Effective Big Data Visualization

Effective Big Data Visualization Every Picture Tells A Story Don t It? Mark Gamble Dir Technical Marketing Actuate Corporation 1 Data Driven Summit 2014

Agenda What is data visualization? What is good? Ed Tufte principles Stephen Few principles Visualizing data Chart basics Visualization Examples BIRT Style Techniques 2 Data Driven Summit 2014

What is data visualization? Data Visualization is the art of information It is a depiction of summarized metrics, culled from various sources, combined into a single descriptive graphic. Data Visualizations are typically employed for quantitative summarization, such as infographics or dashboards While Big Data presents unique challenges for visualization, the fundamentals of good information design apply As big data becomes bigger, and more companies deal with complex datasets with dozens of variables, data visualization will become even more important. http://radar.oreilly.com/2012/02/why-data-visualization-matters.html Julie Steele Editor, Strata - O Reilly Media 4 Data Driven Summit 2014

What is good data visualization? Different things to different people.. Consider your audience How will they use the information? How statistically savvy are they? How do they consume the information? Review the expert opinions Ed Tufte Stephen Few 5 Data Driven Summit 2014

Edward Tufte 5 Grand Principles Of Data Visualization 1. Enforce Visual Comparisons o Draw conclusions faster o Use thickness, color, weight o Compare in adjacent space vs over time 2. Show Causality o Show how one thing makes another occur o Reinforce the meaning of the content o No point is conveyed without it 3. Show Multivariate Data o Show data on more than 2 dimensions o Draws the user in o Adds more usefulness to the information 6 Data Driven Summit 2014 4. Integrate All Visual Elements o Use text, images and numbers where appropriate o Don t push context to a legend or title o Don t make the user learn your system 5. Content-Driven Design o Quality data o Relevance o Integrity http://www.jonkolko.com/projectfiles/scad/iact370_05_tufteprinciples.pdf Good information design will never save poor content!

Stephen Few 7 Core Design Principles For Displaying Quantitative Information 1. Display neither more nor less than what is relevant to your message 2. Don t include visual differences in a graph that do not correspond to realistic comparison 3. Use the size and location of objects to encode quantitative values 4. Differences in values should be portrayed accurately (start from 0 ) 5. Do not connect values that are discrete, suggesting a relationship that does not exist 6. Emphasize the information that is most important to your message 7. Augment people s short-term memory by combining multiple facts into a single visual pattern Good data visualization takes the burden of effort off the brain and puts it on the eyes 7 Data Driven Summit 2014 http://www.perceptualedge.com/articles/whitepapers/visual_communication.pdf

Chart Basics: how do I best depict the data? Choose the appropriate visual for the information Tracking values over time (eg: daily sales for the past quarter): LINE CHARTS or AREA CHARTS with the time dimension on the X-axis Comparing summarized amounts across categories (eg: transactions by merchant): COLUMN or BAR CHARTS Comparing a percentage value against the whole (eg: % breakdown of total expense by division): PIE or DONUT CHARTS Displaying current performance by region/state/country/territory MAPS (color coded, sub-graphics overlay) Animated Visuals interaction increases value 9 Data Driven Summit 2014

Chart Basics: how do I best depict the data? Chart Tips When category values are too long to display in the X- axis of a column chart pivot the X-axis to vertical alignment (bar chart) On column or bar charts, show bars sorted by value ONLY when you want to convey ranking Otherwise X-axis categories will shift when displayed with different contexts On a line chart, show data point markers ONLY if you want to convey specific values Otherwise it detracts from trend depiction of a smoother line 10 Data Driven Summit 2014

Geospatial US Unemployment Level 12 Data Driven Summit 2014

Charts on Top 13 Data Driven Summit 2014

Interaction 14 Data Driven Summit 2014

Icons 15 Data Driven Summit 2014

Information Rich 16 Data Driven Summit 2014

Repetition 17 Data Driven Summit 2014

Drilldown 18 Data Driven Summit 2014

BIRT Styling Techniques Visual Styling Enhances Aesthetic Quality and Understanding 3 layers of style control in BIRT: Styles Granular aesthetic settings font-family, font-size, font-color, etc Themes Collections of Styles Following a Specific Scheme Libraries Encapsulation of BIRT components, including Themes Centralized Control of Application Look-n-Feel 20 Data Driven Summit 2014

Styles Based on Cascading Style Sheets (CSS) Options: Creating custom styles in your report design Predefined styles in your theme Custom styles in your theme Importing a CSS file into your theme Linking to an external CSS file in your theme 21 Data Driven Summit 2014

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Themes A theme is a set of styles applied to BIRT visualizations Themes can be defined at Report level Object level (table, crosstab, chart, label ) Can use default themes Can create custom themes 24 Data Driven Summit 2014

Libraries Libraries are collections of reusable components Data items (connections, data sources, parameters) Report Items Reusable report items Master pages Themes Aesthetics Provides centralized control for Themes and Styles Enables Rapid Changes Change Styles/Themes in Library Will Update Entire Application 27 Data Driven Summit 2014

Demo BIRT Style Techniques CSS Library Themes Styles 28 Data Driven Summit 2014

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