Practice Test 4 | Google Cloud Certified Professional Cloud Architect | Dumps | Mock Test

Question 35

A large financial company wants to collect and analyze (both in real-time and in batches) a huge amount of stock quotes and historical movements. This data must be processed as follows:

It is necessary to calculate a complete set of statistical parameters, even in streaming mode
A series of forecasting models, currently under development, is going to be set up and backtested

The response times have to be, for every type of operation, in milliseconds and with linear scalability.

Which of the following product groups would you recommend?

A. Pub/sub and Cloud Spanner
B. Cloud Dataproc
C. Composer, Cloud Dataprep, and Cloud Dataview
D. Pub/Sub, Cloud Dataflow, and BigTable
E. Cloud Task and Cloud Datastore

A is wrong. Pub/Sub is correct but Cloud Spanner is a global SQL Database with outstanding integrity and consistency, but don’t have milliseconds performances. We don’t need (and want to pay) all these features.

B is wrong. Dataproc is the Hadoop solution in GCP. It doesn’t really solve the real-time requirement that hasn’t milliseconds performances.

C is wrong. Cloud Dataprep is a tool for Data correction and refining (not required in the question).

D is correct. It is the only solution that meets all requirements.

E is wrong. Cloud Datastore is a performant NoSQL Database, inexpensive but not suitable for Big Data and realtime processing.

Cloud Pub/Sub is a serverless product for stream analytics and event-driven computing. You can send and receive messages between independent applications and transmit data across projects and applications running on the cloud, on-premise, or hybrid environments. Cloud Pub/Sub is perfect to decouple systems and components hosted on GCP or elsewhere on the internet. It provides “at least once” delivery at low latency with on-demand scaling to tens of millions of messages per second.

With Cloud Pub/Sub, data engineers can:

Scale without provisioning, partitioning, or load isolation
Expand applications and pipelines to new regions
Enrich, deduplicate, order, aggregate, and land events using Cloud Dataflow
Mix real-time and batch processing via Cloud Pub/Sub’s durable storage

Cloud Dataflow is a fully managed service for transforming and enriching data in real-time and batch stream.

Cloud Dataflow has a serverless approach that saves money because you only pay for what you use. Plus, Cloud Dataflow not only works with Google’s ingestion, data warehousing, and machine learning products but also third-party tools like Apache Spark and Apache Beam.

https://cloud.google.com/dataflow/

Cloud Bigtable is a NoSQL database service for use cases where low latency reads and high throughput writes, scalability, and reliability are critical.

Main features: