Presentation is loading. Please wait.

Presentation is loading. Please wait.

Better Information from Better Visualization Nicole Arksey, Inetco Systems Ltd Scott Chapman, American Electric Power.

Similar presentations


Presentation on theme: "Better Information from Better Visualization Nicole Arksey, Inetco Systems Ltd Scott Chapman, American Electric Power."— Presentation transcript:

1 Better Information from Better Visualization Nicole Arksey, Inetco Systems Ltd Scott Chapman, American Electric Power

2 Who we are Nicole – Manager, User Experience and Web Application Group, gets paid to come up with new ways to make it easier for people to understand their data. Scott – Mainframe capacity and performance guy, gets paid to improve and explain mainframe performance and capacity. That often involves visualizing data that is voluminous, complicated, or both. Y’all – here to keep us honest and make this interactive!

3 Why Good Visualizations Are Important

4 Source: http://peltiertech.com/WordPress/use-bar-charts-not-pies/

5 Outline PART 1: Making Bad Visualizations Better PART 2: Visualization Guidelines

6 PART 1: Making Bad Visualization Better

7 Response times by region

8

9

10

11

12

13

14 CPU Utilization

15

16

17 Real Time Application Status

18 Real Time Application Status (Bullet Charts) Threshold Box Threshold Box Average Value Current Value

19 Application Performance

20 Application Performance (Sparklines) Min Value Thresholds Max Value Max, Min and Average Current Value Current Value

21 Number of Incidents

22 Number of Incidents (with historical perspective)

23 Number of Incidents (variation from SLA)

24 Number of Incidents (Just what’s needed)

25 CPU Delay By Hour (Heat chart)

26 CPU Delay By Hour

27 Transaction Data TimeDuration Application Delay TypeRegionStatus September 16, 12:35.12355PurchaseNorthDeclined September 16, 12:35.124103.1ReversalSouthDeclined September 16, 12:35.12510.23.2ReversalNorthFailed September 16, 12:35.12610.33.1ReversalEastDeclined September 16, 12:35.1274.53.4AuthorizationNorthDeclined September 16, 12:35.1284.53.2ReversalNorthApproved September 16, 12:35.12963.3PurchaseWestApproved September 16, 12:35.130103.2PurchaseWestApproved September 16, 12:35.13153.3PurchaseWestApproved September 16, 12:35.1325.53ReversalSouthApproved September 16, 12:35.13383PurchaseWestApproved September 16, 12:35.134123PurchaseSouthApproved September 16, 12:35.135123PurchaseWestApproved September 16, 12:35.13653PurchaseWestApproved September 16, 12:35.13743PurchaseNorthApproved September 16, 12:35.13843PurchaseWestApproved September 16, 12:35.1394.52.1PurchaseWestApproved September 16, 12:35.1404.52.5PurchaseWestApproved September 16, 12:35.14253PurchaseWestApproved September 16, 12:35.1432015PurchaseWestApproved September 16, 12:35.14453PurchaseEastApproved September 16, 12:35.14553.1PurchaseEastApproved

28 Transaction Data (Bubble Charts)

29 Transaction Data (Parallel Coordinates)

30 PART 2: Visualization Guidelines

31 Determine your message first Your data tells a story—have a clear vision of that story Are you showing: Value changes over time? Ratios? Comparisons to thresholds? Relationships between changing values? What conclusion do you want your audience to come to? If you find you have too much data, think about what really needs to be shown to support the intended conclusion Consider highlighting data that supports the conclusion

32 Picking a chart: Values changing over time Classic Line chart Widely used and easily understood May be hard to find individual data values on the line Consider adding data markers (carefully, can lead to cluttered chart) Wide variability between data points can lead to difficult to read chart In Excel, consider using data markers only—no line Area chart Very similar to line chart, but with more “weight” Sparklines Small line charts, meant to be displayed with other information

33 Picking a chart: Ratios and Comparisons Beware the pie chart! More difficult to perceive differences between angles than length If more than a few slices, labeling becomes difficult Consider bar charts Bar length makes differences easier to perceive Consider ordering the observations intelligently Can effectively display many more values Heat maps for large quantities of data Can be difficult to interpret details Work best when interactive with tool tips or click-through to details Consider bullet graphs for threshold comparisons Much more compact than speedometers

34 Picking a chart: Finding relationships Scatter plots Good for comparing two quantative values Correlation generally stands out visually Bubble charts Can be used similarly to scatter plots but variances in bubble size and color can encode two more variables Can be difficult to discern small differences in size/color Interactive bubble charts can be very compelling though Parallel Coordinates Can be used when variables are both quantitative and qualitative Can help you see correlations between multiple variables Can be used with very large number of observations Limited tooling available

35 Colors Use white as your background for your chart Consider intensities of a single color for data ranges Use less saturated colors Reserve vivid colors for highlighting particular data points Consider gray scale for most data, reserving color for highlights Use different colors with similar intensities to denote categories of data Color blindness is common! Red-green: 7-10% Yellow-blue: 6% Free check tool available at vischeck.com

36 Chart Junk Don’t include what’s not needed! Don’t let visual effects distract the reader from the story of your data Unless obfuscation is the goal 3-D effects are often overused and unnecessary Avoid unnecessary gradients, icons, and backgrounds Sometimes a background indicating thresholds may be ok Grid lines don’t need to be dark Y-axis should usually start at zero

37 Tools – everyday use SAS (and R?) Great for data analysis Sophisticated graphical output, with a significant learning curve Excel and other spreadsheet programs Less sophisticated data analysis Much easier to produce customized graphs Consider combining Use SAS/R for initial data analysis, producing a CSV file Use Excel to read the CSV file and produce charts Data range input can be set up to automatically re-read the data when the spreadsheet is opened

38 Tools – Libraries for Web Apps A lot more work than Excel Appropriate for important daily charts Need HTML, CSS, JavaScript skills Or a package that creates the web pages for your Multiple JavaScript libraries available, many free Protovis and D3 (poor support for IE <9) Plotr / Flotr / Flotr2 Raphaël / gRaphaël YUI Charts Dojo Charts JSCharts (commercial licensed) Highcharts (commercial license)

39 Tools - other Parallel Coordinates Parvis XDAT GGobi Many Eyes Try multiple visualization techniques on your data See other people’s visualizations http://www-958.ibm.com/software/data/cognos/manyeyes/

40


Download ppt "Better Information from Better Visualization Nicole Arksey, Inetco Systems Ltd Scott Chapman, American Electric Power."

Similar presentations


Ads by Google