Ssrs the good the bad the ugly
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Ssrs the good the bad the ugly






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  • In his Eudemiarz Summary, Proclus (410-485) tells us that Ptolemy Soter, the first King of Egypt and the founder of the Alexandrian Museum, patronized the Museum by studying geometry there under Euclid. He found the subject difficult and one day asked his teacher if there weren't some easier way to learn the material. To this Euclid replied, "Oh King, in the real world there are two kinds of roads, roads for the common people to travel upon and roads reserved for the King to travel upon. In geometry there is no royal road."
  • For example: bank statements, pension statements, and mobile phone bills are examples of presented data that we receive frequently.Data Visualisation is about storytelling – going from the data to the facts. Data Visualisation can be used in different ways.
  • Mobilise knowledge of human visual processing to show patterns in the data.Brave New World of Business Intelligence: opening data up to information consumers.Information is only useful when it is has been understoodExposing data, and by extension Information visualisation, is at the centre of business intelligenceStephen Hawking commented once that each equation in ‘A Brief History of Time’ (1988) would 'halve the sales', because it would make the book much more difficult to understand. The aim of a business intelligence solution is to make everything as straightforward as possible to the information consumer; if the users don't like it, then they won't use it. This would result in failure, so it is a key success criterion of the project. Text-based reports require cognitive effort to analyse the presented information.  On the other hand, in order to leverage the abilities of the human visual perception system in addition to alleviate cognitive effort, it is possible to use the principles of information visualisation in order to display data.
  • Same data, this time in a picture. Some of the detail is lost, but we do gain a better appreciation of the patterns in the data. The table and graph complement each other; not necessarily replace one another.
  • Picture worth a thousand words…
  • Effective: the viewer gets it (ease of interpretation)Accurate: sufficient for correct quantitative evaluation. Lie factor = size of visual effect/size of data effectEfficient: minimize data-ink ratio and chart-junk, show data, maximize data-ink ratio, erase non-data-ink, erase redundant data-inkAesthetics: must not offend viewer's senses (e.g. moiré patterns)Adaptable: can adjust to serve multiple needs
  • It’s about the ‘safest bet’
  • AreaMulti dimensionalHard to compareAngles
  • AreaMulti dimensionalHard to compareAngles
  • How many minutes is the blue section worth?Pie charts – bad for multivariate analysisCan’t compare between pie charts very well
  • Data taken from Princeton’s International Archive network
  • Linear versus Quadratic ChangeFlorence Nightingalerepresented the numbers of soldiers using the area, not the radius, of the circle segments
  • Brandie Stewart et al (2009)Design/methodology/approach – Participants are presented with 2D and 3D bar and pie charts in a PowerPoint presentation and are asked to extract specific information from the displays. A three (question difficulty) ×?two (graph type) ×?two (dimension) ×?two (colour) repeated measures ANOVA is conducted for both accuracy and reaction time.Findings – Overall, 2D graphs led to better comprehension, particularly when complex information was presented. Accuracy was similar for colour and black and white graphs.Practical implications – These results suggest that 2D graphs are preferable to 3D graphs, particularly when the task requires that the reader extract complex information.Originality/value – For the past several decades, diagrams have been valuable additions to textual explanations in textbooks and in the classroom to teach various concepts. With an increase in technological advancements, many authors add extraneous features to their graphs to make them more aesthetically pleasing. This paper has shown, however, that 3D rendering may negatively affect graph comprehension.
  • comics
  • small multiples many years ago to describe an arrangement of small graphs, all within eye span, which look precisely the same (including a consistent quantitative scale), except that each displays a different subset of a larger set of data.This clarity which would not have been achieved by using a single graph and making it three dimensional.Note Mexico – goes down from 1989 until 2009.Comparison
  • Projecting multivariate data onto two dimensions for displayattempting to detect and understand the unique features that the data set may contain and then to interpret them.The underlying data may not be related; the problem then becomes an effort to understand the unique features in the data set.The analyst can then interpret them.This type of analysis: principal component analysis (Chapter 2) and cluster analysisUse two interval-level variables. Fully define the variables with the axis titles. Use the chart title should identify the two variables and the cases (e.g., cities or states) If there is an implied causal relationship between the variables, place the independent variable (the one that causes the other) on the X-axis and the dependent variable (the one that may be caused by the other) on the Y-axis. ·         Scale the axes to maximize the use of the plot area for displaying the data points.·         It’s a good idea to add data labels to identify the cases.I have used blue here because the points are smaller; this way, the colour used can be determined by the visual display itself.
  • Data Visualisation can help to offer a ‘royal road’ to the numbers, if done properly.

Ssrs the good the bad the ugly Ssrs the good the bad the ugly Presentation Transcript

  • Data Visualisation using SSRS: The Good, the Bad and the Ugly twitter: @jenstirrup http://www.jenstirrup.comCopper Blue Business Intelligence Ltd March 2011 1
  • Why Data VisComputers have promised us a fountain of wisdom but delivered a flood of data(Frawley, 1992)Footer Text 4/20/2012 2
  • What is Data Visualisation?• Data Visualisation which allows the data consumer to draw their own conclusions.• Very often, the data is not static in nature, but fluid and dynamic.
  • Why not just tables?Zimbabwean inflation rates (official) sinceindependenceDate Rate Date Rate Date Rate Date Rate Date Rate Date Rate1980 7% 1981 14% 1982 15% 1983 19% 1984 10% 1985 10%1986 15% 1987 10% 1988 8% 1989 14% 1990 17% 1991 48%1992 40% 1993 20% 1994 25% 1995 28% 1996 16% 1997 20% 198.93 598.751998 48% 1999 56.9% 2000 55.22% 2001 112.1% 2002 2003 % % 231,150 132.75 585.84 1,281.1 66,212. ,888.872004 2005 2006 2007 2008 % % 1% 3% % (July)
  • Thinking with your Eyes
  • Translated into picture…
  • What makes a good visualisation?• Effective• Accurate: – Lie factor = size of visual effect/size of data effect• Efficient• Aesthetics• Adaptable
  • The Bad…and the Ugly• Pie Chart• Chartjunk• 3D vs 2DCopper Blue Consulting Ltd 4/20/2012 9
  • The Bad…and the Ugly• Pie ChartFooter Text 4/20/2012 10
  • Lost Finale: Mins Breakdown Filler Adverts Questions Answered
  • Chartjunk Example
  • Linear vs Quadratic
  • 4/20/2012 14
  • Chartjunk: unintended
  • 3D vs 2DStudies show that:2D graphs better for comprehension2D graphs were better for complexgraphs3D often considered aestheticallymore pleasing
  • Reporting StructureCopper Blue Business Intelligence Ltd 4/20/2012 17
  • Copper Blue Business Intelligence Ltd 4/20/2012 18
  • SplomsFooter Text 4/20/2012 19
  • Back to the Royal Road• Questions?Footer Text 4/20/2012 20