Big Data — Learn free · DataAI Nexus

Self-check

Questions 1–10 of 10

1. When did the term Big Data emerge, and why?
Question 1A. In the 1970s, when relational databases were inventedB. In the early 2000s, as enterprises faced unprecedented growth in the amount, speed and diversity of informationC. In the 1990s, when Bill Inmon defined the data warehouseD. In 2015, when cloud object storage was launchedE. In the 1980s, when tape drives became cheap
2. Which of the three Vs of Big Data refers to the speed at which data arrives?
Question 2A. VolumeB. VarietyC. VelocityD. VeracityE. Value
3. In Big Data's Variety dimension, which of the following are examples of semi-structured data?
Question 3A. Tables in a relational databaseB. JSON and XMLC. Images and videosD. Audio recordingsE. Free-text logs
4. What does the Veracity characteristic of Big Data address?
Question 4A. The physical size of storage clustersB. The number of data sourcesC. The need to ensure trustworthiness and quality despite scale and diversityD. The speed of streaming ingestionE. The cost of commodity hardware
5. What did Hadoop and HDFS (Hadoop Distributed File System) allow organisations to do?
Question 5A. Encrypt all data at restB. Store petabytes of data across clusters of commodity hardwareC. Replace SQL with a graph languageD. Run transactions with ACID guaranteesE. Virtualise data from source systems
6. How does MapReduce process large data sets?
Question 6A. By loading everything into a single server's memoryB. By splitting tasks into smaller units for parallel processing and then aggregating the resultsC. By converting data into JSON documentsD. By streaming records one at a time through KafkaE. By indexing data in a relational table
7. Which NoSQL database is given as an example of a graph database?
Question 7A. RedisB. CassandraC. MongoDBD. Neo4jE. HBase
8. Which Big Data use case involves detecting the same card being used hundreds of kilometres apart within minutes?
Question 8A. Predictive maintenance in manufacturingB. Targeted marketing in retailC. Fraud detection in bankingD. Healthcare analyticsE. Inventory optimisation
9. Which of the following is a streaming framework of the Big Data era that enabled real-time ingestion and analytics?
Question 9A. HiveB. PigC. Apache KafkaD. MongoDBE. HDFS
10. What happened to the Big Data vendor landscape over time?
Question 10A. Cloudera and Hortonworks merged, MapR was acquired by Hitachi, and Databricks and Snowflake emergedB. All Hadoop vendors were acquired by OracleC. Hortonworks acquired DatabricksD. MapR merged with SnowflakeE. The Apache Software Foundation bought Cloudera