❤️ I have a lot of empathy for the leaders who are adopting data mesh. ❌ Vendors try to sell you a data mesh in a box or as a button, some analysts try to predict doom and gloom and kill it, and consultants have their solution blueprints in a bag for you. All good intentions, to enable and inform you, but commercially-motivated content often leads to creating confusion. 📕I noticed this pattern early on so I got to work and wrote a book that was free of today’s technology details to equip you with a foundation to make decisions and evolve the conversation. It was a complete brain dump of my rational, observations, experience and some future-focused design. I know, the book is an intense read of 300+ pages. If you are not up for that, here is a short and sweet summary. Happy Friday and happy reading everyone! ☀️ #datamesh
During the last few months of my recent 4+ years of experience in leading a team to setup an enterprise-wide, cloud-based data lake platform, the concept of a data mesh started to gain traction in discussions within some of the use cases utilising the platform. I found this concept intriguing, as my initial understanding suggested that the data mesh approach contradicted the conventional centralised data lake model typical of enterprise-wide setups. However, during that period, I lacked the time and resources required to delve deeper into this novel and seemingly revolutionary concept. I decided to devote time to the topic during the last few weeks. I went deep into the topic, and so was motivated to write a book review on Medium 😊 Loïc Giraud, Ramesh Rajamani, Praveen Kumar, Sreedhar Desineni, Omar Pennacchio, Andrea Splendiani, Adrian Heim, Pascal BOUQUET, Tim O'Sullivan, Sampath Srinivasan, Vikas Sindwani, Fang Deng, Marcel Grossert, Omar Khawaja, Reda Berrada, Stephanie McCracken https://lnkd.in/giAz9Dja
Awesome!