IBM A1000-051 Intermediate Practice Exam: Medium Difficulty 2025

A financial services company is deploying BigInsights to process large volumes of transaction data. The architecture team needs to ensure that data processing tasks are distributed efficiently across the cluster while maintaining fault tolerance. Which combination of BigInsights components would best support this requirement?

An analytics team needs to query structured data stored in BigInsights using SQL-like syntax while ensuring optimal performance for complex joins across multiple large datasets. The data is already stored in HDFS in various formats including CSV and JSON. What approach should they implement?

A healthcare organization must implement data governance for their BigInsights cluster to ensure that patient records are only accessible to authorized personnel, while also maintaining an audit trail of all data access. Which combination of security features should be implemented?

During a BigInsights cluster operation, the NameNode becomes unavailable due to hardware failure. The cluster was configured with High Availability. What happens to running jobs and data access requests during this failure scenario?

A data engineering team is designing a data pipeline that ingests streaming clickstream data, performs real-time aggregations, and stores results for batch analytics. Which BigInsights components should be combined to implement this architecture effectively?

An administrator notices that certain DataNodes in the cluster are being underutilized while others are near capacity, causing uneven data distribution. What is the most appropriate action to rebalance the cluster while maintaining data availability?

A retail company needs to implement data lifecycle management in BigInsights where older transactional data (over 2 years) should be moved to cheaper storage tiers while remaining accessible for compliance queries. What approach best achieves this requirement?

A BigInsights administrator observes that Spark jobs are failing with 'Container killed by YARN for exceeding memory limits' errors. The jobs process large datasets with complex transformations. What is the most effective approach to resolve this issue?

A data science team wants to perform iterative machine learning algorithms on large datasets stored in BigInsights. They need fast in-memory processing with support for multiple programming languages. Which processing framework and approach would be most suitable?

An organization needs to secure data in transit across their BigInsights cluster while also ensuring that data stored on disk cannot be accessed if physical drives are stolen. Which security measures should be implemented together?