Analyzing and Visualizing Data

1. Analyzing and Visualizing Data Dr. Lam TECM 4180

2. What we’ll cover today • Importance of data • Data, information, and knowledge • Introduction to a variety of visualizations and their purposes • Visualization exercise and brainstorm activity

3. Big Data • 90% of all data in the world was generated in the last 2 years. • To put it another way, the average person processes more information in a day than a person who lived in the 1500’s did in their lifetime. • Climate information, social media, digital media, purchase transactions, cell phone GPS data, etc. • Big data can be useful or useless depending on what you do with it • The whole goal of data analysis/visualization is to turn data (raw numbers) into information and make decisions based on this information

4. Some fun but not so useful examples

5. More perspective on data from social media… • 650,000 shares every minute on Facebook • 144 million Tweets on Twitter and 936 million shares on Facebook a day

6. Netflix case study • Records 30 million user plays each day • Internal analytics track when users pause, rewind, fast forward, and search • They also track when users like or share Netflix shows/movies on Facebook

7. Netflix continued

8. And they came up with…

9. Even more useful to society… • Predictive Policing Models led to 12% decrease in property crime in LA

10. Big Data isn’t going anywhere

11. Before we differentiate data, information, and knowledge… • Write down a tip or trick you learned about UNT that you would tell an incoming Freshman. • Write down a tip or trick you know from driving around DFW (e.g., Avoid XX highway at XX time).

12. Data vs. Information vs. Knowledge • Data- raw numbers, words, etc. that lack context or meaning (e.g., 33,715) • Information- application of structure to data to convey meaning (e.g., “enrollment at UNT 33,715 for Spring 2014) • Knowledge- understanding of a specific subject through experience or education (e.g., “33,715 is up from 33,505 in Spring 2013”)

13. Visually…

14. Example 1 Raw Data Yes, Yes, No, Yes, No, Yes, No, Yes, No, Yes, Yes Responses to the market research question – “Would you buy brand x at price y?” Context Processing Information ??? Creative commons attribution to FatMax 2007

15. Example 2 Raw Data 42, 63, 96, 74, 56, 86 Jayne’s scores in the six AS/A2 ICT modules Context Processing Information ??? Creative commons attribution to FatMax 2007

16. Example 3 Raw Data 111192, 111234 The previous and current readings of a customer’s gas meter Context Processing Information ??? Creative commons attribution to FatMax 2007

17. Knowledge Examples • Using the 3 previous examples: • A Marketing Manager could use this information to decide whether or not to raise or lower price y • Jayne’s teacher could analyzethe results to determine whether it would be worth her re-taking a module • Looking at the pattern of the customer’s previous gas bills may identify that the figure is abnormally low and they are fiddling the gas meter

18. A few notes about data, information, and knowledge • Data (provided it hasn’t been manipulated, and has been collected correctly) is objective, and therefore, rarely “incorrect” • A yes is a yes, a no is a no • Information, however, is context dependent. This means it can sometimes be “wrong” • E.g., “Customers preferred Coke to Pepsi” (but when?)

19. Choosing the right graphics • Decide what your story (purpose) is • Select a graphic that most effectively represents this story to your user • Include the proper supplementary information

20. Tables • Purpose: To help your readers find data or other information rapidly • Tables can be useful to compare data, but may not be as effective as a more visual representation • Include a descriptive tie, row and column headings, unit of measure (if needed), and source

21. Line Graph • Purpose: To show trends and cycles; To show the relationship between two or more variables • Tend to be good for interval level variables (numerical data)

22. What’s wrong with this?

23. What’s wrong with this?

24. Bar Graph • Purpose: To help readers compare quantities and see trends at a glance • Tend to be good to display categorical variables (non-numerical)

25. What’s wrong with this?

26. What’s wrong with this?

27. Pie Chart • Purpose: To show the composition of a whole

28. What’s wrong with this?

30. What’s wrong with this?

31. What’s wrong with this?

32. Pictographs • Purpose: To help readers compare quantities and see trends • Simply introduces an additional visual element to an already existing graph (bar, line, etc.)

33. Data Visualization Example • http://www.informationisbeautiful.net/2010/in-deeper-water/

34. What, then, is the purpose of data visualizations? • They provide context for user and transform data into information • Data visualizations tell a story • Stories can be simple or complex, but a visualization should tell the story better than the alternative • Help or lead people to make decisions based on the information

35. Exercise • Find an existing Infographic • See http://www.informationisbeautiful.net for examples if you can’t find one • Identify what graphic or graphics are used (tables, bar charts, pie charts, etc.) • Identify the “story” in 1-2 sentences • Evaluate the infographic based on PARC principles • Identify the supplementary information provided (scale, labels, etc.) • Is this a positive or negative example of an inforgraphic?