Data Visualization for Business Intelligence and Analytics A Comprehensive Overview IT 7113 Data Visualization http://idi.kennesaw.edu/it7113/ J.G. Zheng Spring 2019 This lecture notes is hosted at https://www.edocr.com/v/yqwmqeba/jgzheng/Business-Data-Visualization Overview This lecture notes provides a high level overview of data visualization primarily used in business intelligence and analytics. This overview is comprehensive to cover as many aspects as possible but keep them at a high level: What is (business) data visualization? What are the types of visualization? What are the related terms and fields? How are they similar or different? The role and value of data visualization in business intelligence and analytics (information seeking and decision making) Basic data visualization elements and forms Data visualization and IT Design, development, delivery Applications and tools Skills, jobs, and career Learning resources 2 Visualization Visualization is the process of forming a visual imagery of things in human mind What (things) can be visualized? Visible reality: person, animal, building, mountain Hidden reality: earth core, blood vessel, universe Invisible reality: wind, air, heat, electron, sound, smell, magnetic fields Abstract: data, information, idea, hierarchy, process, relationship How to visualize them? - Types of visualization forms 2D vs. 3D Static vs. motion Virtual vs. materialized Realistic vs. abstract 3 Data Visualization Data visualization is the visual and interactive exploration and graphic representation of data of any type (discrete, nominal, relational, etc.). Forms a visual imagery representation of data/information (meaning) The process of presenting (mapping) data as visual symbols and properties Utilizes a combination of visual elements (shapes) and variables like size, color, positions, etc. The general purpose of data visualization is to provide a better way of presentation and interaction; more specifically, we use data visualization for these purposes (different types of data visualization will serve different purposes): Understanding - comprehension of abstract ideas and processes * Information seeking - browsing, navigation, exploration, discovery * Data analysis and decision support * Event or operation monitoring Communication Artistic (beauty) expression and appreciation Entertaining, for fun and story telling 4 * Indicates the focus of this course A Visualization of "Data Visualization" http://prezi.com/qvhyfup5z7yz/dashboard-design-making-reports-pop/ 5 Related Terms and Fields Data presentation Information visualization (including infographic), illustration Computer graphics, reality visualization (VR, AR), scientific visualization Simulation http://setosa.io/bus/ Business data visualization 6 Data Presentation (In the field of statistics) data presentation is the method by which people summarize, organize and communicate information using a variety of tools, including tables and diagrams/charts. Extended readings on data presentation: http://www.slideshare.net/ahsanshafiq90/data-presentation-2-15572325 https://www.slideshare.net/31mikaella/presentation-analysis-and-interpretation-of-data 7 Also textual: bullet points, text style, spacing, etc. People usually don't treat text based paragraphs and tables as visualizations. But they do or can have ample visual properties. This is generally more aligned with data visualization. Information Visualization A very close field, and very often used as the synonym for, or even include, data visualization Major differences Information often is more general and can be more qualitative. Utilizes more free forms (non standard) of visual diagrams or illustrations (illustrational diagrams) Often hand-crafted instead of automatically populated from a data source. Intended for more casual use (informational) for general people. Often used in communication (journalism) and marketing https://www.interaction-design.org/literature/article/information-visualization- who-needs-it https://www.business2community.com/digital-marketing/visual-marketing- pictures-worth-60000-words-01126256 Infographics is a common form of information visualization https://visage.co/throwdown-data-visualization-vs-infographics/ http://www.jackhagley.com/What-s-the-difference-between-an-Infographic- and-a-Data-Visualisation 8 See more resource about information visualization https://www.interaction-design.org/literature/topics/information-visualization https://informationisbeautiful.net Illustration of an Idea/Concept NOT data visualization 9 More examples of information visualization can be found at https://informationisbeautiful.net Computer Graphics Computer graphics is graphics created using computers, mainly based on computing logic and algorithms. Reality visualization (Virtual Reality or Augmented Reality) is the application of computer graphics 10 Scientific Visualization "Primarily concerned with the visualization of three-dimensional phenomena (architectural, meteorological, medical, biological, etc.), where the emphasis is on realistic renderings of volumes, surfaces, illumination sources, and so forth." https://en.wikipedia.org/wiki/Scientific_visualization Physical science visualization Visualization (simulation) of reality (universe, sun, explosion, atom, climate, etc.) Mathematical model/algorithm visualization http://acko.net/blog/how-to-fold-a-julia-fractal/ 11 Business Data/Information Visualization Business is a general term to describe activities, events, and operations that make an system running (more like the term field or domain) Business includes many activities directly associated with human, like commerce, government, education, sports, charity, entertainment, etc. Or events that impact human, such as weather, earthquake, etc. Business data or information records various aspects of these activities. Main features of business data Abstract: data is not directly defining or visualizing a real world phenomenon Often quantitative Often structured or semi-structured Multidimensional Directly comprehendible by average human (in a particular "business") Business data visualization features Main purposes are information seeking, analysis, decision support, monitoring, and communication. Using simple, standard, and abstract images (symbol/chart/diagram/map) Utilizes data binding techniques to generate visualizations in an automated way Where is data visualization used in businesses? Part of a BI or analytics process especially in self-service Communication of results all kinds of reports (periodical/seasonal or real time) and presentations (e.g. PowerPoint) Presentation of results in statistical analysis, data mining or other advanced analytics. Visual analytics Operational or administrative monitoring 12 Yes Business Data Visualization Periodical reports https://myit-2019.itdashboard.gov Performance dashboards https://www.geckoboard.com/learn/dashboard-examples/ Visual data exploration and seeking https://www.productchart.com/smartphones/ https://finviz.com/map.ashx https://www.census.gov/dataviz/ Visual analytics https://www.google.com/publicdata/directory Real time monitoring https://www.nytimes.com/interactive/2018/11/06/us/elections/r esults-dashboard-live.html 13 Not Business Data Visual These examples are not really considered to be business data visualization not the focus of this class Not meaningful business data http://classes.dma.ucla.edu/Spring13/161/projects/students/david/project-5/html/?/image- gallery/ Mathematical visuals https://mathigon.org/world/Fractals https://en.wikipedia.org/wiki/Fractal Scientific visualization https://en.wikipedia.org/wiki/Scientific_visualization Reality simulation https://weather.com/weather/radar/interactive/l/USGA0028:1:US Infographics https://visual.ly/m/design-portfolio/ https://informationisbeautiful.net (not all but many are) Too much artistic (visual embellishment) http://hci.usask.ca/uploads/173-pap0297-bateman.pdf 14 Comparison of Related Visualization Fields Content Visual Forms/Tools Purpose Business data visualization Quantitative data related to business activities; metrics, key performance indicators (KPIs) Charts, diagrams dashboards Data exploration, analysis, decision making General data visualization General quantitative data Charts, diagrams dashboards Data exploration, analysis, decision making Information visualization All kinds of information, quantitative and qualitative Infographics, illustrational diagrams Information seeking, artistic illustration, casual communication, story telling Illustration Processes, structures concepts, ideas Diagram, image, graphics Making the content more vivid and engaging, easier to understand the complexity. Scientific visualization Real world object or phenomenon, mathematical functions and formulas Computer generated graphics, 3D virtual reality Recreate or simulate the real-world object or phenomenon, or visualize an algorithm effect. Simulation Calculated data based on formulas or rules Animated diagram or virtual reality Demonstrate the effect of scenarios under certain rules 15 Why Data Visualization? Visualizing is basically a human physiological and psychological capability, and plays an important role in human information behavior Greatly helps data comprehension and enhance problem solving capabilities Enable perceptual inference operations and detection of patterns (see the figure on the right) Provide a high level overview of complex data sets for quick comprehension Extract/provoke additional (implicit) perspectives and meanings Ease the cognitive load of information processing Recall or memorize data more effectively Effective communication More specifically (see examples in the following slides) Identify patterns and trends Quickly focus on area of interest or area of difference (can be an anomaly) Identify structures or relationships More comprehendible with familiar visual context 16 A picture is worth 1000 words (clicks) Source: How Data Visualization Empowers Decision Making https://community.watsonanalytics.com/wp- content/uploads/2015/04/BlueHill_HowDataVi sualizationDrivesDecisionMaking_Dec14.pdf Identify Trends and Patterns What's the difference between these two cities? Which one is Atlanta? In 10 seconds? 17 Identify Trends and Patterns Monthly average temperature Monthly average precipitation What's the difference between these two cities? Which one is Atlanta? In 10 seconds? 18 Quickly Focus on Area of Interests Which stock performed different from others? http://finviz.com/map.ashx 19 Identify Structures/Relationships Does June report to Joy? Employee Reports to Jane Jack Jessie Jane Jason Jane John Joy Joseph Joy Joy Jack June Jessie Jack Jane Joy Jessie Jason John June Joseph 20 More Comprehendible with Familiar Visual Context 21 Text (non visual) Visual Geo map is the recognizable familiar visual context Data Visualization in BI/Analytics Data visualization is an important part of data exploration and decision making. Given the power of visualization, it is only natural to apply the rich communication techniques in the field of BI and analytics. Visualization has been considered as a separate field from BI until recently, but it quickly brought the traditional business intelligence to life As organizations seek to empower nontechnical users to make datadriven decisions, they must consider the prowess of data visualization in delivering digestible insights. Visualization tools have become increasingly important to business intelligence, in which people need technology support to make sense of and analyze complex data sets and all types of information. Dashboards, reporting, end-user self- service, and advanced visualization are the top most important technologies and initiatives strategic to BI in 2018. https://www.forbes.com/sites/louiscolumb us/2018/06/08/the-state-of-business- intelligence-2018/#b2fca2878289 Data Visualization Concepts Visual elements Visual elements are the basic building blocks in a chart or diagram to visualize data items. The most fundamental and abstract elements are: point, line, surface (area), and volume (3D). These basic elements, and the more complex elements built up on them, can represent almost anything in a visualization. Visual variables (visual properties, or visual attributes) Visual variables are used to "decorate" visual elements, so that the values or categories of data items can be directly and easily perceived and understood by human. Visual variable or property is a basic feature that can represent different values of a particular dimension of data They can be used together to represent multiple dimensions of data The following six can be summarized as "SCOPeS" Shape Color Orientation Position Texture Size For details: http://www.infovis-wiki.net/index.php?title=Visual_Variables Visual forms/styles Visual form is the basic style a visualization is presented based on user needs. 23 We will cover this topic in details in module 2. Cognitive Theories and Principles Human (visual) perception and working memory Explains the cognitive visualization process in human brain https://www.interaction-design.org/literature/article/the-properties-of-human- memory-and-their-importance-for-information-visualization Pre-Attentive Processing Any visual processing of that item prior to the act of selection can be called "preattentive". [Wolfe, Treisma, 2003] Preattentive processing can help to rapidly draw the focus of attention to a target with a unique visual feature (i.e., little or no searching is required in the preattentive case). [Healey, 2005] http://www.infovis-wiki.net/index.php/Preattentive_processing Gestalt Principles of Perception Gestalt principles describes a set of ways how human perceives images and how visual information are identified and related from images. These principles have profound implication on visual design, UX/UI and interaction design, and data visualizations (charts, maps, dashboards) https://www.interaction-design.org/literature/book/the-encyclopedia-of- human-computer-interaction-2nd-ed/data-visualization-for-human- perception 24 We will cover these topics in details in module 2. Basic Visual Forms/Styles used in BI 25 Form/Style Description Typical Types and Examples Embedded visual It is embedded in, or directly on top of, texts and other forms of data presentation (table, graphic, etc.). Conditional formatting (visual cues) Inline chart (Sparkline) Block visual It is displayed as an independent visual unit and occupies a larger space. It is often a part of a report or dashboard, appearing together with other content. But sometimes it can become a standalone visual with many data points or enough complexity. Chart Illustrational diagram Map (smaller) Data table (usually with embedded visuals) Standalone visual It is a standalone application and is not mixed with other types of content or tool. Most interactions are within the visual. It may consist of a combination of different types of visuals. Dashboard Visual analysis tool (or an analytical dashboard) Map (bigger or full screen) Conditional Formatting Conditional formatting Direct formatting on text or numbers using visual properties, embedded in a pre-established presentation Example Golf http://www.masters.com/en_US/scores/ Tag cloud 26 Sparkline A sparkline is a small chart embedded in a context of words, numbers, tables, images, or other type of information. It presents the general shape of the variation in a simple and highly condensed way. http://en.wikipedia.org/wiki/Sparkline Examples http://omnipotent.net/jquery.sparkline/ http://www.klipfolio.com/blog/table-component-overview https://trumpexcel.com/sparklines/ 27 Sparkline Illustrational Diagrams Illustrational diagrams Mainly to visualize quantitative as well as qualitative data to illustrate their features, relationships, sequences, etc. http://en.wikipedia.org/wiki/Diagram https://en.wikipedia.org/wiki/Illustration Common examples used in business information visualization http://extremepresentation.com/design/7-charts/ Flow chart: http://en.wikipedia.org/wiki/Flowchart http://familydoctor.org/familydoctor/en/health-tools/search-by- symptom/cough.html Network graph: https://flowingdata.com/charttype/network-graph/ Structure diagram: http://en.wikipedia.org/wiki/Data_structure_diagram Tree diagram: http://en.wikipedia.org/wiki/Tree_structure Spatial map: https://maps.google.com/gallery/ Time line: http://vizualize.me/ More: http://datavizproject.com/# Examples of those with quantitative data Sankey diagram https://en.wikipedia.org/wiki/Sankey_diagram 28 Chart Chart is a unique combination of symbols (visual elements) with visual properties which directly represents quantitative values General types: line chart, column/bar chart, area chart, pie chart, radar/spider chart, scatter chart, bubble chart, dial or gauge chart http://en.wikipedia.org/wiki/Chart Chart vs Diagram No explicit defined difference. Diagram is considered to include chart. Chart is more abstract and focus on quantitative values 29 We will cover these topics in details in module 4 and 5. Choose a Chart Figure from http://extremepresentation.com/design/7-charts/ or http://extremepresentation.typepad.com/blog/2008/06/visualization-taxonomies.html Online chooser with templates: http://labs.juiceanalytics.com/chartchooser/ 30 Location Intelligence Location intelligence (LI) is a business intelligence (BI) tool capability that relates geographic contexts to business data. http://searchbusinessanalytics.techtarget.com/definition/location-intelligence-LI Data that involves location Geo location: country, state, city, zip, region (park, air port), road, path Contextual location: building, room, shelf, stadium, court, fields, body Abstract location: geo chart/diagram, process, network Forbes report "The Power of Place" https://www.forbes.com/forbesinsights/pitney_bowes_power_of_place/ Location intelligence (LI) can be described as the process of deriving meaningful insight from geospatial data relationships to solve a particular business problem. It involves layering multiple data sets spatially and/or chronologically, for easy reference on a map, and its applications span industries, categories and organizations. Location helps us visualize business data in familiar waystypically with maps. Unlike traditional business analytics, which tends to present results in spreadsheets, pie charts and bar graphs, maps allow businesses to see the underlying proximity relationships and trends in their data. Maps are widely recognized and understoodeven by nontechnical professionalswhich helps make the data represented more accessible and understood by those who might make use of it. Tableau reports "The Power of Where" https://www.tableau.com/learn/whitepapers/government- mapping Quickly associate data with familiar position/location added familiarity increase comprehension. Mapping lets you see the implications of your data in ways not detectable on a standard spreadsheet, linear graph or pie chart. Maps provide context that leads to better ways to prioritize, plan and execute your mission. Location Based Visual Types Geo map Visualize geo location related data directly on real world maps Data represented as points, areas, paths http://luminocity3d.org/WorldCity/ Abstract illustrated map: these are conceptually related to geo location but presented in an abstract way an illustration, rather than accurate geo locations Tile grid map: https://fivethirtyeight.com/features/where-your-state- gets-its-money/ Geo chart: https://googletrends.github.io/search-election-election- night/ Road/path map: http://fatalities.safer63and881.com/#highway Contextual map Any data relevant to the positioning in a particular context or space, e.g., building, campus, mall, stadium, a just a space (like a hitting area) etc. https://www.facilityquest.com/occupancy-utilization-studies/ We will cover these topics in details in module 6. Chart/Diagram Types Summary Andrew's version https://extremepresentation.com/design/7-charts/ Juice Analytics version (online chooser with templates) http://labs.juiceanalytics.com/chartchooser/ Ferdio version http://datavizproject.com Jorge's version https://excelcharts.com/classification-chart-types/ Charlr version http://blog.chartlr.com/post/120607313773/which-chart-type-works-best-for-your-data https://chartlr.com/chart-types Data catalog version http://www.datavizcatalogue.com More http://en.wikipedia.org/wiki/Chart http://www.amazon.com/Information-Graphics-Comprehensive-Illustrated-Reference/dp/0195135326 https://queue.acm.org/detail.cfm?id=1805128 A periodic table of visualization methods: http://www.visual-literacy.org/periodic_table/periodic_table.html 33 Infographics Information graphics or infographics are graphic visual representations of information, data or knowledge. http://en.wikipedia.org/wiki/Information_graphics Usually a mixture of text and multiple visual forms (charts, diagrams, images, tables, maps, lists, etc.) to quickly and vividly communicate complex information (multiple variables or dimensions). Example http://dailyinfographic.com/ http://www.cooldailyinfographics.com/ http://blogs.scientificamerican.com/sa-visual/2014/10/14/sa- recognized-for-great-infographics/ https://visual.ly/m/design-portfolio/ Not exactly same as data visualization http://www.jackhagley.com/What-s-the-difference-between-an- Infographic-and-a-Data-Visualisation 34 Digital Dashboard 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. Dashboard Confusion, Stephen Few, http://www.perceptualedge.com/articles/ie/dashboard_confusion.pdf A set of visualization or presentation of data views organized in a single screen/page The data is generally KPIs and shows trends, breakdowns, and comparisons against a forecast or historical data A dashboard generally contains a variety of different views of data: charts, diagrams, tables, standalone numbers, interactive controls (such a filters) Dashboard vs. report, visual analysis tool, and scorecard http://www.dashboardinsight.com/articles/digital-dashboards/fundamentals/what-is-a- dashboard.aspx The Values of Dashboard Allow decision makers to see a variety of relevant data that affects their divisions or departments Quickly understand data and respond quickly at one place; save time over running multiple reports More: http://www.bidashboard.org/benefits.html 35 We will cover these topics in details in module 7 and 9. Types/Levels of Dashboard Monitoring: Operational real time view of important indicators. Analysis/data interaction: Provides optimized UI and information seeking and navigation feature among data and metrics to support analysis. Summary/overview: As a summary high level report of operating status; may be at the top executive level (strategic) or departmental (tactical) levels. 36 Image from http://prezi.com/qvhyfup5z7yz/dashboard-design-making-reports-pop/ More about types: http://www.bidashboard.org/types.html http://www.klipfolio.com/resources/articles/operational-analytical-bi-dashboards Each of them share common attributes of dashboards (data + visualization + UI), but each of them has some different purpose, data, and design best practices. Dashboard Uses and Examples Where is it used? Public report: The IT Dashboard http://it.usaspending.gov http://www.youtube.com/watch?v=4fe39dh6xFQ Performance monitoring http://www.google.com/appsstatus https://www.google.com/analytics Election: http://elections.nytimes.com/2012/results/president Sports: http://games.idashboards.com/winter2010/?guestuser=vancouver Business: Performance dashboard Scorecard Strategy map More real examples http://www.klipfolio.com/resources/dashboard-examples/ http://www.idashboards.com/solutions/ http://dashboardsbyexample.com http://www.dashboardzone.com 37 Reports Reports A report is the presentation of detailed data arranged in defined layouts and formats Based on simple and direct queries: usually involves simple analysis and transformation of data (sorting, calculating, filtering, filtering, grouping, formatting, etc.) Traditional reports contain detailed data in a tabular format and typically display numbers and text only. Its purpose is mainly for printing (with styling) or exporting (raw data). It is geared towards people who need data rather than a direct understanding of data. Modern reports can be interactive and visual but the focus is still on detailed data. Sometimes the distinction is a bit blurred with dashboards in some practical cases. http://www.crazybikes.com/mrc/CRAZYBIKES.R00090s A report style "dashboard" (or more like a visual intensive interactive report): https://www.itdashboard.gov/drupal/summary/006 38 Visual Analysis Tools A visual analysis/exploration tool is similar to a dashboard in that it uses visualizations intensively to drive data exploration or analysis. Some consider it a kind of dashboard Some consider it a bit deferent - http://www.dashboardinsight.com/articles/digital- dashboards/fundamentals/what-is-a-dashboard.aspx Key characteristics of a visual analysis tool: The visualization is usually a single (or very few) component that occupies a big portion of the screen as the main UI component, with a large number of data points visualized. It is highly interactive and usually provides abundant settings and configurations (for adjusting factors and parameters) including filtering or sorting options. In fact, the number of setting combinations can be quite big. It is not to visual key metrics, but to visualize patterns, trends, and other complex relationships among data. It fits on one screen, but there may be scroll bars and zooming options. It is primarily used for intensive data exploration or analysis, used by data analysts and researchers. Example http://luminocity3d.org/WorldCity https://www.productchart.com https://immersion.media.mit.edu/demo 39 Scorecards A scorecard is special type of dashboard typically with a tabular visualization of measures and their respective targets with visual indicators to see how each measure is performing against their targets at a glance. Scorecards are mainly used for performance monitoring with data directly related to measure, target, status etc. Because of its uniqueness, it is viewed by some as special type of dashboard when used independently. http://www.dashboardinsight.com/articles/digital-dashboards/fundamentals/what-is-a-dashboard.aspx Key characteristics Scorecards are mainly used for performance monitoring with data directly related to measure, target, status etc. It mainly uses a tabular layout with embedded visuals like conditional formatting, sparklines (line, bar, or bullet graphs). Limited interactivity (mainly on filtering and sorting to find score items) It is commonly used in another tools like dashboards and visual analysis tools. More information http://www.dashboardinsight.com/articles/digital-dashboards/fundamentals/a-closer-look-at-scorecards- and-dashboards.aspx 40 Composition of Multiple Elements/Properties More complex visual elements (such as icons and symbols) can be built based on the basic elements and properties discussed above. Combinations of these properties can be used to represent multi-dimensional data in the same visualization. Motions and animations (such as blinking, movement, spinning, etc.) are based on some dynamic changes of these properties, and they can be used for richer meaning and grab greater attention. 41 Data Visualization and IT Modern advanced and interactive visualizations are driven by the need for technology and tool support (design, development/programming, automation, delivery, and administration). Michael Friendly offers these key points where information technology drives the modern data visualization: Highly interactive statistical computing systems have been developed and are in common use. This is compared to early command-driven systems which used compiled, batch processing. There are new methods for visual data analysis that have been implemented such as linking, brushing, selection, focusing, etc. that can be applied to interactive data models. Data with large volumes of dimensions can be better analyzed thanks to the development of tools to do this such as the grand tour, the scatterplot matrix, parallel coordinate plots, etc. There have been new techniques developed for graphing discrete, categorical data. The field of information visualization has broadened to encompass many new forms of data, data structure and indeed problem solving. The information visualization field has begun to implement understanding of the cognitive and perceptual aspects of displaying data in addition to delivering simple static visualizations which were aesthetically pleasing. could have been created manually in practice they require computing power to be manageable to develop cost-effectively. https://www.interaction-design.org/literature/article/information-visualization-a-brief-20th- and-21st-century-history 42 Data Visualization Tools Visualization products have been evolving fast, and there is increasing overlap. But they generally fall into three major categories. Standalone tools They are specifically designed to produce stunning visualizations, and can work with multiple platforms and data sources. Some of them are growing to more full stack analytics tools. Examples include Tableau, Power BI, Qlik, SpotFire, and others. They can be desktop based or cloud based (http://idashboards.com, http://www.klipfolio.com). Embedded tools Broader analytics, business intelligence, and reporting platforms that often incorporate visualization capabilities. These products can address more complex data platform needs and often provide wide-ranging capabilities but may require more training in order to exploit their full potential. In some cases, IT may need to be looped in to assist in integrating these tools with underlying data and related applications. Examples like SSRS, IBM, Oracle, MicroStrategy, SAP Crystal, and others. Visualization libraries or services These tools are offered as programming libraries or services for general applications (web, mobile, etc.). These tools can be useful when the visualization requires complete customization, substantial interactivity, or for developing a framework that allows you to reuse code. Examples include D3.js, Google Charts, dotNetCharting, Telerik, Nevron, amCharts, etc. 43 We will cover these topics in details in module 3. The Industry The data visualization market was valued at USD 4.51 billion in 2017, and is expected to reach a value of USD 7.76 billion by 2023 at a CAGR of 9.47% over the forecast period (2018- 2023). https://www.mordorintellig ence.com/industry- reports/data- visualization-applications- market-future-of-decision- making-industry 44 Magic Quadrant for Business Intelligence and Analytics Platforms February 2017 Data Visualization (Dashboard) Tools Enterprise reporting tools (usually as a part of the complete BI system) SSRS, SAP Crystal, etc. Standalone visualization tool (desktop) Tableau: http://www.tableausoftware.com/public/ Power BI QlikView, Dundas, Spotfire, SAP Lumira, etc. Cloud (web) based http://idashboards.com http://www.klipfolio.com/ Embedded tools Microsoft Excel, Visio Google Docs Spreadsheet http://www.benlcollins.com/spreadsheets/d ynamic-dashboard-in-google- spreadsheets/ Developer oriented libraries and APIs Programming library:, D3, dotNetCharting, Telerik, Nevron, amCharts, etc. Web API: Google Charts (https://developers.google.com/chart/) Casual charting tools Google Chart creators: http://dexautomation.com/googlechartgener ator.php Other free online charting tools http://www.onlinecharttool.com/ http://nces.ed.gov/nceskids/createagraph (for kids) More http://selection.datavisualization.ch https://www.g2crowd.com/categories/data- visualization http://www.creativebloq.com/design- tools/data-visualization-712402 http://www.computerworld.com/article/25068 20/business-intelligence/chart-and-image- gallery-30-free-tools-for-data-visualization- and-analysis.html https://bigdata-madesimple.com/review-of- 20-best-big-data-visualization-tools/ 45 Notes on Excel Excel is the best tool to learn and apply sound data visualization principles and best practices "Many individuals and small business users will discover that MS Excel offers much of what they need without the need." Data Visualization - HorizonWatch 2015 Trend Report http://www.slideshare.net/HorizonWatching/data-visualization-horizon- watch-2015-trend-report-client-version-28jan2015 Excel is the best tool for executive dashboard prototyping, because of its flexibility and development costs. http://www.excelcharts.com/blog/prototype-executive-dashboard-excel/ Main visualization features provided by Excel (practice these following the lab instructions) Conditional formatting Chart (Pivot Chart) Slicer (visual filter) Sparkline 46 Career and Jobs Data visualization has become a fast growing career and job, partly attributed to the rise of data science https://blog.udacity.com/2014/11/data-science- job-skills.html On the way to a data scientist https://www.datacamp.com/community/tutorials/l earn-data-science-infographic 47 https://mywebvault.wordpress.com/2017/05/18/modern- data-scientist-skill-set-marketing-distillery/ Skills in Data Visualization Dev. Most important Visualization design: charts, diagrams, etc. UI and interaction design Business domain knowledge, analysis Highly useful Programming Data models Data preparation Analytics methods Very helpful Artistic design Communication, story telling Information behavior 48 Data Visualization: Sample Real Jobs The Data Visualization Analyst will be responsible for understanding the strategic needs of the business and translating high-level objectives into the development of visual data analysis and dashboards to support the category management and product strategy teams. The candidate will need to need to understand how to create and manipulate large data sets and use various visualization tools to meet the needs of needs of their customers. To ensure adoption by the business, this position will be required to ensure the quality of each dashboard release, data refresh and adhere to a regular refresh and dashboard publishing schedule. https://www.linkedin.com/jobs2/view/12915000 Data Visualization Analyst (originally posted on LinkedIn): Responsible for the management of database analysis projects in support of business initiatives. Data visualization (DV) expertise to design, develop and implement clear, interactive and succinct visualizations by processing and analyzing large quantities of (un)structured data. Candidate should have ability to turn raw data into compelling, lively stories, enriched with powerful, clear visualizations. These visualizations would also provide end-users an ability to discover relationships within related data in fresh and innovative ways. Updates visualization items as defined by department, in accordance with system protocol and requests from relevant departments. Serves as a liaison between business stakeholders and technology resources to optimize processes and designed visualization functionality. Assists with user acceptance testing for new information dashboards and/or analytical systems. 49 Key Readings Zheng (2017) Book Chapter Data Visualization in Business Intelligence (PDF downloadable): https://www.researchgate.net/publication/321804138_Data_Visualization_for_B usiness_Intelligence Data Visualization for Human Perception (by Stephen Few): https://www.interaction-design.org/literature/book/the-encyclopedia-of-human- computer-interaction-2nd-ed/data-visualization-for-human-perception Tegarden (1999) CAIS Business Information Visualization (a bit aged but still classic): http://aisel.aisnet.org/cgi/viewcontent.cgi?article=2483&context=cais How Data Visualization Empowers Decision Making: https://community.watsonanalytics.com/wp- content/uploads/2015/04/BlueHill_HowDataVisualizationDrivesDecisionMaking_ Dec14.pdf https://www.tableau.com/learn/articles/data-visualization Friendly (2006) A Brief History of Data Visualization http://www.datavis.ca/papers/hbook.pdf 50 General Resources Influencers http://www.perceptualedge.com/ Stephen Few https://www.edwardtufte.com/tufte/ Edward Tufte https://en.wikipedia.org/wiki/Ben_Shneiderman http://alignedleft.com Scott Murray https://www.dataplusscience.com/insights.html Jeffrey Shaffer http://people.ischool.berkeley.edu/~hearst/ https://homes.cs.washington.edu/~jheer/ https://bost.ocks.org/mike/ Communities and organizations http://www.visualizing.org/ http://www.interaction-design.org/ http://flowingdata.com/ https://plus.google.com/111053008130113715119 https://plus.google.com/112388869729541404591 https://www.linkedin.com/topic/data-presentation https://www.darkhorseanalytics.com/blog/ TED videos: https://www.ted.com/playlists/56/making_sense_of _too_much_data Company resources https://www.tableau.com/learn/articles/data- visualization https://www.sas.com/en_us/insights/big-data/data- visualization.html http://blog.visual.ly/ https://www.darkhorseanalytics.com News, blog, magazines http://mashable.com/category/data-visualization/ http://searchbusinessanalytics.techtarget.com/resour ces/Data-visualization-tools https://www.interaction- design.org/literature/topics/information-visualization http://hbr.org/special-collections/insight/visualizing- data http://apandre.wordpress.com/ http://nbremer.blogspot.com/ http://understandinggraphics.com/ https://plus.google.com/photos/+AndreiPandre/albu ms/5481981245951662737?banner=pwa https://visage.co/blog/ https://informationisbeautiful.net/ http://www.storytellingwithdata.com Books Stephen Few, Show Me the Numbers, https://www.amazon.com/dp/0970601972/ "Information Dashboard Design" 2nd, by Stephen Few, 2013, http://www.amazon.com/gp/product/1938377001/ "Introduction to Information Visualization", by Riccardo Mazza, Springer, 2009, ISBN 1848002181 "Business Dashboards: A Visual Catalog for Design and Deployment", by Nils Rasmussen, et al. ,Wiley, 2009, ISBN 0470413476 http://www.amazon.com/Information-Graphics- Comprehensive-Illustrated- Reference/dp/0195135326 Designing Data Visualizations, by Julie Steele, Noah Iliinsky, O'Reilly, 2011 51