1. Which Google Cloud product is a distributed messaging service that is
designed to ingest messages from multiple device streams such as gaming
events, IoT devices, and application streams?
Data Studio
Looker
-> Pub/Sub
Apache Beam Ans : Pub/Sub
2. When you build scalable and reliable pipelines, data often needs to be
processed in near-real time, as soon as it reaches the system. Which type of
challenge might this present to data engineers?
-> Velocity
Variety
Volume
Veracity Ans : Velocity
3. Which Google Cloud product acts as an execution engine to process and
implement data processing pipelines?
Data Studio
Apache Beam
Looker
-> Dataflow Ans : Dataflow
4. Due to several data types and sources, big data often has many data
dimensions.This can introduce data inconsistencies and uncertainties. Which
type of challenge might this present to data engineers?
Velocity
Variety
Volume
-> Veracity Ans : Veracity
5. Select the correct streaming data workflow.
Ingest the streaming data, visualize the data, and process the data.
-> Ingest the streaming data, process the data, and visualize the results.
Visualize the data, process the data, and ingest the streaming data.
Process the data, visualize the data, and ingest the data. Ans : Ingest the
streaming data, process the data, and visualize the results.
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