I am a data modeler…and plan on always being a data modeler.
My latest book however, just released last week, is a book on blockchain called Blockchainopoly.
A couple of questions you might have:
— What does a data modeler know about blockchain?
— What’s the book about?
— What does the term “blockchainopoly” mean?
— Why did you write the book?
What does a data modeler know about blockchain? Let’s generalize this question into “what does someone know about any topic?” In the beginning, the answer of course is “absolutely nothing.” But a data modeler is trained to ask questions and based upon the answers received, construct a visual of how the pieces fit together. The visual must be precise and unambiguous, often forcing the modeler to ask more questions as the puzzle is being built. A modeler finishes their work when the subject is understood thoroughly, whether the subject is finance, manufacturing…or even blockchain.
So I applied my modeling skills of asking questions and making things precise to blockchain. If you feel that terms such as “customer” and “account” are difficult to define within your organization, you would not believe the ambiguity that exists within defining terms such as “blockchain” and “bitcoin!” I have been working on this book for about a year…questioning, writing with precision, and then questioning again.
One of my key learnings was that most explanations of blockchain are either too technical or too high level. I hope the first section of my book will provide the right level of explanation to the reader. To answer the second question on what the book is about, there are two other sections of the book: usage and impact.
The usage section discusses how blockchain will impact these nine industries: finance, insurance, government, manufacturing, retail, utilities, healthcare, nonprofit, and media. The reason for building a blockchain application must be one or more of these five drivers: transparency, streamlining, privacy, permanence, or distribution. I discuss the impact to each industry using these five drivers, leading to over 40 use cases. Each use case is explained through a process diagram, which I learned how to use through Artie Mahal’s excellent book, How Work Gets Done.
The impact section explores how blockchain will impact data management. Many of you know about the Data Management Body of Knowledge 2nd Edition (DAMA-DMBOK2). This is an amazing book that defines the data management field along with the often complex relationships that exist between the various data management disciplines. One of the uses of DMBOK2 is to assess the impact of new technologies, so I leveraged DMBOK2 to assess the impact of blockchain across these 11 disciplines: Data Governance, Data Architecture, Data Modeling and Design, Data Storage and Operations, Data Security, Data Integration and Interoperability, Document and Content Management, Reference and Master Data, Data Warehousing and Business Intelligence, Metadata Management, and Data Quality Management.
For the third question on the meaning of “blockchainopoly”…what blockchain does is remove or dramatically change the role of a central power authority from a business process. Blockchain replaces the monopoly role of this central power authority with shared responsibility, which I call a “blockchainopoly.” So a blockchainopoly creates shared responsibility in executing a process, as opposed to the powerful position of a central power authority. However, blockchainopoly does not always mean removing the powerful monopoly position completely from the process. Often the organization owning the monopoly still plays an important role in the blockchain application.
The final question on why I wrote the book…the answer has to tie back in some way to data modeling. I wrote the book primarily because I believe blockchain will impact data modeling and data architecture. In some ways blockchain is similar to NoSQL in that it is yet another potentially non-relational way to store data, and therefore the modeler needs to understand this structure when building the physical data model. More significantly, however, is the impact blockchain will have on data architecture, such as in terms of scope and data distribution. I also wrote the book because I wanted to see if you could really use DMBOK2 to assess a new technology, and luckily I found out the answer is “yes!”
Hope you enjoy the book – until the next column!
