote live session with an expert trainer per day