Differences information visualization and visual analytics

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Reference no: EM132404776

Section A

Explain if the following statements are true or false in details with scholar references.

1. All data science investigations start with an existing dataset.

2. Data scientists do most of their work in Python and are unlikely to use other tools.

3. Most data scientists spend the majority of their time developing new models.

4. The use of historical data to make decisions about the future can rein force historical biases.

Section B

Each question in this section must be answered in detail (at least 2 paragraph) using references (APA style)

1. Explain with references the differences between Information visualization and visual analytics. (2 paragraphs)

2. Why would you want to use data visualization for Big Data? (2 paragraphs)

3. Data used in visual design comes in a "messy" form and as a result the data must go through a data cleansing process.

a. Explain what is a "messy" data.(2 paragraphs)

b. Explain why a data may come in a "messy" data format.(2 paragraphs)

c. Explain methods that maybe used to cleansed the data.(2 paragraphs)

d. Data sets come in many different format. Many formats are prone to error because the data lack any information that indicates structure.

i. Give examples of data sets that lack structure.(1 paragraphs)

ii. Give examples of data sets that includes structure.(1 paragraphs)

Reference no: EM132404776

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