# Course details

Balancing the Four Vs of Data: The Four Vs of Data

### Balancing the Four Vs of Data: The Four Vs of Data

Overview/Description
Expected Duration
Lesson Objectives
Course Number
Expertise Level

Overview/Description

The four Vs (volume, variety, velocity, and veracity) of big data and data science are a popular paradigm used to extract meaning and value from massive data sets. In this course, learners discover the four Vs, their purpose and uses, and how to extract value by using the four Vs. Key concepts covered here include the four Vs, their roles in big data analytics, and the overall principle of the four Vs; and ways in which the four Vs relate to each other. Next, study variety and data structure and how they relate to the four Vs; validity and volatility and how they relate to the four Vs; and how the four Vs should be balanced in order to implement a successful big data strategy. Learners are shown the various use cases of big data analytics and the four Vs of big data, and how the four Vs can be leveraged to extract value from big data. Finally, review the four Vs of big data analytics, their differences, and how balance can be achieved.

Expected Duration (hours)
0.7

Lesson Objectives

Balancing the Four Vs of Data: The Four Vs of Data

• Course Overview
• describe the principle of the four Vs of big data analytics
• specify volume in big data analytics and its role in the principle of the four Vs
• specify variety in big data analytics and its role in the principle of the four Vs
• specify velocity in big data analytics and its role in the principle of the four Vs
• specify veracity in big data analytics and its role in the principle of the four Vs
• discuss the way the four Vs of big data relate to each other
• define variety and data structure and how they relate to the four Vs of big data
• define validity and volatility and how they relate to the four Vs of big data
• discuss how the four Vs should be balanced in order to implement a successful big data strategy
• describe various use cases of big data analytics and the four Vs of big data
• specify how the four Vs can be leveraged to extract value from big data
• describe the four Vs of big data analytics, their differences, and how balance can be achieved
• Course Number:
it_dsbfvddj_01_enus

Expertise Level
Intermediate