Practice Test 4 | Google Cloud Certified Professional Cloud Architect | Dumps | Mock Test
Your company has collected all its historical data in BigQuery and Documents in Cloud Storage.
Most BigQuery 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 years and they have to select data by product families and sale regions.
Older data is stored in tables with only statistical aggregates.
They asked you to improve this process, with the following guidelines:
- Economical
- Ease of use
- Security
The system is going to be used less experienced users, so a special attention have to be cared for.
Which one of the following strategies would you consider appropriate?
A. Leave the Organization untouched, It is just perfect
B. Use BigTables with Views
C. Use BigQuery Clustered tables with authorized views
D. Cloud Spanner with authorized views
E. Use Cloud Firebase
Correct Answer: C
A is wrong. The key requirement that you need to meet is to select data by product families and sale regions
B is wrong. BigTable is a NoSQL database, not an Analytics System
C is correct. Clustering Partitioned Tables with Product Type and Sale Region you will gain in speed and spare money.
D is wrong. Cloud Spanner is a global SQL database and not an Analytics System
E is wrong. Cloud Firestore is a NoSQL database and not an Analytics System
BigQuery is a fully managed, low cost, serverless, columnar and ANSI SQL data warehouse that can analyze terabytes to petabytes of data in blazing-fast speeds.
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, Clustering Tables, and View are uttermost important.
Clustering Tables improve the performance of queries when filter clauses based on the contents of clustered columns are used.
When data is written to a clustered table by a query job or a load job, BigQuery sorts the data using the values in the clustering columns. These values are used to organize the data into multiple blocks in BigQuery storage. When you submit a query containing a clause that filters data based on the clustering columns, BigQuery uses the sorted blocks to eliminate scans of unnecessary data.
Similarly, when you submit a query that aggregates data based on the values in the clustering columns, performance is improved because the sorted blocks find out rows with similar values.
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