Data Mesh in Practice: How Europe's Leading Online Platform for Fashion Goes Beyond the Data Lake

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Databricks

Databricks

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Пікірлер: 11
@SilverDog-zl9wm
@SilverDog-zl9wm 2 жыл бұрын
Interesting that Arif states that Zhamak was the first person to coin the term Data Mesh in her whitepaper. Gartner published an article on Data Mesh in 2016. The term has been around a while.
@αλήθεια-σ4κ
@αλήθεια-σ4κ 3 жыл бұрын
New paradigm, very well explained ! Summary 30:29
@Amivit
@Amivit 3 жыл бұрын
Going on the same journey! How do you handle number of workspaces and external hives? Is it feasible having as few workspaces as possible and using table access control, or do you want many different workspaces and then use syncing mechanisms between external hives to share the metadata? I'm a bit torn on how to do the split.
@hrishabhg
@hrishabhg 2 жыл бұрын
Do we require centralised infrastructure despite having central metastore (table meta & access)? Every derived data product can use its own infra by getting relevant accesses via metastore controls. Centralised governance on all metastores and workflow orchestration (or minimum CDC triggers) can bring the best isolation and best scaling model.
@Gus4r4po
@Gus4r4po 3 жыл бұрын
Great presentation!!! I wonder if at the metadata layer you are using among other many things lake formation.
@anuragmishra5526
@anuragmishra5526 2 жыл бұрын
I did not understand the compulsion of keeping still the centralised service and taking your own bucket concept. A data mesh should everything be decentralised where everything is domain bounded. The interoperability and discoverability should be provided by each service rather than keeping this in centralised storage.
@Michiel012
@Michiel012 2 жыл бұрын
I think it is because then you can still do central governance. Easier to manage access rights when the buckets are centralised.
@hermannjoel7208
@hermannjoel7208 2 жыл бұрын
cristal clear!!!
@vio4jesus
@vio4jesus 2 жыл бұрын
Looks good on paper ~ HOWEVER ~ most of the consumers need data ACROSS domains (or products). This is the VERY REASON we have data warehouses. Integrated data, or data across domains or products. Looks good on the back of a napkin, but uh, it's NOT practical in the real world where integrated data is needed.
@ShravanKumar-yv4be
@ShravanKumar-yv4be Жыл бұрын
You just explained what data mesh is. There are no insights as to how this was implemented.
@vio4jesus
@vio4jesus 2 жыл бұрын
Build data products QUICKLY..... uh, like we just 'add water' and the data grows on its own? LOL. My friend, you be smokin' something. Operational data ALWAYS coexists with function. It's a form or an app that creates data, generally either by selection or data entry. SOMEBODY has to write code SOMEWHERE if you want new data (for a product) that doesn't already exist.
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