Lecture 1: Introduction

Question 1

What are the 4 Vs of Big Data?

as defined by Gartner Group

Answer 1

• Data Volume
• Data Veracity
• Data Velocity
• Data Variety

Question 2

What are the core goals of visualization?

Answer 2

• Exploration
• Explanation
• Engagement

Exploration: Find patterns, outliers, and trends in data.
Explanation: Communicate insights effectively.
Engagement:Create meaningful and impactful visuals.

Question 3

What makes a good Visualization?

Answer 3

• Accurate, clear, and unbiased.
• Tailored to the audience and context.

Question 4

What is Exploratory Data Analysis (EDA)?

“The greatest value of a picture is when it forces us to notice what we never expected to see.”

Answer 4

An approach of analyzing data to summarize their main characteristics without using a statistical model or having formulated a prior hypothesis.

Exploratory data analysis was promoted by John Tukey to encourage statisticians to visually examine their datasets, to formulate hypotheses that could be tested on new datasets.

Question 5

What is Visual Analytics?

Wong and Thomas 2004, Keim 2010

Answer 5

“Visual Analytics is the science of analytical reasoning supported by a highly interactive visual interface.” Wong and Thomas 2004
“Visual Analytics combines automated analysis techniques with interactive visualizations for an effective understanding, reasoning and decision making on the basis of very large and complex datasets” Keim 2010

Detect the expected and discover the undetected!

Question 6

Data Mining/Machine Learning + Visualization =

Answer 6

Visual Analytics/Visual Data Science