Data Quality Tool - Quick Intro for Absolute Beginners

This course contains the use of artificial intelligence.

Disclaimer:
This course is not sponsored by, affiliated with, or endorsed by Collibra or its affiliates. All product names and trademarks are the property of their respective owners.

Modern data quality and observability tools are considered by many to be the best way to manage your data sets by learning through observation and automation rather than manual input. These platforms apply the latest advancements in data science and machine learning to the challenge of data quality, surfacing issues in minutes instead of months.

This is a course for absolute beginners who have never used a data quality and observability tool before. We will cover the main features without going into too much detail, so you can quickly become familiar with the tool’s interface and capabilities.

What will you learn in this course:

• How to set up an account with a data quality tool

• Get familiar with a typical data quality tool interface

• How connecting to data sources works

• How running data quality jobs works

• Understanding data scoring and quality metrics

• Data patterns and profiling features

• Duplicate detection

• Schema monitoring

• Record and source monitoring

• Data formatting and shape validation

• Outlier detection

• Setting up data rules and behaviors

• Scheduling data quality checks

• Using scorecards and dashboards

• Exploring data catalogs

• Generating reports and alerts

• Admin options and best practices

This course is for absolute beginners. If you have experience with data quality tools, you may find the course too basic. However, if you are new to data quality and observability tools, this will be a great starting point. I will also provide tips and resources for further learning after you master the basics.

If this is what you are looking for, enroll today and I will see you in the first lesson!

This course contains a promotion.