Your organization is modernizing their IT services and migrating to Google Cloud. You need to organize the data that will be stored in Cloud Storage and BigQuery. You need to enable a data mesh approach to share the data between sales, product design, and marketing departments. What should you do?
To enable a data mesh approach, it's essential to allow decentralized data management and ownership while ensuring easy discoverability and sharing across departments. Creating multiple projects for storage and enabling each department to create their own Cloud Storage buckets and BigQuery datasets aligns well with these principles. Furthermore, using Dataplex to map each department to a data lake and their respective Cloud Storage buckets and BigQuery datasets to zones ensures organized management and sharing of data assets. By allowing each department to own and share their data lakes, departments maintain control over their data, supporting the key data mesh principle of decentralized ownership and governance.
- Decentralized ownership: Each department controls its data lake, aligning with the core principle of data ownership in a data mesh. - Self-service data access: Departments can create and manage their own Cloud Storage buckets and BigQuery datasets within their data lakes, enabling self-service data access. - Interdepartmental sharing: Dataplex facilitates data sharing by enabling departments to publish their data products from their data lakes, making it easily discoverable and usable by other departments.
that's pure data mesh, which is what dataplex has been built for
For a straightforward data mesh approach where the focus is on decentralizing data management while enabling easy data sharing and discovery, Analytics Hub is often the more appropriate choice due to its simplicity and directness. It facilitates the core objectives of a data mesh—decentralized data ownership and accessible data sharing—without the added complexity of managing data lakes and advanced governance features.
I think its B. I know since we are talking about Datamesh we want to go to the Dataplex service suddenly. However, in Dataplex a Lake can only have assets (bq tables etc) that are in the same project as the Dataplex service. Example: There is bq table in project A and B. I want to to create a Lake in Dataplex in Project A that contains tables of project B. I can´t do that, i can only host tables of the Project A, since the Lake is in project A. With this said, I think the best option is B, because the datamesh approach is related to "to share the data between sales, product design, and marketing departments". So the question is focusing only in the sharing part of the datamesh. Option B fits just fine.
I was wrong in my explanation guys. Look at this link: https://cloud.google.com/dataplex/docs/add-zone "A lake can include one or more zones. While a zone can only be part of one lake, it may contain assets that point to resources that are part of projects outside of its parent project." So, option D seems good.
Option D
For me, Dataplex looks more logical
D. Dataplex looks more suitable for data mesh approach, Check the ref - https://cloud.google.com/dataplex/docs/introduction