What is the primary goal of Big Data analytics?
a) To store large amounts of data
b) To process and analyze large datasets for insights
c) To encrypt sensitive data
d) To organize data into a specific format
Which of the following is an example of Big Data?
a) A small database of employee records
b) Data collected from social media platforms
c) A few gigabytes of customer transaction history
d) A single data point stored in a file
Which of the following is NOT one of the V’s of Big Data?
a) Volume
b) Variety
c) Velocity
d) Value
What is “velocity” in the context of Big Data?
a) The speed at which data is stored
b) The speed at which data is generated, processed, and analyzed
c) The amount of data that can be stored
d) The variety of data types available
What does the term “data lake” refer to in Big Data?
a) A structured database
b) A storage repository that holds raw data in its native format
c) A database for transactional data
d) A tool for managing large datasets
Which of the following is a popular Big Data framework?
a) MySQL
b) Hadoop
c) Oracle
d) SQL Server
Which of the following is NOT a characteristic of Big Data?
a) Massive volume of data
b) High speed data generation
c) Structured data only
d) Variety in data types
What is “NoSQL” used for in Big Data analytics?
a) To store structured data in relational databases
b) To store unstructured or semi-structured data in non-relational databases
c) To speed up data processing
d) To convert data into a readable format
What does “MapReduce” do in Big Data processing?
a) It stores data in distributed databases
b) It reduces the amount of data to be analyzed
c) It processes large datasets in parallel across multiple nodes
d) It indexes data for faster search
Which of the following is the primary challenge when dealing with Big Data?
a) Lack of data storage options
b) Data security and privacy issues
c) Managing the speed of data generation
d) Data redundancy
Which of the following technologies is typically used to process real-time Big Data?
a) Hadoop
b) Spark
c) SQL
d) PostgreSQL
Which of the following is an example of structured data?
a) Text from social media posts
b) Sensor data from IoT devices
c) Data in a relational database table
d) Images from a camera
Which of the following types of analytics is focused on predicting future outcomes?
a) Descriptive analytics
b) Diagnostic analytics
c) Predictive analytics
d) Prescriptive analytics
What is “data mining” in the context of Big Data?
a) Collecting and storing data
b) Finding patterns, correlations, and trends in large datasets
c) Organizing data into structured formats
d) Encrypting data for security
Which of the following is a key benefit of Big Data analytics?
a) Reduced cost of data storage
b) Real-time data processing and analysis
c) Limiting the amount of data generated
d) Data security and privacy
Which Big Data technology is primarily used for storing and managing large-scale datasets across distributed systems?
a) MySQL
b) Hadoop
c) MongoDB
d) PostgreSQL
What is “data visualization” in Big Data analytics?
a) The process of encoding data
b) The process of analyzing large datasets
c) The graphical representation of data to make insights easier to understand
d) Storing data in an encrypted format
What is “streaming data” in the context of Big Data?
a) Data that is generated in small, fixed-size batches
b) Data that is generated continuously and in real-time
c) Data that is stored in a structured format
d) Data that is used for offline analysis only
Which of the following is an example of unstructured data in Big Data?
a) Data in CSV files
b) Data in relational database tables
c) Text from customer reviews
d) Data in Excel spreadsheets
Which of the following is an advantage of cloud computing in Big Data analytics?
a) Increased data security
b) Scalability and flexibility in processing large datasets
c) Reduced need for high-speed internet
d) Simplified data storage and retrieval
Which of the following best describes “business intelligence” (BI)?
a) Analyzing historical data to understand business performance
b) Developing machine learning algorithms
c) Securing business data from unauthorized access
d) Storing business data in a centralized system
Which of the following describes “prescriptive analytics”?
a) Analyzing past data to understand business performance
b) Predicting future outcomes
c) Recommending actions to optimize future performance
d) Analyzing data to find correlations
Which of the following tools is used for data analysis and processing in Big Data environments?
a) Excel
b) Tableau
c) Hadoop
d) Notepad
What is “ETL” in the context of Big Data analytics?
a) Extract, Transform, Load
b) Efficient Time Logistics
c) Extensive Transaction Log
d) Encrypted Text Layers
Which of the following Big Data technologies is used for real-time processing?
a) Hadoop
b) SQL
c) Apache Kafka
d) MySQL
Which of the following describes “descriptive analytics”?
a) Analyzing past data to find trends and patterns
b) Making predictions about future outcomes
c) Recommending actions to improve outcomes
d) Identifying anomalies in real-time data
Which of the following is used to store unstructured Big Data?
a) Hadoop Distributed File System (HDFS)
b) Relational databases
c) Spreadsheets
d) CSV files
What is the primary function of “machine learning” in Big Data analytics?
a) To store large datasets efficiently
b) To perform real-time data processing
c) To automatically improve algorithms based on data patterns
d) To encrypt sensitive data
Which of the following is the main purpose of “data preprocessing” in Big Data?
a) Storing data in its raw format
b) Transforming data into a clean and structured format for analysis
c) Compressing data for faster processing
d) Analyzing unstructured data
Which of the following analytics techniques uses statistical models and machine learning to predict future events?
a) Descriptive analytics
b) Predictive analytics
c) Prescriptive analytics
d) Diagnostic analytics
What does the term “data wrangling” refer to in Big Data analytics?
a) Storing data securely
b) Visualizing data
c) Cleaning and transforming raw data into usable formats
d) Encrypting data for protection
Which of the following is an example of structured data in Big Data analytics?
a) Customer reviews
b) Transaction logs
c) Social media posts
d) Video files
