This was the beginning of John’s journey to data quality, and we have been traveling together on that journey ever since. After I helped him lead Acxiom’s effort to implement a Total Data Quality Management program, he in turn helped me to realize one of my long-time goals of seeing a U.S. university start a degree program in information quality. Through the largess of Acxiom Corporation, led at that time by Charles Morgan and the academic entrepreneurship of Dr. Mary Good, Founding Dean of the Engineering and Information Technology College at the University of Arkansas at Little Rock, the world’s first graduate degree program in information quality was established in 2006. John has been leading this program at UALR ever since. Initially created around a Master of Science in Information Quality (MSIQ) degree (Lee et al., 2007), it has since expanded to include a Graduate Certificate in IQ and an IQ PhD degree. As of this writing the program has graduated more than 100 students.

The second part of this story began in 2008. In that year, Yinle Zhou, an e-commerce graduate from Nanjing University in China, came to the U.S. and was admitted to the UALR MSIQ program. After finishing her MS degree, she entered the IQ PhD program with John as her research advisor. Together they developed a model for entity identity information management (EIIM) that extends entity resolution in support of master data management (MDM), the primary focus of this book. Dr. Zhou is now a Software Engineer and Data Scientist for IBM InfoSphere MDM Development in Austin, Texas, and an Adjunct Assistant Professor of Electrical and Computer Engineering at the University of Texas at Austin. And so the torch was passed and another journey began.

I have also been fascinated to see how the landscape of information technology has changed over the past 20 years. During that time IT has experienced a dramatic shift in focus. Inexpensive, large-scale storage and processors have changed the face of IT. Organizations are exploiting cloud computing, software-as-a-service, and open source software, as alternatives to building and maintaining their own data centers and developing custom solutions. All of these trends are contributing to the commoditization of technology. They are forcing companies to compete with better data instead of better technology. At the same time, more and more data are being produced and retained, from structured operational data to unstructured, user-generated data from social media. Together these factors are producing many new challenges for data management, and especially for master data management.

The complexity of the new data-driven environment can be overwhelming. How to deal with data governance and policy, data privacy and security, data quality, MDM, RDM, information risk management, regulatory compliance, and the list goes on. Just as John and Yinle started their journeys as individuals, now we see that entire organizations are embarking on journeys to data and information quality. The difference is that an organization needs a leader to set the course, and I strongly believe this leader should be the Chief Data Officer (CDO).

The CDO is a growing role in modern organizations to lead their company’s journey to strategically use data for regulatory compliance, performance optimization, and competitive advantage. The MIT CDO Forum recognizes the emerging criticality of the CDO’s role and has developed a series of events where leaders come for bidirectional sharing and collaboration to accelerate identification and establishment of best practices in strategic data management.

I and others have been conducting the MIT Longitudinal Study on the Chief Data Officer and hosting events for senior executives to advance CDO research and practice. We have published research results in leading academic journals, as well as the proceedings of the MIT CDO Forum, MIT CDOIQ Symposium, and the International Conference on Information Quality (ICIQ). For example, we have developed a three-dimensional cubic framework to describe the emerging role of the Chief Data Officer in the context of Big Data (Lee et al., 2014).

I believe that CDOs, MDM architects and administrators, and anyone involved with data governance and information quality will find this book useful. MDM is now considered an integral component of a data governance program. The material presented here clearly lays out the business case for MDM and a plan to improve the quality and performance of MDM systems through effective entity information life cycle management. It not only explains the technical aspects of the life cycle, it also provides guidance on the often overlooked tasks of MDM quality metrics and analytics and MDM stewardship.