By: Bas van Gils (partner at Strategy Alliance)

It is often said that `data is the new oil'. It is hard to figure out with any certainty who wrote about this metaphor first. A cursory search on Google suggests it was used originally in an article by The Economist in 2017, with many authors following suit. The point that is made through this analogy is that data is an important asset to organizations and should be managed as such. This is the field of data management. 

Title

The working title for this book is: A gentle introduction to data management. This book should be available at the end of 2019.

The basics

Data management is a big topic that means different things to different people. In this book it is argued that data management is an organizational capability that helps the organization to (a) get grip on their data assets, and (b) to create value with their data. To be successful, the data management capability has to be firmly embedded in the (existing) processes of the organization. Also, it covers a wide range of topics, ranging from governance, to modeling/ architecture, cloud, analytics and big data. 

Summary

The purpose of this book is to give busy professionals a gentle introduction into the field of data management. This means that data management topics are discussed in a concise manner, helping the reader to understand key issues in the field from a business perspective. The book consists of the following parts:

  • - Introduction: In this part the foundation is laid for the rest of the book. The focus is on defining what it means to manage data as an asset, and why this is important. Also, data management is positioned in the context of other enterprise disciplines such as business process management and enterprise architecture
  • - Theory: The theory part is loosely based on the  DAMA International Guide to Data Management Body of Knowledge(DAMA DMBOK®) , and discusses key topics in the field of data management. After an introduction in which key terms are introduced, this part discusses data governance, metadata management, data modeling, data architecture, data integration, reference data management, master data management, data quality management, business intelligence and analytics, big data, and technology considerations.
  • - Practice: The practice part is concerned with good practices on how to implement an effective data management capability through various use cases. Example topics that are discussed are: how to build a business case for data management? How to find good data owners and data stewards? How to build a good data integration architecture? 
  • - Conclusion: The final part ties theory and practice together and presents an outlook towards the future. It also contains a call to action to practitioners in the field to share their stories, cases, and good practices to keep improving our field together.

Target audience

The book aims at a broad audience: busy professionals who ‘are actively involved with managing data’. This might be a bit too broad because it is hard to imagine a book that would successfully address the needs of strategic decision makers all the way down to analysts and database administrators. A more specific characterization of the audience is:

  • - In the strategic / tactical / operational continuum, the book aims at the middle ground. This means: stay away from executives and top management. It also means: stay away from true day-to-day business operations.
  • - In the business/ technology continuum, the book again aims for the middle ground. It is increasingly true that there is no real difference between business and IT but for the sake of the argument: I am aiming at business people with a sense of IT, IT people with a sense of business, and those who straddle both worlds.
  • - Industry-wise, the book should be agnostic and should be applicable in different industries such as government, finance, telecommunications etc.

Typical roles that come to mind are: data governance office/ council, data owners, data stewards, people involved with data governance (data governance board), enterprise architects, data architects, process managers, business analysts and IT analysts. 

Relevant reading

  • V. Agrawal, Big data in a nutshell - big data is everywhere, but how can we use it? Found online, July 2019, at https://jaxenter.com/big-data-nutshell-159112.html
  • L. DalleMule and T.H. Davenport, What’s your Data Strategy? The key is to balance offense and defense. Harvard Business Review, pages 112–121, May-June 2017.
  • D. Henderson, editor, DAMA DMBOK - Data Management Body of Knowledge. Technics Publications, Basking Ridge, New Jersey, 2017.

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