Long title: The Goal-Question-Metric (GQM) Model to Transform Business Data into an Enterprise Asset.
Today, digitization is dramatically changing the business landscape, and many progressive organizations have started to treat data as a valuable business asset. While many enterprises are investing in improved data management, only a few have leveraged data to truly impact business performance. To address this problem, Data for Business Performance provides readers with practical guidance and proven techniques to derive value from data in today’s business environment. Specifically, this book:
- is holistic, as it looks at deriving value for all three key purposes of data: decision making, compliance, and customer service.
- is for practitioners, with practical guidance and proven techniques supported by real world examples.
- is relevant for the current business and IT landscape.
- is novel, with the adoption of the Goal-Question-Metric (GQM) framework as the core mechanism to monetize data in the organization, based on business goals, key questions, and key performance indicators (KPIs).
- is technology-agnostic, as concepts are used for unlocking the value of data without any reference to proprietary technologies.
This book is absolutely timely and relevant in today’s data-driven world. Most of the books on data available in the market today focus on data quality, governance, and analytics. This book from Dr. Prashanth Southekal is brilliant as it puts the business stakeholder at the center by addressing the key value propositions of the business user. This book is holistic and I strongly believe it will help to bridge the gaps we have today.
Mario Faria — Managing Vice President, Gartner, US
This book is one of the most practical sources for how companies can greatly improve their bottom line by improved data management and becoming a data-centric company. It combines leading data management theory with step-by-step implementation and real-life examples, and is a must-read for those wanting to derive more value from their corporate data.
Lance Calleberg — Application Architect, Husky Energy, Canada
Dr. Southekal provides valuable insights on data and information management in mostly short and clearly written sections. Anyone interested in the data-driven company should read this book and learn about the hurdles on the road to be data-driven, and his valuable suggestions on how to overcome them. His wisdom may prevent some of the failures that helped him learn.
Erik van der Voorden — Domain Architect, Independent Consultant, Netherlands
The book is available, here.
Top DSC Resources
- Article: Difference between Machine Learning, Data Science, AI, Deep Learnin…
- Article: What is Data Science? 24 Fundamental Articles Answering This Question
- Article: Hitchhiker’s Guide to Data Science, Machine Learning, R, Python
- Tutorial: Data Science Cheat Sheet
- Tutorial: How to Become a Data Scientist – On Your Own
- Categories: Data Science – Machine Learning – AI – IoT – Deep Learning
- Tools: Hadoop – DataViZ – Python – R – SQL – Excel
- Techniques: Clustering – Regression – SVM – Neural Nets – Ensembles – Decision Trees
- Links: Cheat Sheets – Books – Events – Webinars – Tutorials – Training – News – Jobs
- Links: Announcements – Salary Surveys – Data Sets – Certification – RSS Feeds – About Us
- Newsletter: Sign-up – Past Editions – Members-Only Section – Content Search – For Bloggers
- DSC on: Ning – Twitter – LinkedIn – Facebook – GooglePlus
