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more information per pixel. Data Visualisation - making your reports useful to business . SQLBITS III Hatfield - 13 September 08. Gary Crawford gary.crawford@xlcubed.com. Introduction. more information per pixel. Gary Crawford Customer Service Manager @ XLCubed

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more information per pixel
more information per pixel

Data Visualisation

- making your reports useful to business

  • SQLBITS III
  • Hatfield - 13 September 08
  • Gary Crawford
  • gary.crawford@xlcubed.com
introduction
Introduction

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  • Gary Crawford
    • Customer Service Manager @ XLCubed
  • Sql Consultancy background
    • Various projects & App Support for Oil Major
  • XLCubed since 2004
    • BonaVista
agenda
Agenda

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  • Objectives
  • Key tools of Data Presentation
    • Tables
      • Best practice
    • Graphs
      • ‘Classic’ graphs – best practice
      • Pies & why they can be bad for you
      • Graph Effects
      • Finely beveled gauges
  • Dashboards
      • The Halls of Shame & Fame
      • Tips & techniques
      • 5 minute example
tables
Tables

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“If the statistics are boring then you’ve got the wrong numbers” – Edward Tufte

  • Use tables rather than charts where users will:
    • Look up precise, individual values
    • Compare individual values
  • So simple, what could go wrong?
tables gestalt principles of visual perception
Tables – Gestalt Principles of Visual Perception

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  • German School of Psychology, developed in 1930s
  • Principle of Proximity
  • Principle of Continuity
  • Principle of Closure
    • Principle of Similarity
    • Principle of Connection
    • Principle of Enclosure
tables gestalt principle of proximity
Tables - Gestalt principle of Proximity

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  • 3 arrangements of 49 dots, 7 by 7
    • – 3 perspectives of what we are looking at
  • Proximity
    • We perceive nearby objects as belonging to a group
tables gestalt principle of continuity
Tables – Gestalt principle of Continuity

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  • Even with inconsistent widths, the visual grouping still persists while the left or right alignment is in place
  • Continuity
    • When something is introduced as a series we tend to perpetuate it
tables gestalt principle of closure
Tables – Gestalt principle of Closure

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  • Even with the introduced space after 1st row we still perceive this as 7 columns
  • Closure
    • Our minds don’t like open ends – they actively seek closure
tables hermann grids
Tables – Hermann Grids

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  • Headache inducing & to be avoided
  • Gestalt tells us gridlines are unnecessary in most cases
    • Where they can’t be avoided, subdue the gridlines. They are at best supporting cast to the numbers.
  • Optical illusion of seeing grey dots at the intersections of a black grid
tables recommendations
Tables – recommendations

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  • The Numbers
    • Align at the decimal point
    • Use thousand separators
    • Precision - round in ‘000s if appropriate to clarify
    • In most cases row & column totals help
  • Use white space and alignment to build the table
    • Right-Align columns of whole numbers, or whole numbers and text (i.e. headings)
    • Left align columns of text
    • Just enough vertical white space in breaks to make them noticeable
    • Relative spacing can affect the direction of reading
  • Avoid Gridlines - They tend to distract from the data
    • If you think you can’t
      • - try alternate, light, fill colours
      • Or just rules, i.e. one axis
    • If you really can’t, make them subtle - thin, and low saturation
tables applying the theory
Tables – applying the theory

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visual tables
Visual Tables

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  • Bringing chart components into tabular data
  • Same principles for layout
  • More later
graphs
Graphs

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“Simplicity is the ultimate sophistication” – Leonardo da Vinci

  • Use graphs rather than tables where:
    • Data sets are large and complex
    • The message is in the shape or distribution of the numbers
    • To reveal relationships among multiple values
  • A picture is worth a thousand words
    • Can be true of graphs, but too many times that’s not the case

“We now have easy access to creative programs which render all of us amateur graphic designers. Too often though the necessary knowledge about basic information design principles is missing.” - Rolf Hichert

graphs classic graphs
Graphs – classic graphs

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“Above all else show the data” – Edward Tufte

  • The purpose of a graph is to visualise the data
    • The data components are the most important elements
    • Everything else is ancillary, and should be muted in comparison
  • Less is more..
graphs classic graphs1
Graphs – classic graphs

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“Above all else show the data” – Edward Tufte

  • Plot area colour - is this helping? No, so remove it.
  • Plot area borders & gridlines – remove / subdue
  • Subdue the axes & Legend, Legend border
  • Remove column borders
    • – difficult to see Product C
      • Because of the abysmal colour scheme
  • Column & Bar Chart colours
    • Shouldn’t clash horribly
    • Low – mid saturation, they have a solid block, don’t overdo it
graphs classic graphs chart junk
Graphs – classic graphs & chart junk

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“Maximise the data–ink ratio” – Edward Tufte

  • Removing the ‘Chart Junk’ leaves a simplified display, and a clearer message
graphs colour in column bar charts
Graphs – colour in column & bar charts

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  • Mid saturated colours for column & bar charts
  • Similar intensity, unless one should stand out e.g. own brand
graphs colour in column bar charts1
Graphs – colour in column & bar charts

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  • Don’t use Colour for colour’s sake
    • Can be distracting & we’ll try to assign meaning
graphs colour in line charts
Graphs –colour in line charts

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  • Again, remove the chart junk
  • Line Series Colours need to be stronger than for Columns & bars , less body
  • Make the lines fairly thick & easy to see, it’s the main aspect
graphs graph sizing
Graphs –graph sizing

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  • Historically graphs & charts have been physically big
    • Partly legacy issues of screen resolution etc
  • Is the smaller, inset chart more difficult to read than the larger?
    • Free more screen real estate, & are often easier processed.
graphs small multiples
Graphs –small multiples

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  • Small Multiples
    • Repetition of small charts, varying by one criteria
    • If you understand one, you’ll understand them all
graphs lies damn lies statistics
Graphs – lies, damn lies & statistics

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  • Columns & bars should be zero-based, or state very clearly they are not
    • Are read by relative comparison of the length
    • S East is actually 48% larger than S West, as opposed to 450% difference in the data columns

Sales are soaring

Sales are flat

graph effects
Graph Effects
  • PCs, graphics cards, displays & software march on
    • ‘Tech Chart Junk
  • Lots of collateral imagery & effects now available on graphs
    • Almost none of the peripherals helps in the central task of displaying data
    • Most common example – 3D
  • Compare the Q3 value for Spain in both charts
graph effects pimp my graph hall of
Graph Effects – pimp my graph hall of..
  • 3D, transparency and reflection
pie charts some issues alternatives
Pie Charts – some issues & alternatives

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  • Pie Charts are now fairly ubiquitous,
    • Typically used for part – to whole relationships
  • Some issues
    • Brain is working to convert 360 to a 10-base.
    • Difficult to compare similar sized segments
    • Don’t handle more than 4 or 5 values well
    • Eye constantly moving to & from the legend
  • In many cases ranked bars will work better
pie charts some issues alternatives1
Pie Charts – some issues & alternatives

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  • Ranked bars really only alternative for longer lists
pie charts some issues alternatives2
Pie Charts – some issues & alternatives

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  • Multiple Pie Charts to show change particularly difficult to read
dashboards
Dashboards

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"A dashboard is a visual display of the most importantinformation needed to achieve one or more objectives; consolidated and arranged on a single screen so the information can be monitored at a glance."

Stephen Few, Information Dashboard Design (2006)

  • Needs an audience and an objective

“By showing vast amounts of data within the eyespan, spatial adjacency assists comparison, search, pattern-finding, exploration, replication, review."

Edward Tufte, Beautiful Evidence (2006)

dashboards some misconceptions
Dashboards – some misconceptions

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  • There is one dashboard which will serve everyone
    • Not unless it’s a very small business
    • Finance / Credit Control / Sales / HR / Ops
  • Mistaking Presentation for content
    • Everyone wants some eye-candy reports right?
    • No, typically people want reports which make their job easier
    • If the content isn’t there it’s the Emperor’s New clothes
    • If your dashboard shows 5 figures, you don’t need a dashboard, you need a table or a sentence.
  • A Dashboard should literally look like a car / train / ship / plane dashboard
    • No!
gauges physical imagery wow that fast
Gauges & physical imagery – wow, that fast!

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  • Gauges, thermometers, traffic lights & other physical imagery has proliferated most charting software
  • Running a business is not like driving a car / ship / boat
    • Cars are real time, needing real time response
    • Need to be able to glance at the instrumentation, not analyse it in any depth
    • Gauges highlight / exaggerate real time movement
      • Pressure build up in boiler #1!
  • Business reports don’t move as you read them
  • You’ll need more than 4 gauges to ‘drive’ a business
    • Guilty as charged (RIP)
gauges issues alternatives
Gauges– Issues & Alternatives

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  • Issues
    • Space hungry, often displaying just 1 number
    • 360 degree base,
    • Imagery detracts from the data display
    • Eye candy, largely non data-ink.
  • Alternatives
    • A text number
    • Simple Bars with a target line
  • ‘Bullet Graph’
    • Invented by Stephen Few as a direct replacement for gauges
sparklines
Sparklines

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"data-intense, design-simple, word-sized graphics“ Edward Tufte

  • Designed by Edward Tufte (Beautiful Evidence, 2006)
    • ‘bare bones’ cut down chart, sized to fit within text or tables
    • succinct, and located where they are discussed
  • No quantitative scale?
    • Not intended for quantitative precision
    • Purpose is to add context & perspective
    • A quick view which can be quickly assimilated
  • Sparklines becoming mainstream
    • business users see their value and actively seek them out
sparklines bullet graphs visual tables
Sparklines, Bullet Graphs & Visual Tables

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  • Sparklines & Bullet Graphs can fit into, and significantly extend tabular data
  • Extension of ‘small multiples’
  • Typically used to show the most important numbers (current) but set their historical context
dashboards perception processing
Dashboards – Perception & Processing

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  • Size
    • All other things being equal we tend to focus on the largest element first.
  • Colour and contrast
    • after an element’s size the next thing that will determine its prominence or visibility is its colour and how that contrasts with the overall colour
    • Use with caution
      • “Avoiding catastrophe becomes the first principle in bringing colour to information: Above all, do no harm." Edward Tufte
hall 1
Hall 1

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hall 2
Hall 2

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hall 21
Hall 2

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hall 22
Hall 2

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resources
Resources

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Edward Tufte

The Visual Display of Quantitative Information (1983)

Visual Explanations (1990)

Envisioning Information (1997)

Beautiful Evidence (2006)

Stephen Few

Show me the Numbers (2004)

Information Dashboard Design (2006)

www.perceptualedge.com

William Cleveland

Visualizing Data (1993)

Rolf Hichert

www.hichert.com

The Dashboard Spy

www.dashboardspy.com

XLCubed blog

www.xlcubed.com/en/blog.html