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GCDL Practice Question: A power utility company collects electricity…

This GCDL practice question tests your understanding of a power utility company collects electricity…. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.

A power utility company collects electricity meter readings from 10 million smart meters every 15 minutes — generating billions of rows of time-series data per year. They need to query this data to detect anomalies and patterns. Which Google Cloud database is optimized for this massive-scale time-series IoT data?

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A power utility company collects electricity meter readings from 10 million smart meters every 15 minutes — generating billions of rows of time-series data per year. They need to query this data to detect anomalies and patterns. Which Google Cloud database is optimized for this massive-scale time-series IoT data?

Answer choices

Why each option matters

Good practice is not just finding the correct option. The wrong answers often show the exact trap the exam wants you to fall into.

A

Distractor review

Cloud SQL (PostgreSQL)

Cloud SQL handles millions of rows efficiently but not billions of rows from IoT at high write throughput. It's an OLTP database not designed for the scale of 10 million meters × 96 readings/day.

B

Distractor review

Cloud Storage (CSV files)

Cloud Storage stores raw files but doesn't provide database query capabilities for anomaly detection or real-time access patterns. Analytics on stored files requires BigQuery or similar.

C

Distractor review

Firestore

Firestore is a document NoSQL database optimized for mobile/web app data with flexible queries. It's not designed for the extreme write throughput and sequential scan patterns of IoT time-series data.

D

Best answer

Cloud Bigtable

Bigtable is designed for exactly this workload: massive time-series data from IoT devices. Row key (meter_id + timestamp) enables efficient range scans. Handles petabytes with sub-millisecond latency.

Common exam trap

Common exam trap: NAT rules depend on direction and matching traffic

NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.

Technical deep dive

How to think about this question

NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.

KKey Concepts to Remember

  • Static NAT maps one inside address to one outside address.
  • PAT allows many inside hosts to share one public address using ports.
  • Inside local and inside global describe the private and translated addresses.
  • NAT ACLs identify traffic for translation, not always security filtering.

TExam Day Tips

  • Identify inside and outside interfaces first.
  • Check whether the scenario needs static NAT, dynamic NAT or PAT.
  • Do not confuse NAT matching ACLs with normal packet-filtering intent.

Key takeaway

NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.

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FAQ

Questions learners often ask

What does this GCDL question test?

Static NAT maps one inside address to one outside address.

What is the correct answer to this question?

The correct answer is: Cloud Bigtable — Cloud Bigtable is a fully managed, massively scalable NoSQL database optimized for time-series, IoT, and financial data — workloads with high-volume sequential read/write patterns keyed by a row key (e.g., meter_id + timestamp). Bigtable handles billions of rows and petabytes of data at sub-millisecond read/write latency. It's purpose-built for this use case: fast ingest of many metrics over time with efficient range scans by key.

What should I do if I get this GCDL question wrong?

Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related GCDL NAT questions on configuration and troubleshooting.

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This GCDL practice question is part of Courseiva's free Google Cloud certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the GCDL exam.