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

Question 32

Your company has collected all its historical data in BigQuery. Most tables are structured on historical sales data and have a large number of fields, many of which are rarely examined.

Almost all the queries target only current and previous year’s data.

Older data are stored in tables with only statistical aggregates.

They asked you to improve this process, with the following guidelines:

Economically
Ease of use
Security

The system is also going to be used by inexperienced users, so special attention has to be cared for.

Which of these strategies do you consider appropriate (Choose 3)?

A. Use federated Tables organized by timestamp and with mnemonic names
B. Use Partitioned Tables
C. Create Views with a limited number of fields in a new Dataset
D. Create Views with a limited number of fields in the same Dataset
E. Organize reference data produced by analysts with Cloud Storage and External Tables
F. Organize reference data produced by analysts with BigTables and External tables

Answer

Correct Answers: B, C, E

A is wrong. It would require a lot of hard work to organize the new structures every year. It is far much easier to use Partitioned Tables

B is correct. With Partitioned Tables, it is totally automatic to save data in such a way that the queries are faster and, above all, less expensive

C is correct. Views are also important because they can show only the required fields and computed data. In a different Dataset we can manage security in a better way, giving the correct rights to users

D is wrong. Views are also important because they can show only the required fields and computed data. In the same Dataset all users may access all the Data, with security and billing concerns.

E is correct. Analysts create new Data in a very easy way that may be used immediately by BigQuery

F is wrong. BigTable is a powerful NoSQL Database suitable for Big Data. Definitely, not the right choice for small reference data.

BigQuery is a fully managed, low cost, serverless, columnar and ANSI SQL data warehouse that can analyze terabytes to petabytes of data at blazing-fast speed.

Additional features:

Analyze geospatial data using familiar SQL with BigQuery GIS
ML models on large-scale structured or semi-structured data: BigQuery ML
Real-time interactive dashboarding with sub-second query latency using BigQuery BI Engine.
Transferring services and flexible data ingestion
Pay-for-what-you-use pricing

It doesn’t use indexes, but only full scan searches. It is important because you will be charged for the amount of data processed for a query.

So, the use of Partitioned Tables and View is uttermost important.