How to manage data, lineage, and quality in a decentralized ecosystem?
You are part of a healthcare organization where data is organized and managed by respective data owners in various storage services. As a result of this decentralized ecosystem, discovering and managing data has become difficult. You need to quickly identify and implement a cost-optimized solution to assist your organization with the following: • Data management and discovery • Data lineage tracking • Data quality validation How should you build the solution?
Community Votes
100% of anonymous learners picked answer D. Votes are pick records left by other test-takers — they are not the verified answer.
Community Insight
This question tests your knowledge of Google Cloud's unified data governance service, Dataplex, and its ability to solve the specific problems of data discovery, lineage, and quality, with the common trap being choosing more specialized but incomplete tools.
For a decentralized data environment requiring centralized management, lineage tracking, and quality validation, Google Cloud Dataplex is the recommended solution. The community consensus strongly supports this approach.
A common mistake is choosing Option C (BigQuery and Dataprep), as while these tools perform individual tasks, they do not provide the unified, centralized governance and management across disparate storage services that Dataplex is designed for.
Community Discussion (8 comments)
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Expert Analysis
Why the Answer Is Correct
Dataplex is Google Cloud's intelligent data fabric service designed to provide a unified way to manage, secure, and govern data across data lakes, data warehouses, and data marts. It directly addresses the core requirements of the question: providing a centralized view for data discovery and management, built-in data lineage tracking, and data quality validation rules and checks. This makes it the single, most comprehensive solution for the described decentralized ecosystem.Why the Other Options Are Wrong
Option A, BigLake, is primarily an open storage format that enables queries over data lakes, not a full-fledged data governance and management platform. Option B, building a custom tool on GKE, is a complex, costly, and time-consuming engineering effort that re-invents the wheel, rather than using a managed service. Option C is partially correct as BigQuery and Dataprep can handle lineage and quality, but they are separate services that do not provide the unified, cross-service data management and discovery layer that is the primary challenge described in the scenario.Community Comment Notes
The community comments are unanimous in their support for Option D. The comments consistently describe the choice as "straightforward" and indicate "no doubt" in selecting Dataplex. This strong consensus confirms that Dataplex is the clear and intended answer for this specific set of requirements.Official Reference
Exam Strategy
When presented with a scenario requiring multiple data governance capabilities (management, discovery, lineage, quality) across a decentralized environment, look for a single, integrated service like Dataplex that is designed to provide a unified fabric, rather than cobbling together multiple specialized tools.