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CHAPTER 11
Data Visualization and Geographic Information Systems
C H A P T E R O U T L I N E
Case 11.1 Opening Case: Safeway and PepsiCo Apply Data Visualization to Supply Chain
11.1 Data Visualization and Learning
11.2 Enterprise Data Mashups
11.3 Digital Dashboards
11.4 Geospatial Data and Geographic Information Systems
Case 11.2 Visualization Case: Are You Ready for Football?
Case 11.3 Video Case: The Beauty of Data Visualization—Data Detective
L E A R N I N G O B J E C T I V E S
11.1 Describe how data visualization applications and interactive reports support learning and business functions.
11.2 Explain how data mashup applications streamline the process of integrating diverse data sources and information feeds to support data needs that cannot be anticipated.
11.3 Describe how companies optimize operations with the help of dashboards. Explain how enterprise dashboards are built and how they leverage real-time data and people’s natural ability to think visually.
11.4 Assess the business applications and benefits of geospatial data and geographic information systems.
IntroductionThe concept of using pictures or graphics to understand data has been around for centuries—from seventeenth century maps and graphs to the invention of the pie chart in the early 1800s. In recent years, technology has brought the art and science of data visualization to forefront, and it is changing the corporate landscape.
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Historically, data analytics was performed by statisticians, programmers, and data scien-tists who rarely interact directly with the business. However, easier-to-use data visualization, dashboard, and mashup technologies have changed this “experts-only” approach to data anal-ysis and presentation. Data analytics are being pushed out into the business by advances that make it possible for employees at most levels of the organization to analyze data in a mean-ingful way. Vendors of enterprise-level analytics are also upgrading their visualization and reporting platforms previously designed for use by the statistical experts.
In Chapter 3, you learned about big data analytics, data mining, and business intelligence (BI) and how they are being used to enhance performance, productivity, and competitive advantage in organizations around the globe. In this chapter, we expand on these topics to introduce you to the latest in data visualization, visual discovery, dashboards, mashups, and geographic information systems (GISs). We also introduce you to another important concept—geospatial data and how companies are incorporating geospatial data and GISs into their cus-tomer relationship management (CRM), supply chain management (SCM), BI, and other related enterprise activities
Several tools discussed in this chapter enable you to be self-sufficient. Drag-and-drop, automation, “show me” wizards, and easy-to-use dashboards enable you to develop your own interactive data visualization apps and dashboards. Reducing dependency on IT staff has a long history. For example, at one time, managers did not analyze data with spreadsheets, but now Excel expertise is expected. Vendors offer academic alliances to enable universities to teach their software in MBA and undergraduate business courses. Tableau Desktop, QlikView, TIBCO Spotfire, and IBM’s SPSS Analytic Catalyst enable business users to perform the kind of advanced analysis that could only have been performed by expert users of statistical software a few years ago.
Geospatial data is data that has an explicitly geographic component, ranging from vector and raster data to tabular data with site locations.
Case 11.1 Opening Case
Safeway and PepsiCo Collaborate to Reduce Stock Outages using Data VisualizationIf there’s one activity that is central to retail operations, it’s inventory management. Striking just the right balance between enough and not too much stock puzzles even those retailers who are regarded as inven-tory management experts. So, when PepsiCo suggested to Safeway that they try using data visualization software to improve forecasting and inventory management, Safeway leaders jumped at the chance!
Enhancing Supply Chain VisibilityIn an effort to improve awareness and sharing of POS data and data about product orders, inventory levels, demand forecasts, transpor-tation, and logistics, Safeway implemented data-sharing programs with PepsiCo and other key vendors using data visualization tech-niques (Figure 11.1 and Table 11.1). This type of improved data vis-ibility can result in increased sales and millions of dollars in reduced
costs along the entire supply chain—from raw material to delivery to end customer.
Safeway’s Data Visibility program was already forward thinking, so when they partnered with PepsiCo’s 360¤ Retail execution program, Safeway’s teams were equipped to improve an already lean supply chain. But to further improve their supply chain, Safeway needed an altogether different way to view the data. So, when Deloitte Consulting offered to partner with PepsiCo and Safeway to provide an effective way to inter-pret massive amounts of data at its Highly Immersive Visual Environment (HIVE), they were very interested.
Excel-based analyticsIn the past, when Safeway wanted answers about stockouts, managers used spreadsheets to gather and compile inventory data and see how stockouts trended across the company. With spreadsheets, managers could discover general trends over time, but they could not identify trends across a specific brand or universal product code (UPC). Trends
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PepsiCo worked with majorcustomers to improve demandforecasts in order to minimizeinventory on-hand.
Deloitte Consulting partnered withPepsiCo and Safeway to help themvisually analyze POS data at theDeloitte Analytics HIVE, short forHighly Immersive VisualEnvironment.
PepsiCo and Safeway
The goal of Safeway’s DataVisibility program is to improvesupply chain visibility with keyvendors, such as PepsiCo.
FIGURE 11.1 Deloitte Consulting partnered with PepsiCo and Safeway to help them analyze massive amounts of point-of-sale (POS) data at its state-of-the-art visualization center called HIVE.
TA B L E 1 1 . 1 Opening Case Overview
Business Safeway, headquartered in Pleasanton, CA. has 197,000 employees and 1,368 stores in the United States and Canada. Safeway, Inc., reported revenue of $36.3 billion in 2015.PepsiCo, Headquartered in Purchase, NY. has 263,000 employees across operations in over 200 countries and territories in Europe, Sub-Saharan Africa; in Asia, Middle East, and North Africa. PepsiCo reported a net revenue of $63 billion in 2015.
Products Lines PepsiCo—food, snacks and beveragesSafeway—food and drug retailers
Business challenges Inventory management is critical in retail operations—and a challenge throughout the supply chain.
Digital Technology HIVE—a physical environment where people can examine the latest analytics approaches themselves using their own data offered by Deloitte Consulting
Taglines PepsiCo—“You Got the Right One Baby”Safeway—“Ingredients for Life”
about each brand required more data than could be represented in rows and columns of a spreadsheet. These spreadsheet limitations ulti-mately led the company to try data visualization. To initialize the pro-ject, representatives from Safeway and PepsiCo traveled to Deloitte’s HIVE in Washington, DC, for a day-long design session to analyze many terabytes of data.
HIVEDeloitte’s HIVE is a research lab that measures and studies the inter-actions between business analytics technologies and real-world data. The applications used at the HIVE to develop real-world business solu-tions are translated into portfolios that are intuitive to understand. Deloitte hosts business leaders who want to understand business analytics better in sessions tailored to address their specific business
challenges (Curtis, 2013). At the HIVE, executives get help with analytics tools using their own data.
The HIVE gathers together a wide range of the latest analytics tech-nologies from all over the world. In a very short amount of time, execu-tives can learn what might otherwise have taken months of meetings, demonstrations, and business pitches. You can find out more about the HIVE in the video “Deloitte Analytics HIVE”.
Data Visualization at the HIVEPepsiCo and Safeway participants collaborated to understand how to reduce the “number of days of supply” from their supply chain while maintaining service levels—a project that would save PepsiCo and Safeway millions of dollars each year! During their HIVE session, they built data visualizations to explore questions about stockouts.
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11.1 Data Visualization and LearningData visualization harnesses the power of data analytics and adds a visual display to capital-ize on the way our brains work. You’ve probably heard the saying “A picture is worth a thousand words”—interactive displays, charts with drill down capability, and geospatial data analysis do just that and are some of the many ways companies can present data to enhance decision-making. For example, maps can tell a much more compelling story than words or numbers, as shown in Figure 11.2, by effective use of visual cues. Organizational decision-makers rely on visual cues to grasp and process huge amounts of information.
Visualizing data can save a business money, help communicate important points, and hold customer attention. Data visualization is important because of the way the human brain processes information. Using pie charts, histograms, or bar graphs to visualize large amounts of complex data is much easier than poring over spreadsheets or reports. Data visualization is a quick, easy way to convey concepts in a universal manner—and you can experiment with dif-ferent scenarios by making slight adjustments.
Data visualization software can be extremely powerful and complex, similarly to Deloitte’s HIVE platform. At the other continuum are tools with simple, point-and-click interfaces that do not require any particular coding knowledge or significant training. Most non-data-scientist-friendly tools have interactive elements and can pull data from Google
Data visualization is the presentation of data in a graphical format to make it easier for decision-makers to grasp difficult concepts or identify new patterns in the data.
Drill down is searching for something on a computer moving from general information to more detailed information by focusing on something of interest, for example, quarterly sales—monthly sales—daily sales.
The data included brands, UPC barcodes, costs, districts, store numbers, out-of-stock scans, and out-of-stock reason codes. After Safeway and PepsiCo decided on the visualization technique that best represented their supply chain, they designed three processes to operationalize it. The three processes they chose to design were as follows:
1. How to feed the huge data sets into the visualization software2. The best ways to display the data visually3. How to gather feedback
Within 40 days after their session at HIVE, PepsiCo and Safeway were able to implement their initial data visualization with dash-boards and drill-down capabilities, then spent another 20 days refin-ing it. Employing these data visualization techniques led to greatly improved performance and reduced the frequency of stockouts at Safeway. In some areas, managers were able to increase accu-racy by 35%!
What PepsiCo and Safeway Learned from Data Visualization and DashboardsSafeway identified the stores experiencing the most stockouts and their root causes. For example, it learned a disproportionate number of stockouts were occurring at a store on Catalina Island. The store is in a resort area where the tourist traffic causes uneven demand. Safeway adjusted its supply chain strategy to address uneven demand patterns.
Safeway also discovered that they were sending multiple and con-flicting forecasts to their vendors from various departments. Safeway changed the way the company creates and communicates forecasts with its suppliers.
Two significant operational improvements at Safeway from discov-eries made through data visualization are as follows:
1. Improved forecast accuracy by 35%2. Reduced on-hand warehouse inventory, which cut inventory
carrying costs significantly
PepsiCo also benefited because now it has incredible, near real-time access to the movement of every PepsiCo item, at every Safeway store, every day. Moreover, Pepsi recognizes that communicating data in an effective manner is important as Generation Z is increasingly becom-ing a large proportion of the customer base and workforce. The new players in the workforce need visuals that abbreviate information but still provide thorough analysis to make quicker decisions. Pepsi’s experi-ence at Deloitte have allowed it to develop a mobile app for cross-team collaboration and data publication, derive consistent information from customer surveys, and more accurately segment and attract different consumer markets.
Questions1. What is a potential benefit of supply chain visibility?2. What was the limitation of Excel-based data analytics at Safeway?3. What makes Deloitte’s HIVE unique in its approach to data analysis?4. What steps did Safeway and PepsiCo undertake to arrive at their
data visualization solution?
5. What were the two operational improvements at Safeway? 6. Name one way in which PepsiCo benefited from the partnership
with Safeway?
Sources: Compiled from Deloitte (2016), Pathak (2015), pepsico.com (2017), safeway.com/ShopStores/Our-Story.page (2017).
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Docs, Excel spreadsheets, Access databases, and other sources that most business people work with already. Some useful business applications for data visualization include the following:
• Identifying areas that need attention or improvement• Clarifying which factors influence customer behavior• Helping understand which products to place where• Predicting sales volumes
First, we’ll explore different technologies that fall into the data analytics category, as shown in Figure 11.3. Vendor packages usually offer tools in more than one category. In general, reporting tools generate BI that shows what has already happened in a business. Analytical tools show what might or could happen in the future. Later sections discuss information delivery and data integration.
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FIGURE 11.2 U.S. Census Bureau map shows easily identifiable changes in county population density. Different colors are used to indicate areas that gained and lost population. Intensity of color indicates extent of gain/loss.
Information Delivery Data IntegrationData Analytics
• Data visualization• Data discovery• Geospatial & GIS
• Dashboards• Interactive reports
• Data mashups• GIS
FIGURE 11.3 Tools and technologies in this chapter fall into three related categories.
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Learning, Exploration, and Discovery with VisualizationData visualization enables learning that is the basis for continuous improvement. When com-panies, political parties, sports teams, or fund-raising agencies invest in marketing programs, campaigns, promotions, special events, or other projects, they use visualization to learn some-thing from them. Visualization is also used as a data explorer and data discovery tool. Com-panies, such as Safeway and PepsiCo, are discovering new relationships and learning how to improve performance using data visualization in all types of industries and governmental agen-cies. Enterprise visualization apps for Androids, Apple iPads, and Surface tablets are replacing static business reports with real-time data, analytics, and interactive reporting tools.
Examples of Visuals Examples of visualizations include dials, charts, graphs, time-lines, geospatial maps, and heat maps. The tricolor heat map in Figure 11.4 instantly alerts the viewer to critical areas most in need of attention. Visual displays make it easier for individ-uals to understand data and identify patterns that offer answers to business questions such as “Which product lines have the highest and lowest profit margins in each region?” Interactivity and drill-down capabilities are standard features that make visualization even more valuable. Two other types of heat maps, created in Tableau Desktop, are shown in Figure 11.5; both heat maps are based on the same data set. Notice that the way in which the data are visually displayed depends on what you want to learn or convey.
Human expertise is an essential component of data visualization (see Figure 11.6). A common mistake organizations make is to invest in the analytics foundation—tools, quality data, data integration, touch screens—but overlook the most crucial component, which is the users’ ability to interpret the visual reports and analyze them correctly.
Data Discovery Market Separates from the BI MarketAccording to Gartner Research, the data analytics market has split into two segments: the tradi-tional BI market and the newer data discovery market. Data discovery software had previously been viewed as a supplement to traditional BI platforms. Now it is a stand-alone alternative to BI. This split occurred because today’s data discovery technologies provide greater data explo-ration and ease of use to help users find answers to “why” and “what if” questions through self-service analytic apps. The split is another example of pushing analytics onto the computers of business workers. IT at Work 11.1 describes the trend at IBM.
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FIGURE 11.4 This heat map uses three colors to convey information at a glance. The heat map is like a spreadsheet whose cells are formatted with colors instead of numbers.
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FIGURE 11.5 These heat maps represent the same data set using different colors (usually red and green) and color intensity to show the profitability of three product categories and their subcategories. In (a), data labels show detailed profit, while in (b), the area of each segment is used to make comparisons.
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Analytics/Visualization Vendors Respond to Demand Smaller data visu-alization vendors are competing head-on with BI megavendors IBM, Oracle, and SAS. For example, vendors DOMO, QlikView, Birst, Tableau, Sisense, and others are adding enterprise features with each new release. SAS is one of the leaders in the data visualization space. SAS® Visual Analytics uses intelligent autocharting to help business analysts and nontechnical users create the best possible visual based on the data that is selected. The visualizations make it easy to see patterns and trends and identify opportunities for further analysis. The SAS® LASR™ Analytic Server feature executes and accelerates analytic computations through in-memory processing. The combination of high-performance analytics and an easy-to-use data explora-tion interface enables different types of users to create and interact with graphs and charts to better understand and derive more value from their data faster than ever.
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FIGURE 11.6 Data visualization, human expertise, and high-quality data are needed to obtain actionable information.
IT at Work 11.1
IBM Tackles Big Data DiscoveryAs one of the world’s leading technologies corporations, IBM con-sistently takes advantage of opportunities to increase its market share in the computing and data analytics realm. In addition to hosting data storage platforms, IBM produces ways for customers to analyze data more effectively. Its most recent development is a service package of application programming interfaces (APIs) called the Watson Discovery Service. Watson is intended to decrease the amount of time analysts have to spend organizing and cleaning data and allow them to focus on making data-driven decisions.
The most prevalent issue in data analytics is the struggle to standardize and organize data in a way that makes information usable. Steve Lohr of the New York Times claims that analysts spend 80% of their time cleaning and organizing data for use (Lohr, 2014). The Watson Discovery Service solves this problem by standardizing
and categorizing data and making it available for query by the user. The most impressive aspect of the new service is its ability to accu-rately analyze text sources on a “massive scale” (Forrest, 2016). This allows employees of any level to gather the most important information from numerous sources without having to manually research each source individually.
IT at Work Questions1. How is IBM’s approach to big data unique?2. Why is a data organization service so vital to data analysis?3. What makes the Watson Discovery Service attractive to
companies?4. Do you think the service will make data analysis more
accurate?
Sources: Lohr (2014) and Forrest (2016).
Data Visualization and Learning 339
Others, such as Qlik, are integrating inference engines to replace the query-based approach, which divorces data from its context. Using an inference engine, users can input as much information as they have, and the software not only will search for the information provided but also will make associations with all other data that is related to the information provided.
These vendors continue to focus on business users of all levels and backgrounds. For example, Jeff Strauss, BI architect at Allstate Insurance Company, explained that Allstate invested in Tableau data discovery tools, so users throughout the organization could do their own analysis rather than rely on the IT department. Tableau has built a large following with its easy-to-access dashboards.
Data Discovery Offers Speed and Flexibility Data discovery is expected to take on a greater role in corporate decision making. Companies are investing in the latest data dis-covery solutions largely because of their speed and flexibility. Experts and novices can collect data quickly from disparate sources and then explore the data set with easy-to-use interactive visualizations and search interfaces (Figure 11.7). Drill-down paths are not predefined, which gives users more flexibility in how they view detailed data.
FIGURE 11.7 Data discovery tools allow users to interact with multiple corporate data sources.
A powerful feature of data discovery systems is their ability to integrate data from multiple data stores and identify data types and roles. See Tech Note 11.1. While data are being loaded into the program, the software automatically extracts and organizes them by data type. Soft-ware may also extract and organize terms from unstructured content, such as texts, e-mail, and PDFs, and create tag clouds. Figure 11.8 shows an example of a Word cloud that give users a quick way to evaluate the most aspects of SCM and start to make discoveries.
Big Data Visualization Challenges The speed, size, and diversity of big data brings new challenges to visualization. One challenge is how to display the results of data discovery in a meaningful way that is not overwhelming. For example, you may need to collapse and con-dense the results to display graphs and charts in a way that decision makers are accustomed to viewing. Results may also need to be available quickly on mobile devices, and users may want to be able to easily explore the data on their own in real time.
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Tech Note 11.1
Understanding Data Types and RolesData types and roles are fundamental components that affect how visualizations behave. Each field in any data source has an associ-ated data type. For example, a field that contains customer names has a string (text) data type, and a field that contains price informa-tion usually has a numeric data type. To visualize data QlikView, Tableau—or in any analytics or BI tool, for that matter—you need to understand dimensions and measures.
• Dimensions Dimensions contain discrete or categorical data, such as a region (e.g., Northeast, Southwest), product category, product subcategory, product name, supplier, size,
date, and zip code. Dimensions often become labels in the data visualization.
• Measures A measure is a calculation based on numeric data, such as profit, margin, quantity sold, speed, and miles. The calculation always returns one single value that summarizes all relevant records. The calculation is called an aggregation. As in spreadsheets, there are several aggregation functions: Sum(), Count(), Average(), Min(), Max(), and so on. Key performance indicators (KPIs) of interest might include monthly revenue, number of orders, quantity on hand, and total cost. A measure is always based on an aggregation.
Another issue associated with big data is the speed within which traditional architec-tures and software can process the data. If the data are not processed in a timely manner, the data may not be accurate or useful, for example, stock market data. For example, IBM SPSS integrates three visualization tools to handle big data—Netezza, InfoSphere BigInsights, and InfoSphere Streams—to provide comprehensive analytics capabilities in the big data platform. Netezza is a high-performance data warehouse whose data can be used for model building, scoring, and model refresh; InfoSphere BigInsights is an enterprise-ready distribution of Hadoop.
How Is Data Visualization Used in Business?The ultimate goal of data analytics is to drive profits, and often that depends on learning how to manage assets, such as inventory, or engage customers in a smarter way. Collecting data is relatively easy. Making sense of that data is not. Here are examples of how companies and/or entire industries are using data visualization and interactivity to improve decision speed and performance often with mobile displays.
The latest data visualization software addresses issues associated with processing big data by speeding up data discovery and returns the visualization within an appropriate time-frame, in an easy-to-understand format. BI and data visualization vendors are working to assist business analysts and nontechnical users in determining how best to display these massive amounts of data.
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Quick Detection and Decisions in Stock Markets Wall Street firms, traders, wealth managers, risk analysts, and regulators rely on their ability to process and capitalize on market anomalies in real time. Because of the demanding pace of their decisions, capital market professionals use visualization for risk analysis, pretrade and posttrade checks, compli-ance monitoring, fraud detection, client profitability analysis, research and sales, and portfolio performance. Vendor Aqumin provides real-time visual interpretation solutions for the finan-cial services industry. Aqumin’s OptionVision enables traders, risk managers, and market par-ticipants to spot opportunities, risk, and market changes. AlphaVision for Excel enables visual interpretation capabilities directly within the Microsoft Excel platform, and AlphaVision for Bloomberg is developed for professional portfolio managers, traders, and risk analysts and is connected directly to the Bloomberg Terminal to leverage data provided by Bloomberg.
The Chicago Board Options Exchange (CBOE), Gain Capital, JP Morgan, hedge funds, and other asset management firms not only need data visualization but their executives and inves-tors expect the quality and excitement of visuals to make sense of dry financial data.
Improving the HR Function ADP Corporation is one of the largest payroll service pro-viders in the world, with data on 33 million workers. When payroll processing company ADP rolled out data visualizations with predictive analytics to improve its human resource (HR) function, it was surprised by what it found. After organizing the information and funneling it through an analysis program, the HR department found that ADP would soon face a serious retirement problem. To mitigate its foreseeable future talent gaps, ADP constructed new training programs to prepare the next generation of workers.
Prompt Disaster Response by the Insurance Industry The effectiveness of an insurer’s response to a devastating hurricane or other catastrophic event depends on its ability to combine large amounts of data to fully understand the impact. Leading insurers are using Web-based data visualization and analysis technologies to better manage their responses to major disasters. In the days and weeks after a disaster, insurers face analysis and report-ing bottlenecks. Analysts capable of creating maps and reports work frantically to respond to requests for information. Because new data continue being generated even after the event, the data have a short life span and reports need to be regenerated and redistributed.
For example, when an earthquake occurs, workers throughout an insurance company access a Web-based (cloud) data app to visualize and analyze the impact. Users quickly deter-mine which properties were subject to specific shake intensities and can visually build analyses on their own, rather than waiting for a report.
Data Visualization ToolsA number of vendors offer data visualization software. The following list describes a few of these. Many of these vendors offer a free trial of their software on the websites.
• SAS Visual Catalyst has an intelligent autocharting feature that automatically presents the most appropriate visualization of a specified data set based on the amount and type of data being analyzed. By building hierarchies “on the fly,” interactively exploring data, and displaying data in different ways to answer specific questions or solve new problems, these new data visualization products relieve the user of constantly having to rely on assistance from the IT department when they want to change the ways in which the data is displayed. For example, if you have a billion rows of data, it would be impossible to see so many data points on a scatter plot. However, a box plot would convey the information that you need.
• Birst combines capability, scale, and data governance that IT needs with the agility, speed, and usability of consumer-grade desktop tools. Birst’s adaptive user experience offers users a wide range of self-service, data analysis, and presentation options, and its cloud architecture allows users to instantly share findings and data across its supply chain.
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• QlikView distinguishes itself from other BI tools through its unique inference engine that automatically maintains data associations. The inference engine works much the same as the human brain, in that when it “thinks” of a data set, it is reminded of all things related to it. Qlikview also offers a simple, Google-like search that works in an associative manner, producing results for the phrase and also for things commonly related to the phrase. For example, if a user wants contact information for a salesperson in an organization, and only knows the product that the salesperson specializes in but didn’t know the person’s name or the company, Qlikview could produce the desired results.
• IBM SPSS Analytic Catalyst has made sophisticated analytics accessible. Analytic Cat-alyst enables business users to conduct the kind of advanced analysis that had been designed for experts in statistical software. The software fast tracks analytics by identi-fying key drivers, selecting an appropriate model, testing it, and then explaining the results in plain English. See the YouTube video titled “IBM SPSS Analytic Catalyst” for an over-view. The tool condenses the analytic process into three steps: data upload, selection of the target variable (the dependent variable or outcome variable), and data exploration. Once the data are uploaded, the system selects target variables and automatically cor-relates and associates the data. Based on characteristics of the data, Analytic Catalyst chooses the appropriate method and returns summary data rather than statistical data. On the initial screen, it communicates the so-called top insights in plain text and presents visuals, such as a decision tree in a churn analysis. Once the user has absorbed the top-level information, he or she can drill down into top key drivers. This enables users to see interactivity between attributes.
• IBM Watson Analytics is a cloud-based data visualization tool that guides data explora-tion, automates predictive analytics, and enables effortless creation of dashboards and infographics.
• Tableau is one of the easier data discovery tools to implement, requiring just basic database information to connect it to the target data sources. With a new in-memory database engine, such tools are developing the power to perform big data analytics. Despite data visualization advancements, data integration between data sources can still be very challenging.
• Roambi Analytics is a leading mobile reporting and data visualization app designed for iPads and iPhones. The app can take data from most sources, including Box, Google Docs, spreadsheets, BI systems, databases, and Salesforce.com, and transform them into inter-active data visualizations. Roambi has a worldwide customer base of Global 500 companies and small and medium businesses across industries, including telecommunications, bio-technology, pharmaceuticals, consumer technology, and packaged goods.
Questions
1. How does data visualization contribute to learning?2. How do heat maps and tag clouds convey information?3. Why are data visualization and discovery usage increasing?4. Give two examples of data visualization for performance management.
11.2 Enterprise Data MashupsEnterprise data mashups combine business data and applications from multiple sources—typically a mix of internal data and applications with externally sourced data, SaaS (software as a service) and Web content—to create an integrated experience. Mashups, in general, became popular because of social and mobile technology. The ability of enterprise mashups to quickly and easily consolidate data and functionality that is normally spread across several
Enterprise data mashup the combination of data from various business systems and external sources without relying on the middle step of ETL (extract, transform, and load) into a data warehouse or help from IT.
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For organizations, mashup apps decrease IT implementation costs over traditional, custom software development (discussed in Chapter 12) and significantly simplify business workflows—both increase the ROI (return on investment) of mashup implementations.
Point-and-click dashboard building is a common feature in data mashups. These mashup technologies provide visually rich and secure enterprise apps created from live data. They provide the flexibility to combine data from any enterprise app and the cloud regardless of its location. Users can build apps and dashboards that can be displayed on the Web and mobile devices.
Mashup ArchitectureTechnically, a data mashup is a technique for building applications that combine data from multiple sources to create an integrated experience. As techniques for creating mashups became easier, companies started using them to build enterprise mashups that supported their business models. Tech-savvy managers realize that they can use mashup apps with their exist-ing data and external services to provide new and interesting views on the data.
Figure 11.9 shows the general architecture of an enterprise mashup app. Data from oper-ational data stores, business systems, external data (economic data, suppliers; information, competitors’ activities), and real-time news feeds are integrated to generate an enterprise mashup.
applications, onto a single Web page or mobile device screen, offers real business opportuni-ties for companies of all shapes and sizes around the world.
Enterprises use mashups as quick, cost-effective solutions to a range of issues. Because mashups use preexisting technology, they do not require a huge investment and can be devel-oped in hours rather than days or weeks.
Data mashups are becoming an increasingly important tool for businesses of all sizes by allowing users to gain new insights and spot trends within data. While combining disparate data sources is common for a data mashup, even if there is only a single data source, a mashup can be made by combining data in a way that is not anticipated. End users and analysts who rely on dashboards and drill-down capabilities benefit from greater access to data, but the mashups remain behind the scene and invisible. Interactive dashboards and drillable reports can be rapidly built based on mashed-up data. Tech Note 11.2 discusses dashboard software. Heat maps and tree maps can be created as data visualizations in mashups.
Tech Note 11.2
Adaptive Discovery Dashboard Software
Software vendor Adaptive Insights offers Adaptive Discovery, next-generation finance, and operations software built for the cloud. The software is widely used by businesses, nonprofits, government, and universities. Several users are Boston Scientific, Goodwill, Arizona Cardinals, Coca-Cola, Blue Cross/Blue Shield, AAA, Mayo Clinic, and DHL.
The Adaptive Suite consists of Budgeting and Forecasting that can increase financial planning and analysis productivity by more than 705: faster Financial Reporting that allows management to slice and dice financial data and drill down into details with self-service reporting on the Web or using Microsoft Office, and dash-boards and analysis tools that track business metrics and KPIs faster and tell a story with the data.
Hortonworks, an open-source data company, uses Adaptive Planning to track new hires and prospects. Dan Bradford, Hor-tonworks’ VP of Finance, noted that when using it “The ability to change a headcount assumption and have it globally run through our entire business model to see the impact on payroll taxes or per-sonnel allocations is instantaneous.”
Hortonworks built its business on innovation, so it sought a financial management solution that shared the same mindset. That’s why it turned to Adaptive Planning. With the click of a but-ton, a user could drill down into KPIs and forecast the impact of employee growth. The visibility elevated financial management beyond just tracking labor and managing expenses. This newly gained proficiency with data visualization gave Hortonworks a competitive edge in a landscape of continuous innovation in the open-source data market.
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Why Do Business Users Need Data Mashup Technology?Business users have a hard enough time identifying their current data needs. It is not realistic to expect them also to consider all the new sources of data that might be made available to them and the analyses they might do if they had access to that data. With traditional BI and data warehousing systems, data sources have to be identified, and some understanding of data requirements and data models is needed.
Realizing that there will always be data needs that cannot be anticipated, the question is whether IT should be in the middle of supporting those requests? Providing business users with self-service enables them to meet their needs more quickly. They also have the opportunity to explore and experiment.
Enterprise mashups improve operational efficiency, optimize the sales pipeline, enhance customer satisfaction, and drive profitability. Within government, mashups have positively impacted strategic areas such as citizen engagement and satisfaction, financial transparency, project oversight, regulatory compliance, and legislated reporting. A summary of enterprise mashup benefits is given in Table 11.2.
Enterprisemashup app
Enterprise mashup
Externaldata
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FIGURE 11.9 Architecture of enterprise mashup application.
TA B L E 1 1 . 2 Enterprise Mashup Benefits
• Dramatically reduces time and effort needed to combine disparate data sources.• Users can define their own data mashups by combining fields from different data sources that were
not previously modeled.• Users can import external data sources, e.g., spreadsheets and competitor data, to create new
dashboards.• Enables the building of complex queries by nonexperts with a drag-and-drop query building tool.• Enables agile BI because new data sources can be added to a BI system quickly via direct links to
operational data sources, bypassing the need to load them to a data warehouse.• Provides a mechanism to easily customize and share knowledge throughout the company.
Enterprise Mashup TechnologyMashup technology leverages investments in both BI tools and interactive technologies. BI systems are very good at filtering and aggregating huge data volumes into information. With mashup technology, for example, users can filter down the data based on their needs so that only the information needed is provided by the available data services. Tech Note 11.3 describes mashup self-service.
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Questions
1. Sketch or describe the architecture of an enterprise mashup application. 2. What is an enterprise data mashup?3. What are the functions and uses of enterprise mashups?4. Explain why business workers may need data mashup technology.5. What are the three benefits of mashup technology to the organization?
11.3 Digital DashboardsA digital dashboard provides in-depth business analysis while providing a real-time snap-shot of productivity. The digital dashboard emerged in the 1970s from the different report formats produced by decision support systems. As more and more companies moved to the Web some 20 years later, digital dashboard systems were developed to combine data reporting and facilitate smooth business operations and decisions. When done well, a digital dashboard is a tool that helps an organization efficiently develop analytical goals and strategies.
Digital dashboards pull data from disparate data sources and feeds to report KPIs and operational or strategic information on intuitive dashboards and interactive displays (Figure 11.10).
Table 11.3 lists typical metrics displayed on dashboards by function. An executive dashboard displays a company’s performance metrics, which are automatically updated in real time (every 15 minutes) based on custom programming and connectivity with existing business systems. Dashboards improve the information synthesis process by bringing in mul-tiple, disparate data feeds and sources, extracting features of interest, and manipulating the data, so the information is in a more accessible format. Users no longer need to log into mul-tiple applications to see how the business is performing.
Digital dashboard is an electronic interface used to acquire and consolidate data across an organization.
Tech Note 11.3
Mashup Self-ServiceMany BI systems are designed by the IT department and based on inflexible data sources. The result is a bottleneck of end-user change requests as business needs and data sources change. The solution is self-service mashup capabilities.
Using data mashup apps, nontechnical users can easily and quickly access, integrate, and display BI data from a variety of operational data sources, including those that are not integrated into the existing data warehouse, without having to understand the intricacies of the underlying data infrastructures or schemas.
In an enterprise environment, mashups can be used to solve a wide variety of business problems and day-to-day situations. Examples of these types of mashups are as follows:
1. Customer A customer data mashup that provides a quick view of customer data for a salesperson in preparation for
a customer site visit. Data can be pulled from internal data stores and Web sources, such as contact information, links to related websites, recent customer orders, lists of critical situ-ations, and more.
2. Logistics A logistics mashup that displays inventory for a group of department stores based on specific criteria. For example, you can mash current storm information onto a map of store locations and then wire the map to inventory data to show which stores located in the path of storms are low on generators.
3. Human resource An HR mashup that provides a quick glance at employee data such as profiles, salary, ratings, ben-efits status, and activities. Data can be filtered to show custom views, for example, products whose average quarterly sales are lower than last quarter.
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FIGURE 11.10 Dashboards pull data from disparate data sources and feeds, manipulate the data, and display the metrics.
TA B L E 1 1 . 3 Metrics Displayed on Dashboards by Function
Dashboard Type MetricsFinancial performance • Net income
• Cash balance, actual vs. expected• Profit, current month projection• Changes in A/R and A/P
E-commerce • Daily website visitors by traffic source• Trend of mobile vs. tablet traffic• Location where visitors are located• Top referring websites• Top keywords referring traffic• Revenue per website visitor
Revenue • Sales per day per channel• How revenue is trending• Days with the strongest sales, weakest sales• Products selling the best, worst
Sales team • Sales by lead source; which leads are most and least effective• Number of leads and proposals per salesperson• Proposal close percentage• Salesperson closing percentages• Where in the conversion funnel customers are being lost. Conversion funnels are paths
that prospective customers take before they become paying clients
Advertising • Number of leads generated by advertising; which advertising is most and least effective• Cost per lead, by advertising source• Advertising expense, as a percent of sales• Which advertising sources directly lead to sales
Order fulfillment • Number of products manufactured, reworked• On-time completion percent• Changes in inventory levels• Percent of on-time delivery per week, month
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Components of dashboards are as follows:
• Design The visualization techniques and descriptive captions to convey information so that they are correctly understood. Infographics are widely used because they convey information in interesting and informative designs.
• Performance metrics KPIs and other real-time content displayed on the dashboard. All dashboard data should reflect the current value of each metric.
• API APIs connect disparate data sources and feeds to display on the dashboard. The alternative is for users or IT to manually enter data to the dashboard. Dashboards created in this manner tend to fail because of the risk of incomplete, outdated, or wrong data, which users learn not to trust.
• Access Preferred access is via a secure Web browser from a mobile device.
Dashboards are Real TimeDashboards are often mistakenly thought of as reports consisting of various gauges, charts, and dials, but the purpose of business dashboards is much more specific and directed. The purpose of dashboards is to give users a clear view of the current state of KPIs, real-time alerts, and other metrics about operations. Dashboard design is a critical factor because business users need to be able to understand the significance of the dashboard information at a glance and have the capability to drill down to one or more levels of detail. Having real time, or near real time, data is essential to keep users aware of any meaningful changes in the metrics as they occur and to provide information for making decisions in real time. Users can take corrective actions promptly.
It’s easy to see in Figure 11.11 how color-coded displays can quickly inform the user of the status of KPIs.
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FIGURE 11.11 Dashboards are designed to meet the information needs of their users.
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How Operational and Strategic Dashboards WorkDashboards are custom programmed to automatically and securely pull, analyze, and display data from enterprise systems, cloud apps, data feeds, and external sources. They work by con-necting to business systems, such as accounting software, ERP, CRM, SCM, e-mail systems, web-site analytics programs, and project management software via APIs. IT at Work 11.2 describes dashboards in action at Hartford Hospital. Tech Note 11.4 lists vendors that offer free trials of dashboard software.
Tech Note 11.4
Free Trial DashboardsA few vendors that offer free trials to build your own dashboards are as follows:
• Dundas• GrowThink
• MicroStrategy• SAP Crystal Dashboard Design• Sisense
IT at Work 11.2
VA Employs Digital Data DashboardsIn December, 2016, the Department of Veterans Affairs (VA) launched a new website to raise awareness of the Agency’s Digital Health Platform (DHP)—a cloud-based approach to integrating veterans’ health data to produce real-time, analytics-driven personalized care.
The VA has been historically inefficient at managing the health information and care of veterans. The new website (http://www .oit.va.gov/specialreports/dhp/index.html) explains the purpose of the DHP, provides a detailed overview of how the DHP works and provides “user stories” of veterans who have benefits from the comprehensive digital dashboard that enables customized care. The DHP is used to gain recommendations for care and analysis on potential or existing health issues. Instead of providers having to respond to health issues as they arise, the DHP makes preventive care a priority and easy to implement.
A fact sheet published by the VA says “DHP leverages a net-work of application programming interfaces (APIs) to integrate mil-itary and commercial health data, while unifying VA’s data stores, connecting patient to provider in real-time, and predicting the most successful care to provide a better experience to the veteran” (U.S. Department of Veterans Affairs, 2016).
IT at Work Questions1. What benefits do veterans get as a result of the digital dash-
board approach to health care?2. Why would the VA implement a digital dashboard instead
of staying with their traditional approach to processing electronic health records?
Benefits of Digital DashboardsThe interrelated benefits of business dashboards are as follows:
1. Visibility Blind spots are minimized or eliminated. Threats and opportunities are detected as soon as possible.
2. Continuous improvement A famous warning from Peter Drucker was “if you can’t meas-ure it, you can’t improve it.” Executive dashboards are custom designed to display the user’s critical metrics and measures.
3. Single sign-on Managers can spend a lot of time logging into various business systems and running reports. Single-sign-on dashboards save time and effort.
4. Deviations from what was budgeted or planned Any metrics, such as those listed in Table 11.3, can be programmed to display deviations from targets, such as comparisons of actual and planned or budgeted.
5. Accountability When employees know that their performance is tracked in near real time and can see their results, they tend to be motivated to improve their performance.
Sources: Compiled from Verton (2016), Slabodkin (2016), and U.S. Department of Veterans Affairs (2016).
Geographic Information Systems and Geospatial Data 349
Questions
1. Describe business dashboards and their functions. 2. Why do you think dashboards must be in real time and customized for the executive or manager?3. How do business dashboards differ from other types of visual reports?4. Explain the components of dashboards.5. What are benefits of dashboards?
11.4 Geographic Information Systems and Geospatial DataEvery day millions of decisions are made using geographic information systems (GISs). A GIS connects data with geography to understand what belongs where. For example, it’s really diffi-cult to visualize the locations of towns by their latitude and longitude coordinates listed in a spreadsheet, but it’s easy to know where they are when you show these positions on a map (Figure 11.12).
Geographic information system (GIS) is a computer-based tool that captures, stores, manipulates, analyzes, and visualizes geographic data on a map.
Seattle
New York
Miami
Dallas
Los Angeles
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name latitude longitude
Washington DC
Seattle
New York
Miami
Washington DC
DallasLos Angeles
FIGURE 11.12 Longitude and Latitude Coordinates on a spreadsheet are much more difficult to visualize than when they are displayed on a map.
GIS is not just about mapping data, government, businesses, and individuals find GIS useful in solving everyday problems using geospatial data. For example, GIS can connect to location-tracking devices and apps. GIS software can link geospatial data—where things or people are and where they are going—with descriptive data—what things are like or what cus-tomers are doing. GIS’s ability to track customers’ movement and behavior in real space enables new strategies for marketing, retail, and entrepreneurship. Their ability to track products along the supply chain also offers opportunities in logistics and order fulfillment.
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Collecting home and work addresses only paints a static picture of consumer loca-tions. Their movements over time are not tracked. Data that are organized by zip code only cannot reveal customers’ habits. By integrating GISs, businesses can more effectively solve problems such as organizing sales territories, pinpointing optimal locations, finding cus-tomers, managing campaigns, and delivering services. Geospatial data can also map compet-itors’ actions.
GeocodingIn many cases, locations are already in existing data stores, but not in a format suitable for ana-lytics. A simple process called geocoding can convert postal addresses to geospatial data that can then be measured and analyzed. By tapping into this resource, decision-makers can use the geographic or spatial context to detect and respond to opportunities.
Case in Point: GM General Motors (GM) spends a staggering $2 billion a year on market-ing. In the past, it shotgunned its ads at the general public. Now, it maps out which types of households will buy new cars, more accurately determines locations where people buy certain models, and channels its ads specifically to those areas. As a result, GM spends less money to generate higher sales.
GM managers use ESRI’s ArcGIS software to view local demographics, location character-istics, regional differences, and the competitive brand environment to determine how a given dealership should be performing compared to actual results. The GIS makes it possible for GM to isolate demand, target its marketing efforts to local preferences, and position its dealerships to improve sales. With the intelligence provided by the GIS, GM has increased sales despite cutting the advertising budget.
GIS Is Not Your Grandfather’s MapUnlike a traditional flat map, a GIS-generated map is made up of many layers of information that provides users different ways to view a geographic space (Figure 11.13).
Imagine for a moment that you are a regional sales manager who needs to view sales data for one of your 75 stores distributed throughout the State of South Carolina. On a flat map of South Carolina, if you looked at retail store #50, you would see the name of the store and a dot showing where it is located on the map. However, if you view a GIS map of the United States on your computer, smartphone, or tablet, you can hover over South Carolina and when you click on retail store #50, up pops the store’s location, store manager’s name and phone number, weekly and monthly revenue, product categories, a photo of the storefront, and a virtual tour. As a highly paid, busy regional sales manager, this saves you time and your company money, increasing organizational effectiveness and efficiency.
Infrastructure and Location-Aware Collection of Geospatial DataThe infrastructure needed to collect geospatial data continues to expand. Cellular and Internet service providers, sensors, Google Earth, GPS, and RFID systems know the location of each con-nected user or object. Foursquare, Google Maps, and other mobile apps rely on GPS locations. With the Shopkick app, Macy’s can track a shopper’s every move within one of its stores and send the shopper notifications about deals and items of interest. iBeacon is a feature available in iOS 7 devices that uses a low-power Bluetooth transmission to broadcast a user’s location. iBeacon allows Apple, or app developers leveraging Apple technology, to track users inside buildings where satellite transmissions may not reach.
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Similarly to Macy’s, businesses can motivate customers to download a location-tracking app. Using GIS can help businesses target their customer markets more effectively and dynam-ically by engaging with them in real time.
Applying GIS in BusinessGIS tools have made significant contributions to decision making in finance, accounting, mar-keting, and BI. Business applications include the following:
• Analysts can pinpoint the average income in areas where the highest performing stores are established.
• Retailers can learn how store sales are impacted by population or the proximity to com-petitors’ stores.
• A retail chain with plans to open a hundred new stores can use GIS to identify relevant demographics, proximity to highways, public transportation, and competitors’ stores to select the best location options.
• Food and consumer products companies can chart locations of complaint calls, enabling product traceability in the event of a crisis or recall.
• Sales reps might better target their customer visits by analyzing the geography of sales targets.
With current GIS, geospatial, and geocoding technologies and platforms, GISs can be easily incorporated and managed within data analytics and visualization software.
With the GIS moving into the cloud, developers of enterprise applications based on SAP, Microsoft Office, SharePoint, MicroStrategy, IBM Cognos, and Microsoft Dynamics CRM are using it to create a wide range of mobile applications.
FIGURE 11.13 An example of a GIS-generated map. By hovering over a state, such as Texas, another layer of sales and financial data appears.
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Key Termsaggregation 340analytical tools 335data discovery 336data visualization 334
digital dashboard 345drill down 334enterprise data mashup 342geocoding 350
geographic information system (GIS) 349geospatial data 332reporting tools 335
Assuring Your Learning
Discuss: Critical Thinking Questions
1. How people use, access, and discover data in business is being actively disrupted by tablets, which had been designed for consumers. Users have higher expectations for data displays and capabilities. Bor-ing, static graphs and pie charts are unacceptable. Discuss how per-formance management—the monitoring of KPIs, for example—may be improved by providing managers with data visualizations. Now con-sider the opposite. In your opinion, would lack of data visualization hurt the ability to manage performance?
2. Lots of data are available to retailers to make good decisions— loyalty programs, Web analytics, and POS data. However, there is a big
gap between having data and being able to leverage them for real-time decision-making. How can enterprise mashups close this gap?
3. Visit SAS.com and search for Visual Data Discovery.a. Review the screenshots, features, and benefits.b. In your opinion, what are the two most important benefits of this data discovery tool?
c. Would you recommend this tool? Explain your answer.4. Explain how executive dashboards can lead to better business in-sights. What are the limitations of dashboards?
Explore: Online and Interactive Exercises
1. Periscopic is a socially conscious data visualization firm that specializes in using IT to help companies and organizations facilitate information transparency and public awareness. From endangered species, to politics, to social justice, it is the goal of Periscopic to engage the public and deliver a message of responsibility and action. Its philosophy and tagline are “do good with data.”
a. Visit http://periscopic.com and explore its recent work. b. Discuss how data are used to do good. c. How effective is Periscopic’s approach to public awareness and social justice?
2. Visit TIBCO Spotfire and click “Demos” and “Demo Gallery.”a. Select and watch one of the demos.
b. Describe the data visualizations features in the demo.c. Explain the benefits of the application or analytics.
3. Visit the Analysis Factorya. Click Gallery and then select Custom Solutions.b. View one demo, such as Performance Trends, Fusion Charts, Manufacturing Performance, and Sales Map Dashboard.
c. Create a table listing all of the customer solutions for which you tried the demo in the first column. In the second column, list the departments or functions each customer solution supports. In the third column, list the types of visualizations used in each solution.
d. In the team report, discuss how dashboards can impact the quality of business decisions.
Analyze & Decide: Apply IT Concepts to Business Decisions
1. Qlik offers a complimentary e-book entitled “Turn your Excel Re-ports into Stunning Dashboards.”Download the e-book. Write a report about what you learned.
2. Visit IBM’s Watson Analytics Event Center any Thursday at 3 pm ET to take a Tour of Watson Analytics. Write a report on what you learned.
3. Visit the website of software provider Microstrategy
a. Click “Explore the Product.”b. Click “Browse Solutions.”c. Scroll down to choose an industry that interests you. Click on that Industry and “Learn More.”
d. Click “Watch the Video.”e. Write a report describing what you learned.
References 353
Case 11.3 Video Case: The Beauty of Data Visualization—Data DetectiveTED stands for technology, entertainment, and design. Visit TED.com and search “data visualization.” Select “Making Sense of Too Much Data” and find “David McCandless: The beauty of data visualization.” The video and transcript are available. In his TED talk, The Beauty of Data Visualization, David McCandless says that data visualization gives us a second language—the language of the eye.
Questions1. Explain what McCandless means by language of the eye.2. What are the examples of language of the mind?3. What happens when language of the eye and language of the
mind combine?
4. What did David McCandless say about information design?
IT Toolbox
Create Your Own Digital DashboardVisit software provider Sisense. Sign in, start your free trial, and build your first dashboard in minutes.
ReferencesCurtis, K. “Deloitte Hosts PepsiCo and Safeway at the HIVE (Highly
Immersive Visual Environment).” GMAOnline.Org. 2013. gmaonline.orgDeloitte CIO Journal. “Data Visualization Helps Safeway Keep Shelves
Stocked.” The Wall Street Journal. December 3, 2013.Deloitte. “Deloitte Analytics Labs.” 2016. Retrieved December 22, 2016
from https://www2.deloitte.com/us/en/pages/deloitte-analytics/ solutions/deloitte-analytics-labs.html.
Forrest, C. “IBM launches Watson Discovery Service for big data ana-lytics at scale.” TechRepublic, December 16, 2016.
Lohr, S. “For Big-Data Scientists, ‘Janitor Work’ Is Key Hurdle to Insights.” New York Times, August 17, 2014.
Pathak, S. “How PepsiCo sweetens up consumer insights.” Digiday, June 8, 2015.
pepsi.com. 2017.safeway.com/ShopStores/Our-Story.page. 2017.Slabodkin, G. “VA lays out plans for cloud-based Digital Health
Platform.” HealthData Management, December 16, 2016.U.S. Department of Veterans Affairs. “Digital Health Platform.” 2016.
Retrieved December 27, 2016 from http://www.oit.va.gov/library/dhp/DHP_factsheet.pdf.
Verton, D. “VA Launches New Site for Digital Health Platform.” MeriTalk, December 8, 2016.
Case 11.2 Visualization Case: Are You Ready for Football?Nothing inspires passionate comments among sports fans like pre-season predictions. Brett McMurphy’s data visualization looks at how teams ranked in different polls. Visit www.tableausoftware. com and search using “ready for football.” You will see the Preseason Polls & Returning Starters visualization. (a) Interact with the Presea-son Polls & Returning Starters visualization. (b) Select various filters and observe the changes. (c) Download the workbook by clicking the Download button at the lower right corner of the display. View and interact with two other sports-related visualizations, for example, CBS Sports Defensive Matchup Tracker, Fantasy Closers, and Premier
League Points Leaders. Download each. Click the Business and Real Estate Gallery. View and interact with two data visualizations in the gallery. Download each.
Questions1. Which visualization was the easiest to understand at a glance?
Explain.
2. Which visualization was the most difficult or complicated to understand easily? Explain.
3. What are the benefi ts and potential drawbacks of interactive visualizations?