Hello and welcome to the first edition of Knowledge Graph & Data Mesh Metaverse which looks at what open source and research communities are talking about with regards to the above. We share a lot of articles, videos, and research via our Discord channels so thought we’d share the love and provide a regular update as to what’s been floating our boats. So, here goes…
A Data Product’s North Star Metric
Head of Data Product at Yelp, Eric Weber, is a regular commentator about all things Data Product. In this article he talks about the importance of identifying ‘one’ metric, or North Star, so data product teams can focus, collaborate with the organisation and data consumers, and monitor and review performance over time.
Paco Nathan talks about graph thinking in this article for the Knowledge Graph Conference. The article looks at graph thinking in terms of cognition and how people who use graph thinking effectively conceptualise problems. The article features lots of further reading and links to his video explaining ‘the village’, detailing the lives and economy of a small village using graph thinking.
Dispelling Common Misconceptions of the Data Mesh
Zhamak Dehghani and Lena Hall joined Barr Moses of Monte Carlo Data to discuss data mesh to help dispel common misconceptions about it. From differentiating mesh from visualisation, to whether a data mesh is the right solution for all data teams, the article is a great abridged version of their recorded talk, which you can see here.
The Path to Data Centricity
Eura Nova released a succinct article focused on a very top level strategic view of implementing a data mesh inside a large organisation. With five main pillars and three recommendations, the article provides a concise framework to build upon.
Architect’s Open-Source Guide for a Data Mesh Architecture
Director of Engineering at Microsoft, Lana Hall, presents this insightful video for the Data & AI Summit. As the title suggests, it is an open-source guide for a data mesh architecture. Lana describes the benefits, challenges, and considerations of a data mesh and features examples of usage and technology to provide an on point presentation around a complicated subject matter.
2021 Developer Survey
Okay, we’re smashing out of the metaverse, but this is still massively relevant. Over 80,000 developers told Stackoverflow how they learn, level up, what tools they use and what they want in this mammoth survey. If you’re interested in learning from your peers, then this survey is a great place to start.
A Parable about Building a Data Team
Finally, a story to make you squirm, laugh, and reach for the bottle of wine. This is an entertaining piece that we’re sure some of you will have lived.
Thanks for reading, if you’ve seen or read anything that you think others might like, get in touch via our Discord community and we’ll ensure we shout about it – and give you credit :).
Why Knowledge Graph & Data Mesh Metaverse?
Glad you asked. Firstly, Metaverse sounds cool and immediately makes us think of a team of data superheroes, plus it’s a trendy word at the minute. Secondly, knowledge graph is close to our hearts, it’s what we build, a document orientated knowledge graph merging the best of document stores and knowledge graphs to be precise, plus we’re part of some amazing knowledge graph communities. Last, but by no means least, we believe that data mesh can provide organizations with the ability to make data easier, less resource intensive, and faster for data consumers to access. By keeping data with domain teams, where the knowledge is, data products will provide more accuracy, security, and flexibility to make businesses more agile and responsive to their customer needs. Maybe we are all data superheroes.