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Introduction to Data Quality

Beginner
Updated 12/2024
Explore the basics of data quality management. Learn the key concepts, dimensions, and techniques for monitoring and improving data quality.
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Course Description

Explore the Basics of Data Quality

Data quality is a fundamental concept critical to understand if you work with data. Data quality concepts and processes span industries and can be applied by any person who produces or consumes data. This course covers the basics, including data quality dimensions, roles and responsibilities, and types of data quality rules. You’ll gain an understanding of the data quality process and be prepared to start monitoring your own data’s quality.

Learn About Data Quality Dimensions

You’ll start by learning the definition of data quality and why it is so important to consider in business decision-making. Once you understand the importance, you will learn about six foundational data quality dimensions. You will use these dimensions to define detective and preventative data quality rules.

You will also learn the basics of anomaly detection, a more advanced way to monitor data quality. You will put these concepts together by applying the data quality process. You will learn which role is responsible for specific data quality tasks and the order in which these tasks should be completed.

Master the Basics of Data Quality Management

By the end of this course, you will understand how to monitor, identify, and resolve data quality issues. You will look at your data through a more critical lens and think about potential data quality issues before using it. Ultimately, you will be able to make better decisions and have more trust in your data by applying the basic data quality techniques covered in this course.

Prerequisites

There are no prerequisites for this course
1

Defining Data Quality Terms

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2

Data Quality Processes and Components

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3

Data Quality Rules In Action

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Introduction to Data Quality
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