Google Cloud Digital LeaderDigital transformation with Google CloudMedium
A multinational financial services company is undergoing a digital transformation to modernize its risk assessment models. They need to process petabytes of historical market data and real-time transaction feeds to identify complex patterns and predict potential financial risks with high accuracy. The solution must be highly scalable, cost-effective for large datasets, and integrate well with machine learning services. Which Google Cloud service is most appropriate for storing and analyzing this data?
- ACloud Spanner
- BCloud Storage
- CBigQuery
- DCloud SQL
Show answer & explanationAnswer & explanation
Correct answer: C. BigQuery
BigQuery is a serverless, highly scalable, and cost-effective enterprise data warehouse designed for petabyte-scale analytics. Its integration with machine learning (BigQuery ML) makes it ideal for complex risk assessment models requiring large datasets.
Why the other options are wrong
- A. Cloud Spanner is a globally distributed, strongly consistent relational database, primarily for transactional workloads requiring global consistency, not a data warehouse for petabyte-scale analytics.
- B. Cloud Storage is an object storage service, suitable for storing raw data but not for directly performing complex analytical queries on petabytes of data.
- D. Cloud SQL is a relational database for transactional workloads, not optimized for petabyte-scale analytical queries.
BigQuery
Google Cloud's fully managed, serverless enterprise data warehouse that enables super-fast SQL queries using the processing power of Google's infrastructure.
- Scales automatically to petabytes and beyond.
- Optimized for analytical workloads, not transactional.
- Offers BigQuery ML for in-database machine learning.
Memory trick: BigQuery queries big data, quickly and clearly.