Question 1:

DEVELOPING INTIMACY WITH YOUR DATA

This exercise involves you working with a dataset of your choosing. Visit the Kaggle (https://www.kaggle.com/datasets) website, browse through the options and find a dataset of interest, then follow the simple instructions to download it. With acquisition completed, work through the remaining key steps of examining, transforming and exploring your data to develop a robust familiarisation with its potential offering:

Examination: Thoroughly examine the physical properties (type, size, condition) of your dataset, noting down useful observations or descriptions where relevant.

Transformation: What could you do/would you need to do to clean or modify the existing data to create new values to work with? What other data could you imagine would be valuable to consolidate the existing data?

Exploration: Using a tool of your choice (such as Excel, Tableau, R) to visually explore the dataset in order to deepen your appreciation of the physical properties and their discoverable qualities (insights) to help you cement your understanding of their respective value. If you don’t have scope or time to use a tool, use your imagination to consider what angles of analysis you might explore if you had the opportunity? What piques your interest about this subject?

(You can, of course, repeat this exercise on any subject and any dataset of your choice, not just those on Kaggle.)

Assignment Link: http://book.visualisingdata.com/chapter/chapter-4

Discussion Length (word count): At least 500 words (not including direct quotes).

Question 2: 

Why is it so important to know your data? Discuss some methods you would implement to better learn and understand your data. What are some advantages to your methods? What are some disadvantages?

Discussion Length (word count): At least 250 words (not including direct quotes).

References: At least two peer-reviewed, scholarly journal references.