20+ practice questions focused on Storing the Data — one of the most tested topics on the Google Professional Data Engineer exam. Each question includes a detailed explanation so you learn why the right answer is correct.
Start Storing the Data PracticeA data engineer is building a data lake on Google Cloud and needs to separate raw ingested data, curated/cleaned data, and processed/aggregated data. Which Cloud Storage bucket structure is recommended?
Explanation: The recommended data lake structure on Google Cloud is to use a single bucket with separate folders (prefixes) for raw, curated, and processed data. This aligns with the zone-based data lake architecture (raw/bronze, curated/silver, processed/gold) and simplifies management, access control, and lifecycle policies while keeping all data in one place. Cloud Storage folders are just object name prefixes, so this is a logical separation that works well with IAM and lifecycle rules.
A company stores sensitive data in BigQuery and needs to encrypt certain columns with customer-managed encryption keys (CMEK) while using BigQuery's analytics capabilities. What should they do?
Explanation: BigQuery's AEAD encryption functions allow you to encrypt specific columns at query time using customer-managed keys, while still leveraging BigQuery's full analytics capabilities on the unencrypted portions of the data. This approach meets the requirement of encrypting certain columns with CMEK without losing the ability to run analytical queries on the rest of the table.
A data engineer needs to design a Bigtable row key for a time-series IoT application where each device sends data every second. The query pattern is to retrieve all data for a specific device over a time range. Which row key design minimizes hotspots?
Explanation: Bigtable sorts row keys lexicographically and stores contiguous key ranges in tablets on specific nodes. If the row key begins with device_id, all writes for a single device land in one tablet, and if the device_id space is small or skewed, a few tablets absorb most traffic, causing hotspots. Prefixing with a hash of device_id distributes writes uniformly across the key space, while the timestamp suffix preserves the ability to scan a device's data over a time range within a single hash bucket.
A data engineer is designing a Bigtable row key for a time-series application that records temperature sensor readings every second. To avoid hotspotting, they want to distribute writes across all nodes. Which row key design is best?
Explanation: Bigtable sorts rows lexicographically by row key, and writes to adjacent keys land on the same tablet, causing hotspotting. Hashing the sensor_id and prefixing it to the timestamp spreads writes uniformly across the key space, so consecutive writes from different sensors distribute across many tablets. This is the canonical Bigtable time-series pattern recommended by Google.
A company uses Cloud Spanner for a global e-commerce platform. They have a table of orders and a table of order items. To optimize performance for queries that join these tables on order_id, which Spanner schema design feature should they use?
Explanation: Interleaved tables store child rows physically with parent rows, reducing join latency. Secondary indexes are for filtering. Partitioned tables not in Spanner. Denormalization could help but interleaved tables are the designed approach.
+15 more Storing the Data questions available
Practice all Storing the Data questions1. Baseline your knowledge
Start with 10 questions to gauge your current understanding of Storing the Data. This tells you whether you need a concept refresher or just practice.
2. Review every explanation
For each question — right or wrong — read the full explanation. Understanding why an answer is correct is more valuable than knowing the answer itself.
3. Focus on exam traps
Storing the Data questions on the PDE frequently use trap wording. Look for subtle differences in answers that test your precision, not just general knowledge.
4. Reach 80% consistently
Do repeated sessions until you score 80%+ three times in a row. Then move to mixed-mode practice to test cross-topic recall under realistic conditions.
The exact number varies per candidate. Storing the Data is tested as part of the Google Professional Data Engineer blueprint. Practicing with targeted Storing the Data questions ensures you can handle any format or difficulty that appears.
Yes. Courseiva provides free PDE practice questions across all exam topics and domains. The platform includes topic-based practice, mock exams, missed-question review, bookmarked questions, and readiness tracking — no account required.
Difficulty is subjective, but Storing the Data is a high-priority exam concept tested in multiple ways — direct recall, scenario analysis, and command-output interpretation. Consistent practice is the best way to build confidence.
Launch a full Storing the Data practice session with instant scoring and detailed explanations.
Start Storing the Data Practice →