Data Quality Fundamentals for Beginners

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!