Название: Data Quality: Empowering Businesses with Analytics and AI
Автор: Prashanth Southekal
Издательство: Wiley
Год: 2023
Страниц: 302
Язык: английский
Формат: pdf (true), epub
Размер: 10.2 MB

Discover how to achieve business goals by relying on high-quality, robust data.

In Data Quality: Empowering Businesses with Analytics and AI, veteran data and analytics professional delivers a practical and hands-on discussion on how to accelerate business results using high-quality data. In the book, you’ll learn techniques to define and assess data quality, discover how to 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 Artificial Intelligence (AI) applications.

To provide organizations a competitive advantage from data, this book, Data Quality: Empowering Businesses with Analytics and AI provides readers with practical guidance and proven solutions to derive quality business data. While there are many books on data quality in the market, the book has three key elements that will make it unique in the marketplace:

• The book is for practitioners written by a fellow practitioner. It is based on my data, analytics, and AI experience, while consulting for over 80 companies including big brands such as GE, SAP, P&G, Apple, and Shell. In addition, this content has been reviewed by senior data and technology leaders from many leading organizations worldwide.

• The book is relevant in today's context. Today, companies operate under stiff competition, expanded business networks, increasing regulatory compliance, and emerging technologies such as cloud computing, Big Data, Machine Learning (ML), Artificial Intelligence (AI), blockchain, IoT (Internet of Things), and more. This book caters to managing quality business data in the current AI and analytics landscape. Every effort has been made to ensure that the contents are well researched, the chapters are logically and coherently organized, the topics are relevant for today's context, and the book is written in a simple, clear, and precise manner.

• The book is technology agnostic. Many data quality books available in the market are IT product–centric. This book looks at the technical concepts without any reference to proprietary vendor technologies. The primary objective of this book is to enable improved business performance from data. Any business leader who is keen to derive quality data can use this book, regardless of which IT and data products they utilize.

The author shows you how to:

Profile for data quality, including the appropriate techniques, criteria, and KPIs
Identify the root causes of data quality issues in the business apart from discussing 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

An essential resource for data scientists, data analysts, business intelligence professionals, chief technology and data officers, and anyone else with a stake in collecting and using high-quality data, Data Quality: Empowering Businesses with Analytics and AI will also earn a place on the bookshelves of business leaders interested in learning more about what sets robust data apart from the rest.