Reading current stakeholder needs and mapping a path to the target state
This objective focuses on gap analysis: understanding existing stakeholder requirements, data sources, current architecture, and skill sets, then designing a migration or modernization plan toward the target state on Google Cloud. Exam questions test whether you can map business requirements to appropriate GCP services while respecting constraints like existing investments, compliance, timelines, and team capabilities.
1 · Learn the must-know
- Always distinguish business requirements (e.g., cost reduction, faster reporting, compliance) from technical requirements (e.g., latency, throughput, schema evolution) since exam scenarios often hide the true driver in a business statement.
- Identify current state artifacts explicitly: existing data sources (on-prem DBs, SaaS, streaming), current processing tools (Hadoop, Spark, ETL scripts), team skills (SQL-only vs. Java/Python), and pain points (manual pipelines, scaling limits, lack of governance).
- A migration/modernization plan should be staged (lift-and-shift then optimize) rather than a full re-architecture in one step, especially when stakeholders have limited cloud experience or tight timelines.
- Map desired state needs to service choices using key differentiators: BigQuery for SQL-based warehousing/analytics, Dataflow for unified batch/stream processing, Dataproc for lift-and-shift of existing Spark/Hadoop jobs, and Pub/Sub for event ingestion.
- Consider organizational constraints such as existing licensing (e.g., keep using Spark/Hive skills via Dataproc instead of rewriting to Beam), data residency/compliance needs, and change-management/training requirements when proposing the plan.
- A good plan explicitly ties each proposed GCP service back to a stated stakeholder need or current gap, since the exam often tests whether the 'best' answer matches the actual requirement versus a technically superior but requirement-mismatched option.
2 · Check your understanding
A logistics company's dispatch team currently pulls GPS location data from trucks into an on-premises MySQL database, where an hourly cron job aggregates distances for rerouting decisions. Dispatch complains that hourly latency is too slow, but the finance team depends on those same hourly aggregates for accurate billing reports and does not want the report format to change. A data engineer is asked to create a plan to modernize this pipeline on Google Cloud. Which action best reflects a thorough analysis of current needs before proposing a new architecture?
What you have tried across GCP PDE's objectives, not a readiness score.
Designing data processing systems~22% of the exam0 of 17 tried
Ingesting and processing the data~25% of the exam0 of 11 tried
Storing the data~20% of the exam0 of 13 tried
Preparing and using data for analysis~15% of the exam0 of 11 tried
Maintaining and automating data workloads~18% of the exam0 of 15 tried
3 · Keep going
Ready for more? Take a weighted mock or try free practice questions.