DMT322 Topic 4

What is data in the context of information visualization?

• Finished reports used for decision-making

• Raw facts and figures that must be processed for insights

• Fully processed visual charts

• Only numerical information

What is the main purpose of data transformation?

• To convert data to another programming language

• To make the data unusable for unauthorized users

• To clean, organize, and adapt data for analysis

• To increase the size of the dataset

What is “Exploratory Data Analysis” (EDA) mainly used for?

• Fixing programming errors

• Identifying memory leaks in data processing

• Encrypting sensitive information

• Understanding data by asking and refining questions

What is data abstraction?

• The process of simplifying and structuring raw data to match visualization goals

• The process of removing all metadata from the dataset

• The process of storing data securely

• The act of deleting irrelevant data permanently

In a dataset, what does an “attribute” represent?

• The entire dataset

• A link between datasets

• A property or feature of an item

• A user interaction

What type of data is “car brand” in a dataset?

• Ordinal

• Quantitative

• Nominal

• Boolean

In data abstraction, what does “cardinality” refer to?

• The maximum and minimum values in the data

• The error margin in a dataset

• The type of visualization used

• The number of unique values in an attribute

What is the difference between static and dynamic datasets?

• Static datasets contain only images; dynamic contain text

• Static datasets are unchangeable; dynamic ones are encrypted

• Static datasets are fully available at once; dynamic datasets stream in over time

• Static datasets are used only for print; dynamic for web