FREE MS-DS Master of Data science Big Data Technologies Questions and Answers

Question 1

A financial services company needs to process massive volumes of historical transaction data for end-of-day reporting.
The processing involves complex aggregations and joins.
The key requirements are cost-effectiveness for handling petabyte-scale data and reliability, even with hardware failures.
Which technology is most suitable for this large-scale batch processing task?

Accepted Answer

Hadoop MapReduce

Answer

Apache Kafka

Answer

Apache Spark

Answer

Redis

Question 2

A data science team is developing a machine learning model that requires multiple passes over the same dataset for training. The performance of this iterative algorithm is critical. The cluster has sufficient RAM available. Which big data framework's core design provides a significant performance advantage for this type of workload?

Accepted Answer

Apache Spark

Answer

Hadoop MapReduce

Answer

Apache Hive

Answer

Apache HDFS

Question 3

An e-commerce company wants to implement a real-time recommendation engine. The system needs to ingest a continuous stream of user clickstream data, process it with very low latency, and update recommendations instantly. Which of the following technologies is best suited for building this high-throughput, real-time data pipeline?

Accepted Answer

Apache Kafka

Answer

Hadoop MapReduce

Answer

SQL Data Warehouse

Answer

Apache Pig

Question 4

A social media startup is designing its data architecture. They anticipate storing vast amounts of user-generated content, including posts, images, and connection graphs. The data structure will evolve rapidly as new features are added. Which type of database is most appropriate for this scenario due to its flexible schema and horizontal scalability?

Accepted Answer

NoSQL Database (e.g., Cassandra, MongoDB)

Answer

Relational Database (e.g., PostgreSQL)

Answer

In-memory Database (e.g., Redis)

Answer

File-based Storage (e.g., HDFS)

Question 5

A large enterprise has decided to create a central repository to store all its data—structured transaction records, semi-structured logs, and raw, unstructured video files. Data scientists need access to this raw data for exploratory analysis and to build various machine learning models. The structure of the data will be defined when it is read for analysis. Which big data storage solution best fits these requirements?

Accepted Answer

Data Lake

Answer

Operational Database

Answer

Data Warehouse

Answer

Data Mart

Question 6

A data engineering team is building a unified data processing pipeline. They need a framework that can handle both batch jobs on historical data and real-time processing of incoming data streams using a single, consistent API. This approach would allow them to reuse code and simplify logic. Which framework is explicitly designed to unify these two processing models?

Accepted Answer

Apache Spark

Answer

Hadoop YARN

Answer

Apache Flink

Answer

Apache Kafka Streams