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Answer: 1. Create a Dataplex virtual lake for each data product, and create multiple zones for landing, raw, and curated data. 2. Provide the data engineering teams with full access to the virtual lake assigned to their data product.
The correct answer is D. Creating a Dataplex virtual lake for each data product ensures that each team's data is isolated and can be managed independently. Multiple zones within each lake for landing, raw, and curated data help in organizing and managing data based on its stage in the data pipeline. This structure supports the principle of decentralized ownership and responsibility, crucial for a data mesh architecture. Each team can be given full access to their respective virtual lakes, ensuring they have the autonomy to develop and manage their data products. Additionally, the setup facilitates easy sharing of curated data products across teams by using cross-lake sharing functionality within Dataplex.
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You are tasked with designing a data mesh architecture on Google Cloud, where multiple distinct data engineering teams are responsible for building various data products. The typical data curation design pattern involves landing files in Cloud Storage, then transforming the raw data in both Cloud Storage and BigQuery datasets, and finally storing the curated data product in BigQuery datasets. To achieve this, you need to configure Dataplex in such a way that each team has access only to the assets necessary for their specific data product development, while also ensuring that the curated data product can be easily shared among teams. What steps would you take to accomplish this?
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