Professional Data Engineer

0/12 checked

Q_01 domain/d1 · medium single discuss →

A data engineering team needs to build a serverless pipeline that handles both batch and streaming workloads with a single unified programming model, and they want the resulting code to remain portable across clouds, on-premises, and edge devices. Which characteristic of Dataflow directly supports this portability requirement?

A It is built on the open source Apache Beam SDK with unified batch and streaming support
B It provides committed use discounts of up to 40%
C It offers a job cost monitoring UI for cost estimation
D It supports customer managed encryption keys (CMEK)

Q_02 domain/d1 · medium single discuss →

An architect must design a low-code path to move change data capture (CDC) events into BigQuery quickly, but the team still needs the ability to inject custom transformation logic into those jobs without building a full pipeline from scratch. Which Dataflow approach best fits these requirements?

A Use pre-designed Dataflow templates optimized for CDC and BigQuery integration and add logic with the integrated UDF builder
B Write a fully custom Beam pipeline from scratch and deploy it with the Dataflow runner
C Use Dataflow Insights recommendations to generate the pipeline automatically
D Configure straggler detection to transform the incoming CDC events