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1 more information per pixel Data Visualisation - making your reports useful to business Gary Crawford SQLBITS III Hatfield -

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Presentation on theme: "1 more information per pixel Data Visualisation - making your reports useful to business Gary Crawford SQLBITS III Hatfield -"— Presentation transcript:

1 1 more information per pixel Data Visualisation - making your reports useful to business Gary Crawford SQLBITS III Hatfield - 13 September 08

2 2 Introduction  Gary Crawford  Customer Service Manager @ XLCubed  Sql Consultancy background  Various projects & App Support for Oil Major  XLCubed since 2004  BonaVista more information per pixel

3 3 Agenda  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 more information per pixel

4 4 Tables  Use tables rather than charts where users will: Look up precise, individual values Compare individual values  So simple, what could go wrong? “If the statistics are boring then you’ve got the wrong numbers” – Edward Tufte more information per pixel

5 5 Tables – Gestalt Principles of Visual Perception  German School of Psychology, developed in 1930s more information per pixel  Principle of Proximity  Principle of Continuity  Principle of Closure  Principle of Similarity  Principle of Connection  Principle of Enclosure

6 Tables - Gestalt principle of Proximity  Proximity  We perceive nearby objects as belonging to a group 6 more information per pixel  3 arrangements of 49 dots, 7 by 7  – 3 perspectives of what we are looking at

7 Tables – Gestalt principle of Continuity  Continuity  When something is introduced as a series we tend to perpetuate it 7  Even with inconsistent widths, the visual grouping still persists while the left or right alignment is in place more information per pixel

8 Tables – Gestalt principle of Closure  Closure  Our minds don’t like open ends – they actively seek closure 8  Even with the introduced space after 1 st row we still perceive this as 7 columns more information per pixel

9 Tables – Hermann Grids  Optical illusion of seeing grey dots at the intersections of a black grid 9  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. more information per pixel

10 Tables – recommendations  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 10  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 more information per pixel

11 Tables – applying the theory 11 more information per pixel

12 12 Visual Tables more information per pixel  Bringing chart components into tabular data  Same principles for layout  More later

13 13 Graphs more information per pixel “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 “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

14 14 Graphs – classic graphs more information per pixel “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..

15 15 Graphs – classic graphs more information per pixel “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

16 16 Graphs – classic graphs & chart junk more information per pixel “Maximise the data–ink ratio” – Edward Tufte  Removing the ‘Chart Junk’ leaves a simplified display, and a clearer message

17 17 Graphs – colour in column & bar charts more information per pixel  Mid saturated colours for column & bar charts  Similar intensity, unless one should stand out e.g. own brand

18 18 Graphs – colour in column & bar charts more information per pixel  Don’t use Colour for colour’s sake  Can be distracting & we’ll try to assign meaning

19 19 Graphs –colour in line charts more information per pixel  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

20 20 Graphs –graph sizing more information per pixel  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.

21 21 Graphs –small multiples more information per pixel  Small Multiples  Repetition of small charts, varying by one criteria  If you understand one, you’ll understand them all

22 22 Graphs – lies, damn lies & statistics more information per pixel  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 flat Sales are soaring

23 23 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

24 24 Graph Effects – pimp my graph hall of..  3D, transparency and reflection

25 25 Graph Effects – pimp my graph hall of..  Our winner is

26 26 Pie Charts – some issues & alternatives more information per pixel  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

27 27 Pie Charts – some issues & alternatives more information per pixel  Ranked bars really only alternative for longer lists

28 28 Pie Charts – some issues & alternatives more information per pixel  Multiple Pie Charts to show change particularly difficult to read

29 29 Dashboards "A dashboard is a visual display of the most important information 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) more information per pixel

30 30 Dashboards – some misconceptions  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! more information per pixel

31 31 Gauges & physical imagery – wow, that fast! more information per pixel  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) 

32 32 Gauges– Issues & Alternatives more information per pixel  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

33 33 Sparklines more information per pixel  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 "data-intense, design-simple, word-sized graphics“ Edward Tufte  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

34 34 Sparklines, Bullet Graphs & Visual Tables  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 more information per pixel

35 35 Dashboards – Perception & Processing  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 more information per pixel

36 36 Hall 1 more information per pixel

37 37 Hall 2 more information per pixel

38 38 Hall 2 more information per pixel

39 39 Hall 2 more information per pixel

40 40 Resources 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) William Cleveland Visualizing Data (1993) Rolf Hichert The Dashboard Spy XLCubed blog more information per pixel

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