Larry Burns’ latest book, Data Model Storytelling, is all about maximizing the value of data modeling and keeping data models (and data modelers) relevant. Larry Burns is an employee for a large US manufacturer.
In his roles as Data Architect, Data Modeler, and Database Administrator, he has had to complete challenging projects and also fix projects where data modeling was initially skipped. What makes the projects challenging is a combination of vendor packages, government regulations, Agile, Domain-Driven Development, and NoSQL.
This mixture creates a perfect storm that tempts development teams and project managers to focus on solutions and lose sight of understanding the data and business requirements that data modeling delivers. Larry has fought (in nice but influential ways), to make sure proper data modeling is done. He shares his data modeling approaches and beliefs in this book.
This is Larry’s third book. His first was Building the Agile Database, which covers making Agile work without sacrificing data management. His second was Growing Business Intelligence, which provides a gardening analogy to building successful business intelligence projects. The common theme across all of Larry’s books is honesty. When you read any of his books, including Data Model Storytelling, you hear someone objectively sharing their hopes, beliefs, and approaches. There is no ego in his writing, no “you must do it this way,” no taking sides – he unbiasedly shares his thoughts, and it makes his suggestions much easier to accept.
You get a good feel for the book, right at the introduction to Section I, Data Model Storytelling (excerpted with permission from Technics Publications):
We, as data management professionals, play parts in an ongoing story of how data and information are used to add value to various human endeavors. We either realize this fact, or we do not. If we do not, we will fail to recognize opportunities for our characters to advance the purpose of the story and to support the efforts of the other actors on the stage. We will be moving aimlessly around the stage while the audience ignores us, and the story continues on without us.
Once we understand this, we will learn to support the story and its characters rather than against it. Every actor learns to understand the purpose and intent of the story being presented, what the author of the story wishes to communicate to the audience, and what purpose each character contributes to the telling of the story. Every actor, every character, exists for the purpose of moving the intent of the story along and supporting the other characters who are doing the same thing. Every actor needs to learn both his or her “lines” (that is, the specific things that his/her character is doing to advance the story) and also the “cues” that he or she will give to or receive from other characters as the story moves along. Every actor learns to keep one eye on the stage, and one eye on the director.
In data management, the “story” (or “play”) is usually a project of some sort. The intent of the story is to deliver content of some value to an audience (usually business people). The characters are all the people working on different aspects of the project, in different supporting roles. The director is usually a project manager or SCRUM Master. The director’s “direction” takes the form of sprint goals, user stories, and task or work assignments. The director “blocks out” the movement of the actors (project team) on the stage, makes sure each actor understands his/her lines and cues (user stories and tasks), and ensures that the interaction of the actors advances the purpose (goal) of each scene (sprint).
I found myself reading certain paragraphs more than once, trying to remember them to quote Larry in my classes and presentations. I like this quote from Chapter 16:
In my view, the job of the data modeler is not so much the describing of reality to the business as it is the enabling of the business to function effectively within the reality it has chosen; to tell the story that it wants to tell to the world, both now and in the future.
Like any good storyteller, Larry brings bits of other stories into his own. He weaves his tales by referencing some other great storytellers, including Giles, Kent, Simsion, Fowler, Silverston, Hay, and even F. Scott Fitzgerald!
A reader has to have at least one favorite chapter, and mine are Chapters 4 and 5. Larry uses a storytelling analogy throughout the book, and you see this analogy most strongly presented in Chapter 4.
I don’t want to spoil too much of the book for you (don’t you hate those movie reviewers who give away the whole plot…), but I also think his allies and surrogates discussion is brilliant, and also I fully agree with what Larry says with the most important skill a data modeling must possess. What is that skill? Read the case study at the end to find out. I am not going to ruin the plot of the story!