19 Sep Week 4: Discussion: Activities Encapsulated by Working With Data Options Menu: Forum
Week 4: Discussion: Activities Encapsulated by Working With Data 
***THIS IS A NEW Discussion Assignment and has never been used in any previous course****
According to Kirk (2016), most of your time will be spent working with your data. The four following group actions were mentioned by Kirk (2016):
Data acquisition: Gathering the raw material
Data examination: Identifying physical properties and meaning
Data transformation: Enhancing your data through modification and consolidation
Data exploration: Using exploratory analysis and research techniques to learn
Your response will include a pretend project/initiative/effort that does require data to be used as an objective. You will first provide 3-5 sentences describing this effort. You will then describe the actions that would be performed for each group.
This example is very high level that would not earn any points, but will be a general idea that cannot be used and must be expanded in your response:
My project is related to the Widget Company. Our company manufactures widgets and we want to increase revenue.
Data acquisition: Copy all data from internal company sources to my working database.
Data examination: List all files and description of content including dates and field descriptions.
Data transformation: Modify all dates to be presented as MM/DD/YYYY.
Data exploration: Multiple filters used on data to determine gaps, went to library.
Remember your initial post on the main topic should be posted by Wednesday 11:59 PM (EST). Your 2 following posts should be commenting on your classmates’ post on different days by Sunday 11:59 PM (EST). You should end the week with 3 total discussion posts.
A quality post is more than stating, “I agree with you.” Maybe you should state why you agree with your classmate’s post. Additionally, post some examples or find a related topic on the internet or University’s library and comment on it in the discussion post.
Reference: Kirk, A. (2016). Data Visualisation: A Handbook for Data Driven Design (p. 50). SAGE Publications
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