About This Chapter
Data Quality Management: Chapter Summary
Data quality management can be a large concern for businesses. Managing data on a single site is difficult enough, but when you have to maintain data quality across multiple sites or even internationally, more questions and obstacles can arise. This chapter help you better understand the processes involved in data quality management and gain the skills needed to monitor your organizations data more effectively.
Our instructors have divided this topic into several lessons, with each lesson focusing on a single aspect of data quality management. If you need a full overview of this topic, you can go through every lesson in the chapter, but if you only need to review a few key concepts, you can use the chapter menu to go directly to those lessons.
Topics addressed in this chapter will give you the skills to:
- Describe the importance of data quality
- Identify the process of data quality management
- Analyze the best practices and framework for data quality management
- Maintain data quality in the healthcare industry
- Examine concerns related to data warehouses
1. What is Data Quality? - Definition & Importance
Data Quality is an important area in today's world. It tells us how well we've accomplished something and whether we've done it the right way. In this lesson, we'll take a look at its various aspects, and uses.
2. What is Data Quality Management? - Definition & Process
Discover how Data Quality Management makes our data accurate. Huge databases exist today and duplication of records occurs. Ever stop working for a company and still receive mail as if you are employee? Ever have a bill in which you complained and got credit but on the next bill, the credit is not appearing? Well, Data Quality Management Information ensures that these problems do not occur.
3. Data Quality Management: Framework & Best Practices
In this lesson, you will get the inside scoop on data quality management. You will also learn why data quality management is important to you and your particular field.
4. Data Quality in Healthcare
Data quality in healthcare consists of several characteristics, including accuracy, consistency, and relevancy. In this lesson, we'll see how health information technology encourages data quality by reducing redundancy, decreasing medical errors, and enhancing health outcomes.
5. Data Quality Issues in Data Warehouses
In this lesson, we will be looking at what data, data quality and data warehousing is all about. We will also learn about how data quality issues affects in Data Warehouses.
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