This document summarizes a webinar on creating effective graphs and charts using native FileMaker functionality. It discusses best practices for visualizing data, including understanding the audience and purpose, selecting appropriate chart types, preparing the data, and following design principles. Examples are provided of good and bad charting techniques. The webinar focuses on using charts to tell stories and convey meaningful insights from data in a clear, accurate manner.

1. “Ace of Charts” Webinar:
FileMaker-Native Graphs
Lee Lukehart
SavvyData Inc.

2. Facts about Lee
 Certified Developer, FileMaker 11/10/9/8/7
 Authorized Trainer, FileMaker 11/10/9/8/7
 FBA member since 2002 (FSA)
 Practicing consultant
 Datavis enthusiast

3. Assumptions about You
 Experienced FileMaker Pro developer
 Not a graphic designer
 Want to produce effective graphs
 for management vs. marketing
and for business vs. science

4. This web seminar…
will offer:
A bit of theory
A bit of how-to
Alerts to “gotchas”
Cool techniques
will not present:
Dogma
Charting basics
Schema design
Detailed calcs

5. Visual is our dominant modality
 We evolved biologically to rely primarily on sight
 >50% of the brain is used for visual processing
 We use visual metaphors to understand our world
 Visualization is everywhere we look! (pun intended)

6. Visualization Classifications
http://www.visual-literacy.org/periodic_table/periodic_table.html

7. Visualization Classifications
http://www.visual-literacy.org/periodic_table/periodic_table.html

8. Native Charts Types in FileMaker Pro
 Bar
 Horizontal Bar
 Line
 Area
 Pie

9. Composite Charts in FileMaker Pro
 Bullet
 Sparkline
 Horizon
 Gauge
download demo files of these techniques from savvydata.com/resources/

10. Purpose of Charting
 Discern relationships between data points or series
 Identify patterns, trends and exceptions
 Evoke a story about the data
 Engage » Inform » Induce Decision/Action

11. Problems with Charts
 Can be Confusing
 Can be Boring
 Can be Inaccurate and Misleading
 Can be Ineffective and Worthless (or worse)
To be compelling, efficiently display meaningful and unambiguous data.

12. Example
A
Identify a pattern, trend or exception:

13. Example
B
Identify a pattern, trend or exception:

14. Example
C
Identify a pattern, trend or exception:

15. Example

16. Example
D
Identify a pattern, trend or exception:

17. Example
D
Evokes a Story
Identify a pattern, trend or exception:

18. Example
E
Identify a pattern, trend or exception:

19. Example
Truly Tells the Story
To be compelling, efficiently display meaningful and unambiguous data.
E
Identify a pattern, trend or exception:

20. Example
Truly Tells the Story
To be compelling, efficiently display meaningful and unambiguous data.
E
Identify a pattern, trend or exception:
Stacking is now respectable*…
*overlaying elements is a beneficial charting technique

21. How to Produce an Effective Chart
1. Know when not to chart (a table or list may be preferable)
2. Know your data (source, scope… clean & complete?)
3. Consider your audience (their needs & familiarity)
4. Determine chart’s message or focus
5. Select an effective chart type (to best convey message)
6. Construct data transforms (aggregate/augment, as needed)
7. Conduct pre-flight checklist (for QA & K.I.S.S. testing)

22. Know when not to chart
53%*
of 2010 class is female
*dataset 98% complete
the chart in this example is a waste of space

23. Know your data
Example
Four sets of data that
produce identical statistics
can look quite different
when graphed...
(Anscombe’s Quartet)

24.  Ranking comparison (ordered by size or quantity)
 Categorical/Nominal comparison (no inherent natural order)
 Time series, Ordered intervals (contiguous X-axis values)
 Proportion of the Whole (contribution/composition)
 Variance/Deviation (to goal, history or other reference value)
 Distribution (frequency, range, concentration)
 Correlation (causation, dependent variable, pattern echo)
Common uses for business charts:

25. Select the best chart type for the message
 Bar, Vertical
 Bar, Horizontal
 Line
 Area
 Pie
To rank items, show counts, magnitudes, discrete
frequency distributions; to compare different categories
or one category under varied conditions;
Horizontal especially suited for displaying many
categories or when category labels are lengthy
To show contiguous change and other functional
relationships over time; good for multiple data series;
slope of line between points conveys “shape”;
Area charts additionally suggest cumulative values
To represent ratios and relative proportions;
inherently conveys composition and contribution

26. Composite Charts in FileMaker Pro
 Bullet
 Sparkline
 Horizon
 Gauge

27. Composite Charts in FileMaker Pro
 Bullet graphs
stackingorder—>
invented by Stephen Few
“horizontal bar charts on steroids”
conveys several data points qualitatively

28. Composite Charts in FileMaker Pro
 Sparklines invented by Edward Tufte
“data-intense, design-simple, word-sized graphics”
+10%
0
–10%
+5%
0
–5%
compact but informative with high data density
Conveys the “shape” of data over time
Can present as area chart;
colorize for further +/– clarity:

29. Composite Charts in FileMaker Pro
 Horizon charts
stackingorder—>
an atypical chart type (inverted negative scale); requires viewer familiarity
“extremely dense information packing”

30. Construct data transforms as needed
 Aggregate: summarized total, count, average, running average
 Segment: derive subset attributes (e.g. month name, price tier)
 Factor: inflation-adjusted, year-to-year change, time-shifting
 Augment: extend data with truly new data (via web services, etc.)
 Find: full year, by category, include/omit “others”
 Organize/Sort: for display, e.g. multiple years by month
Derive new data to tell the real story

31. Chart Palettes
Normal vision Simulated red-green blind
First 20 colors of each FMP 11 paletteFirst 20 colors of each FMP 11 palette

32. Color Blindness
Normal vision Simulated red-green blind
Usability resources: Photoshop CS4+
Vischeck.com
Colorschemedesigner.com
Etre.com

33. Cognitive Tendencies
We have difficulty discerning volumes and angles
How easily can you rank
the following slices by size?
How about the bars?

34. Cognitive Tendencies
We are often fooled by “obvious” attributes
What is the difference between these two charts?

35. Cognitive Tendencies
non-zero Y-axis scale minimum
Misleading Accurate and Truthful
What is the difference between these two charts?
We are often fooled by implied attributes

36. Chart Scaling in FileMaker Pro
notice the scale range when the spread (low-to-high range of values) is ≥20%

37. Chart Scaling in FileMaker Pro
charts dynamically scale when the value spread is <20%
(assuming y-axis scale min-max is not set)

38. Chart Scaling in FileMaker Pro
notice the largest value is 90% of the scale max

39. Chart Scaling in FileMaker Pro
auto-scale expands when a value is >90% (or <14%) of scale range

40. Charting Pre-flight Checklist
 No chart/multiple charts considered
 Human factors accounted for
 Chart has clear message or focus
 Chart type matches message
 Data integrity confirmed
 Min-max scale covers plotted data
 Y-Axis label: units matches data
 Y-Axis starts at zero (or has reason not to)
 Pie charts have 7 or fewer slices
 Data sorted correctly
Pie chart slices in decreasing size
Bar charts by rank or name order
Time series complete and in sequence
 Audience attributes considered
 Sources footnoted for credibility
 Data selection criteria documented
 Last update & author info optionally noted
 Chart title lists data source & data range
 Descriptors (titles, legend, labels) complete
 Legible font face, size and color
 Color consistently applied
 Info “chunked”: overview first, then detail
 Each element serves a clear purpose
 High data/ink ratio — chartjunk removed
 Other design principles applied as needed

41. Q & A
 Additional resources:
– demo files at savvydata.com/resources/