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tangential: Has anyone read DMBOK and what's your impression of its usefulness for software engineers? https://www.dama.org/cpages/body-of-knowledge https://www

tangential: Has anyone read DMBOK and what's your impression of its usefulness for software engineers? https://www.dama.org/cpages/body-of-knowledge https://www.dama.org/cpages/body-of-knowledge I ran into DMBOK just a few days ago when trying to figure out how to level up my schema-design skills. It sounds potentially useful as a map breaking down which directions to research in, but based on my research DMBOK also seems potentially much broader and shallower than what I need if what I'm really interested in is just the data modeling / data implementation slice. SWEBOK doesn't doesn't appeal as much to me personally right this moment, because my software engineering foundation already feels secure. DMBOK and PMBOK on the other hand feel more potentially interesting because they cover adjacent fields, so they feel like they'd be helpful in giving me hooks to grow towards being a "T-shaped" expert. DMBOK in particular sounds intriguing because my company and team are running into more and more data scalability and queryability challenges. I'm no stranger to day-to-day data modeling and schema building as it applies to webapps, but data modeling is something I've never had any formal training in, so I suspect my solutions tend to be only naively mature. I'm probably currently sitting in the Dunning-Kruger valley of data modeling. At the same time, DMBOK is intimidating because it's only available as a giant paper tome. I am a minimalist and am worried about the space on my bookshelf. I'd appreciate any impressions you can give if you've used it in the past. Curious about the other DAMA publications as well.

haffi112 5y ago
I started reading DMBOK, it's quite detailed as you describe. It's more of a reference in my opinion though. It can be a nice exercise to read through it with a group at your company. Have people relate to what is stated in the book to create actionable goals.
- NAR8789 5y ago
  Thanks! To pick your brain... did you approach mostly the data modeling / data security / other slices more closely related to software engineering, or did you also socialize it out and get other people and teams involved in other slices like data governance? Can you speak to your specific situation at the time and any specific takeaways? More nitty-gritty... any suggestions for how to read through as a group in remote work? Feels like the only way might be to get each person a copy...
  - haffi112 5y ago
    We read it cover to cover (this was a mistake as the book is just way too long). We usually covered a chapter in each meeting. I recommend picking one or two chapters that you need to focus on. They also have a shorter version that was released a couple of years ago you might want to look at first. Every meeting started with five minutes of writing on post-it notes how the contents of the chapter related to us (6-10 people in each meeting). Each person then put their post-it notes on a whiteboard. We had several categories to put the notes into (like "good"/"bad"/"how to apply"). This encourages people to read as they need to actively participate and contribute in the discussion. However, this book is not for everyone, some will definitely find it boring and dry. I think it is more fun the deeper you are involved in data related issues. The end of the meeting consisted of us summarizing the results to see if people were experiencing the topic similarly. We had several stakeholders in the reading group and they were from different siloes in the enterprise. It was nice to see that a lot of the experience was shared and there was general agreement regarding feedback. One memorable takeaway was the realization that we needed a data dictionary. That eventually led to a pilot project.

haffi112 5y ago

I started reading DMBOK, it's quite detailed as you describe. It's more of a reference in my opinion though. It can be a nice exercise to read through it with a group at your company. Have people relate to what is stated in the book to create actionable goals.

NAR8789 5y ago
Thanks! To pick your brain... did you approach mostly the data modeling / data security / other slices more closely related to software engineering, or did you also socialize it out and get other people and teams involved in other slices like data governance? Can you speak to your specific situation at the time and any specific takeaways? More nitty-gritty... any suggestions for how to read through as a group in remote work? Feels like the only way might be to get each person a copy...
- haffi112 5y ago
  We read it cover to cover (this was a mistake as the book is just way too long). We usually covered a chapter in each meeting. I recommend picking one or two chapters that you need to focus on. They also have a shorter version that was released a couple of years ago you might want to look at first. Every meeting started with five minutes of writing on post-it notes how the contents of the chapter related to us (6-10 people in each meeting). Each person then put their post-it notes on a whiteboard. We had several categories to put the notes into (like "good"/"bad"/"how to apply"). This encourages people to read as they need to actively participate and contribute in the discussion. However, this book is not for everyone, some will definitely find it boring and dry. I think it is more fun the deeper you are involved in data related issues. The end of the meeting consisted of us summarizing the results to see if people were experiencing the topic similarly. We had several stakeholders in the reading group and they were from different siloes in the enterprise. It was nice to see that a lot of the experience was shared and there was general agreement regarding feedback. One memorable takeaway was the realization that we needed a data dictionary. That eventually led to a pilot project.