WorksheetsWeek1
Total questions: 12
Worksheet time: 6mins
How does Big Data Analytics help in customer acquisition?
By reducing product prices
By offering free samples
By providing a personalized shopping experience
By increasing advertising costs
What is the projected growth of the datasphere from 2018 to 2023?
33 Zettabytes to 120 Zettabytes
50 Zettabytes to 150 Zettabytes
40 Zettabytes to 130 Zettabytes
60 Zettabytes to 180 Zettabytes
What percentage of data will need real-time processing by 2025?
20%
25%
30%
35%
Which technology is mentioned in the module for data storage?
Python
MongoDB
Tableau
R
What is one of the tasks you will be able to perform using technologies after this module?
Predict weather patterns
Predict finance trends
Predict geological changes
Predict historical events
What is one of the primary responsibilities of a Big Data Analyst?
Designing infrastructure for large datasets
Analyzing cleaned up data to provide meaningful insights
Managing storage systems
Building data processing tools
What type of database management system is Apache Cassandra?
SQL Database Management System
NoSQL Database Management System
Relational Database Management System
Object-Oriented Database Management System
Which step in the Big Data Analytics Landscape involves transforming raw data into meaningful insights?
Data acquisition
Data processing & analytics
Data storage
Visualisation
Which challenge in Big Data involves ensuring the protection of information?
Data verification
Security issues
Real-time data
Wide variety of technologies
Which of the following is a key benefit of using NoSQL databases in Big Data applications?
They are limited to small datasets
They only support structured data
They offer high scalability and flexibility
They require complex table joins
What is the main purpose of data visualization in Big Data Analytics?
To store large volumes of data
To clean and preprocess data
To transform raw data into insights
To present complex data in an understandable format
Which of the following is considered a challenge when working with Big Data?
Limited data sources
Ensuring data quality and consistency
Small data volumes
Simple data structures
