Google Professional Data Engineer Question 214
Select 4Google Cloud PlatformYour company is analyzing a large dataset containing customer transaction records stored in Google BigQuery. The goal is to identify trends over time and calculate key business metrics. The team is considering using SQL queries to analyze the data, but they are concerned about the cost and efficiency of running large queries repeatedly. Which of the following approaches should you recommend to optimize cost and performance for exploration and analysis in this scenario?
- A
Use BigQuery's preview feature to explore the data before running full queries.
- B
Partition the BigQuery table by the transaction date to reduce scanned data when querying.
- C
Store the dataset in Google Cloud Storage and analyze it using Dataflow to avoid BigQuery costs.
- D
Create materialized views in BigQuery to precompute and reuse frequently accessed query results.
- E
Use BigQuery's data sampling feature to run queries on a subset of the dataset during exploration.
Show answer and explanation
Correct answers: A, B, D, E
Explanation
To optimize cost and performance while analyzing large datasets in BigQuery, you can leverage features like table preview, partitioning, materialized views, and data sampling. These techniques enable efficient exploration and analysis by minimizing the amount of data scanned and reducing computational overhead, ensuring cost-effective and performant queries.
- A. Correct.
Using BigQuery's preview feature allows you to examine the structure and content of the table without incurring query costs, making it an efficient step for exploration.
- B. Correct.
Partitioning the table by transaction date ensures that only relevant partitions are scanned during queries, reducing query costs and improving performance.
- C. Incorrect.
While Google Cloud Storage and Dataflow are useful for ETL processes, they are not optimized for interactive exploration and analysis of structured data like in this scenario. BigQuery's native features are better suited for this use case.
- D. Correct.
Materialized views precompute results of complex queries, enabling faster and more cost-efficient reuse for repeated analyses.
- E. Correct.
BigQuery's data sampling option allows you to analyze a smaller subset of the data, reducing costs during the initial exploration phase.