Question 1

Why is big data analytics useful?

Accepted Answer

Big data analytics is useful because it helps organizations uncover insights, patterns, and trends from large data sets, enabling informed decision-making, enhancing operational efficiency, understanding customer behavior, and gaining competitive advantages.

Question 2

What is an example of big data analytics?

Accepted Answer

An example of big data analytics is the healthcare sector using vast patient records, medical claims, and clinical outcomes to derive insights for better patient care, treatment predictions, and resource allocation.

Question 3

What are the 3 types of big data?

Accepted Answer

The three types of big data are:
Structured Data: Organized and easily searchable data, like databases.
Semi-Structured Data: Contains both structured and unstructured components, like XML or JSON files.
Unstructured Data: Includes raw, unorganized data, such as text, images, videos, and social media posts.

Question 4

What are the primary sources of Big Data?

Accepted Answer

The primary sources of Big Data include internet clickstream data, web server logs, cloud applications, mobile applications, social media content, customer communications (emails, surveys), mobile phone records, and data from Internet of Things (IoT) sensors.

Question 5

Why is data cleansing essential in Big Data Analytics?

Accepted Answer

Data cleansing, or data cleaning, is crucial in Big Data Analytics as it ensures data accuracy, consistency, and reliability. By eliminating errors, redundancies, and inconsistencies, organizations can derive more accurate insights and make informed decisions.