Data Governance- Challenges and Dynamics.- Strategy and Data Governance.- Data Governance Maturity Models.- Data Governance Organization.- Data Governance Metrics.
Rupa Mahanti, Ph.D. is a Business and Information Management consultant and has worked in different solution environments and industry sectors in the United States, United Kingdom, India, and Australia. She holds a Bachelor’s degree in Computer Science, Master degree in Information Technology and a Doctorate in Engineering. She has expertise in different information management disciplines, business process improvement, regulatory reporting, and more. She is the author of four other books entitled Data Quality, Data Governance and Compliance, and Data Governance and Management, and Thoughts respectively, as well as a large number of research articles. She is Editorial review board and Associate Editor of Software Quality Professional Journal, USA and a reviewer for several international journals.
While good data is an enterprise asset, bad data is an enterprise liability. Data governance enables you to effectively and proactively manage data assets throughout the enterprise by providing guidance in the form of policies, standards, processes and rules and defining roles and responsibilities outlining who will do what, with respect to data. While implementing data governance is not rocket science, it is not a simple exercise. There is a lot confusion around what data governance is, and a lot of challenges in the implementation of data governance. Data governance is not a project or a one-off exercise but a journey that involves a significant amount of effort, time and investment and cultural change and a number of factors to take into consideration to achieve and sustain data governance success. Data Governance Success: Growing and Sustaining Data Governance is the third and final book in the Data Governance series and discusses the following:
• Data governance perceptions and challenges
• Key considerations when implementing data governance to achieve and sustain success
• Strategy and data governance
• Different data governance maturity frameworks
• Data governance – people and process elements
• Data governance metrics
This book shares the combined knowledge related to data and data governance that the author has gained over the years of working in different industrial and research programs and projects associated with data, processes, and technologies and unique perspectives of Thought Leaders and Data Experts through Interviews conducted. This book will be highly beneficial for IT students, academicians, information management and business professionals and researchers to enhance their knowledge to support and succeed in data governance implementations. This book is technology agnostic and contains a balance of concepts and examples and illustrations making it easy for the readers to understand and relate to their own specific data projects.