Unlock the Power of High-Quality Data to Achieve Business Goals
Discover how to accelerate business results by relying on high-quality data. In this comprehensive guide, you’ll learn techniques to define and assess data quality, ensure that your firm’s data collection practices avoid common pitfalls and deficiencies, improve the level of data quality in the business, and guarantee that the resulting data is useful for powering high-level analytics and AI applications.
Key Benefits of High-Quality Data
• Improved Decision-Making: With high-quality data, you can make informed decisions that drive business growth and success. • Enhanced Business Intelligence: High-quality data enables you to create more accurate and reliable business intelligence reports, which in turn inform strategic business decisions. • Increased Operational Efficiency: High-quality data streamlines business operations, reduces errors, and improves overall efficiency. • Better Compliance and Risk Management: High-quality data ensures that your business is compliant with regulatory requirements and reduces the risk of data-related issues.
Mastering Data Quality: Essential Techniques and Best Practices
The author of Data Quality: Empowering Businesses with Analytics and AI provides a practical and hands-on discussion on how to accelerate business results using high-quality data. In this book, you’ll learn techniques to:
- Profile for data quality, including the appropriate techniques, criteria, and KPIs
- Identify the root causes of data quality issues in the business, including the 16 common root causes that degrade data quality in the organization
- Formulate the reference architecture for data quality, including practical design patterns for remediating data quality
- Implement the 10 best data quality practices and the required capabilities for improving operations, compliance, and decision-making capabilities in the business
Who Should Read This Book?
Data Quality: Empowering Businesses with Analytics and AI is an essential resource for:
- Data scientists, data analysts, and business intelligence professionals
- Chief technology and data officers
- Business leaders interested in learning more about what sets robust data apart from the rest
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