Practice Test 3 | Google Cloud Certified Professional Cloud Architect | Dumps | Mock Test
A Financial Organization has been growing at a rapid rate and dealing with massive data sets has become an issue. The management has decided to move from on premise to Google Cloud to meet the scaling demands. The data analysts are looking at services which can analyze massive amount of data and can run SQL queries -does data manipulation and visualization in Python. What Google Cloud services can fulfill the requirements?
A. Use Bigquery to run the SQL queries and use Cloud Datalab for detailed data manipulation and visualization in Python.
B. Use Bigtable to run SQL queries and use use Cloud Datalab for detailed data manipulation and visualization in Python.
C. Use Datastore to analyze massive data and use Dataprep for data manipulation and visualization in Python.
D. Use Cloud Spanner to analyze massive data and use Data Studio for data manipulation and visualization in python.
Option A is correct. Big Query can analyze large amounts of data also you can run SQL queries , Cloud Datalab does detailed data manipulation and visualization in Python.
Option B is incorrect. Cloud Bigtable is Google’s NoSQL Big Data database service , and it doesn’t support SQL queries ,use it when you need low latency for high writes and high reads.
Option C is incorrect. Cloud Datastore is a NoSQL document database built for automatic scaling, high performance, and ease of application development not suitable for the current scenario and Dataprep is data service for visually exploring, cleaning, and preparing structured and unstructured datasets of any size with the ease of clicks(UI), not code.
Option D is incorrect. The workload is analytics and Bigquery is the right choiceand Data Studio is a decision report generator service.
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