Data Visualization - Exploring and Explaining with Data

This set of flashcards covers key concepts from the Data Visualization lecture notes, focusing on definitions, types of analytics, and the significance of data visualization.

What is data visualization?

Data visualization is the graphical representation of data and information using displays such as charts, graphs, and maps.

What is analytics?

Analytics is the scientific process of transforming data into insights for making better decisions.

What are the three developments that have driven the growth of analytics?

Technological advances, methodological developments, and explosion in computing power and storage capability.

What are the types of analytics?

Descriptive analytics, predictive analytics, and prescriptive analytics.

What is the primary purpose of data visualization?

To explore data and to communicate or explain a message.

What is descriptive analytics?

It encompasses a set of analytical tools that describes what has happened in the past.

What distinguishes quantitative data from categorical data?

Quantitative data involves numerical values indicating magnitude, while categorical data involves labels identifying categories.

What are the four Vs of big data?

Volume, velocity, variety, and veracity.

What is Benford's Law?

Benford's Law states that the proportion of observations in which the first digit is 1 through 9 follows given probabilities.

What does a control chart display?

It is a graphical display of a variable of interest plotted over time relative to lower and upper control limits.

What is the function of a funnel chart?

A funnel chart shows the progression of a numerical variable for various categories from larger to smaller values.

What type of chart is used to show data collected over several time periods?

A line chart.

What is a word cloud?

A visual display that contains key terms from a document, sized according to frequency of use.

What type of chart can help identify patterns in data?

A column chart can help identify patterns in data.

What is a higher-level description of predictive analytics?

Predictive analytics uses past data to predict future outcomes or ascertain the impact of one variable on another.

Why is data visualization critical for explaining results found in predictive models?

It helps to convey complex relationships and findings in a clear and understandable manner.