Data Visualization and data mining


Assignment 1

Q1. There are various languages, some are better for data visualization than others.  Please review the basics of Python, SAS, R, and SQL.  What are the qualities of each language regarding data visualization (select at least two to compare and contrast)?  What are the pros and cons of each regarding data visualization (select at least two to compare and contrast)?

Q2. Kirk (2019) notes the importance of formulating your brief.  What does he mean by this?  Please expand this thought by noting how you would create a vision for your work.  Note any real-world examples to expand upon this thought.

250 words each. There must be APA formatted references (and APA in-text citation) to support the thoughts in the post.

Course Textbook: Kirk, Andy.  Data Visualization: A Handbook for Data Driven Design, Second Edition. Sage, 2019.

Assignment 2

Chapter 2

  1. What is the difference between discrete and continuous data?
  2. Why is data quality important?

Chapter 3

  1. Note the basic concepts in data classification.

Discuss the general framework for classification.

The assignment should be 100-150 words. There must be APA formatted references (and APA in-text citation) to support the thoughts in the post.