Data Quality Fundamentals for Beginners
Data quality is a key business challenge of the 21st century.
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What You Will Learn!
- What is Data Quality?
- Why data quality is important?
- What are the important roles within Data Quality Management
- What are the different Data Quality Management techniques
Description
Hello there,
Data quality is a key business challenge of the 21st century. Quality has been an issue since the dawn of the IT profession and becomes increasingly challenging as the volumes of data increase and the uses for data expand. Regardless of your roles and responsibilities in IT - manager, developer, or technologist - you will at some time be challenged by data quality issues. And quality is an equal opportunity issue, imposing itself in every aspect from transaction systems to Web content and business intelligence
Why is data quality important?
Data quality matters because it significantly impacts your business performance. High-quality data helps you make better decisions and perform better actions, leading to increased revenue, decreased costs, and reduced risk. Low-quality data has the opposite effect, resulting in poor profitability and an increased risk that your business will fold prematurely.
At the end of the course, you'll be able to grasp an all-round understanding of below concepts:
Data Quality
Data Strategy
Data Governance
Data Architecture
Data Lifecycle Management
Analytics and Data Science
Data Quality Objectives
6 Data Quality Dimensions and Examples
Roles and Responsibilities of Data Owners and Data Stewards
Data Quality Management Principles
Data Quality Management Process Cycle
Data Quality Issue Management
Data Cleansing
Outcome:
Understand the various Data Quality areas
Explore Data Quality policies and procedures
Discuss data profiling, validation rules, facets, data cleansing, and more...
Understand how Data Quality is linked to other data disciplines
Thank you!
Who Should Attend!
- Professionals that want to undertand what is Data Quality and how it can help their organization
- Data Scientists
- Management that wants to gain knowledge in the importance of Data Quality Management
- Big Data Developers/Administrator
