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Professional Data Engineer practice questions

262 free questions with answers and explanations.

Practice test
  1. 251.A global media streaming service processes billions of user interaction events (clicks, views, searches) in real-time. They need to monitor their streaming data pipelines for data quality issues, such as missing events, malformed data, or sudden drops in throughput, and be alerted immediately. The solution must provide real-time visibility into data health and trigger notifications to the data engineering team. Which combination of Google Cloud services is best suited to implement real-time data quality monitoring and alerting for this streaming pipeline?Ensuring solution quality
  2. 252.A global media company uses Google Cloud for its data analytics platform. They have multiple BigQuery datasets across different regions, each containing sensitive user data. To comply with GDPR, CCPA, and other regional regulations, they need to ensure that data access is strictly controlled based on the user's role and their need-to-know, regardless of the dataset's physical location. Specifically, they want to restrict access to certain columns (e.g., email addresses) for specific user groups, while allowing them to view other columns in the same table. Which BigQuery security feature should be implemented to achieve this granular control?Ensuring solution quality
  3. 253.A marketing analytics team uses BigQuery for ad-hoc analysis and reporting. They frequently run queries on large datasets, leading to unpredictable monthly costs due to BigQuery's on-demand pricing model. The team has a consistent budget for data analytics and prefers predictable spending. You need to recommend a BigQuery pricing model that provides cost predictability and potentially better performance for their workload. Which pricing model should they choose?Ensuring solution quality
  4. 254.A media company is developing a new recommendation engine that uses machine learning models. The data scientists frequently experiment with new features and model architectures, requiring rapid iteration and testing. They need a data processing environment that allows them to quickly provision and de-provision clusters, run various open-source data tools (e.g., Spark, Hadoop, Presto), and scale resources up or down on demand without managing underlying infrastructure. You need to recommend a Google Cloud service for this flexible and agile data processing. Which service is most suitable?Ensuring solution quality
  5. 255.A global logistics company uses BigQuery for its operational analytics, processing billions of rows daily. They notice that certain complex queries, particularly those involving large joins and aggregations on historical data, sometimes run for several minutes, impacting dashboard refresh times. The queries are critical and cannot be simplified. You need to optimize the performance of these specific, complex queries while minimizing cost impact. What BigQuery feature should you leverage?Ensuring solution quality
  6. 256.A multinational retail company is building a new customer analytics platform on Google Cloud. They store customer personal identifiable information (PII) in BigQuery and need to comply with GDPR and CCPA regulations. This requires ensuring that customer data can be securely deleted upon request (right to be forgotten) and that data access is restricted based on user roles and data sensitivity. Which BigQuery features should they combine to meet the 'right to be forgotten' and granular access control requirements?Ensuring solution quality
  7. 257.A global ride-sharing company is building a new data processing pipeline to analyze driver and rider location data. Due to the massive scale (trillions of records) and the need for extremely low-latency queries (milliseconds) for real-time decision-making (e.g., dynamic pricing, driver matching), a traditional relational database or standard data warehouse is insufficient. The data is primarily time-series, with new data constantly appended and historical data frequently accessed. You need to select a Google Cloud database service that can handle this scale and performance requirement. Which service is most appropriate?Ensuring solution quality
  8. 258.A global media company needs to process millions of user interaction events per second, such as clicks, views, and searches, to power real-time personalization and analytics dashboards. The data needs to be ingested reliably and cost-effectively, with the ability to scale dynamically to handle peak loads. Which Google Cloud product should the company use for ingesting these events?Designing data processing systems
  9. 259.A global pharmaceutical company is building a new data lake on Google Cloud to store vast amounts of clinical trial data. This data includes highly sensitive patient information, which must be protected according to strict regulatory compliance (e.g., HIPAA, GDPR) and internal privacy policies. The company needs a solution to classify, discover, and protect this sensitive data across various data stores (Cloud Storage, BigQuery, Cloud SQL) without manually inspecting every dataset. Which Google Cloud service should the company leverage to meet these requirements efficiently?Ensuring solution quality
  10. 260.A pharmaceutical company needs to build a data pipeline to process genomic sequencing data. This data arrives in large batches (terabytes per day) and requires complex transformations, including alignment, variant calling, and annotation, before it can be used for research. The processing must be highly parallelizable, fault-tolerant, and able to scale dynamically based on the daily data volume, without requiring the team to manage underlying infrastructure. Which Google Cloud service is best suited for building this batch processing pipeline?Designing data processing systems
  11. 261.A data engineering team is designing a data processing system for a global e-commerce platform. They need to store and analyze customer order history, which can grow to petabytes in size, and perform complex analytical queries on this data for business intelligence and reporting. The solution must provide high availability and strong consistency for query results, while also being cost-effective for long-term storage and ad-hoc analysis. Which Google Cloud product is the most appropriate choice for this scenario?Designing data processing systems
  12. 262.A financial institution processes sensitive customer transaction data daily. Due to stringent regulatory requirements, all data must be encrypted at rest and in transit, access must be strictly controlled and auditable, and data residency must be maintained within a specific geographic region. The solution must also allow for flexible, cost-effective long-term storage of historical data for compliance purposes. Which combination of Google Cloud services and features best addresses these requirements?Designing data processing systems