A White Paper

by Dan Carotenuto

Business Intelligence Best Practices forDashboard DesignKeys to Effective Dashboards: Data, Data, Data

Dan Carotenuto is a technical director in Corporate Marketing at InformationBuilders. He is a driving force behind Information Builders’ businessintelligence and integration technical marketing materials. His team createsproduct demonstrations, educational materials, and Flash-based marketingsolutions; conducts public relations, press, and analyst product reviews; andresearches new and emerging business intelligence technologies.

Dan has been with Information Builders since 1989. He often speaks aboutbusiness intelligence and integration at industry conferences and seminars.

Dan Carotenuto

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Overview

Visual Design

A “Few”Words on Visual Design

Visual Design in Action

Word-Sized Graphics

Dashboard Data Integration

Show Me the Data

Integration Styles

Integration and Information Builders

Conclusion

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Table of Contents

The real estate axiom “location, location, location” makes it apparent that the most important attributefor a piece of property is where it is located. For dashboards, think, “data, data, data.” An often-overlooked aspect, data is one of the most important things to consider in designing dashboards.

Even if a dashboard’s appearance looks professional, is aesthetically pleasing, and includes graphsand tables created according to accepted visual design standards, other issues come into playwhen assessing the true success of the application. Remember, appearances can be deceiving. It isalso important to ask yourself: Is the data reliable? Is it timely? Is any data missing? Is it consistentacross all dashboards?

Although visual design is important, sometimes the biggest challenge is getting the right data into the right dashboard in the most efficient way. This paper offers an overview of best practicebusiness intelligence (BI) dashboard design principles and discusses data integration options forgetting data into a dashboard.

1 Information Builders

Overview

2 Business Intelligence Best Practices for Dashboard Design

First, let’s make sure we are using the same language with regards to dashboards. In 2004 StephenFew, a data visualization expert, wrote an article for Intelligent Enterprise magazine that defined adashboard as “a visual display of the most important information needed to achieve one or moreobjectives consolidated and arranged on a single screen so the information can be monitored at aglance.”1 In 2007 Gartner expanded the definition to: “…a reporting mechanism that aggregatesand displays metrics and key performance indicators (KPIs), enabling them to be examined at aglance before further exploration via additional BI tools. Dashboards are useful KPI and metric-reporting mechanisms that enable users to quickly monitor and track performance via an aestheticuser interface. They employ visualization components, such as gauges, thermometers, dials, andtraffic lights.”2

From these definitions we can make several agreed upon assumptions about dashboards: A usershould be able to look at a dashboard and quickly make observations without scrolling, drilling, orclicking off the initial screen. Minimal user interaction can be included to enhance understandingand clarify observations, but too much interaction defeats the purpose of a dashboard and crossesover into the realm of analysis. And that dashboards also:

n Provide a way to monitor and track performance

n Should be able to convey what is going on rather quickly

n Typically contain key performance indicators and use several types of data visualization

A “Few” Words on Visual DesignSince dashboards serve as a way to monitor performance at a glance, graphs, icons, and tabularreports should not be put together in an uncoordinated, unplanned manner. Dashboards must bebuilt methodically, strategically, and with attention to detail. The size, color, and style of a font –such as whether it’s bold or italics – matter more in a dashboard than anywhere else in a businessintelligence solution.

“Two of the greatest challenges in dashboard design,” says Stephen Few in his book, InformationDashboard Design,“ are to make the most important data stand out from the rest, and to arrangewhat is often a great deal of disparate information in a way that makes sense, gives it meaning, andsupports its efficient perception. An understanding of the preattentive attributes of visual percep-tion and the Gestalt principles provides a useful conceptual foundation for facing these challenges.”3

Achieving at-a-glance observations means making data pop. Designers must manipulate thegraphs and tabular reports common to dashboards so the data reflects problems or opportunities– depending on which is important to the user – and stands apart from the rest of the information.This can be done through the use of icons, colors (hues), shapes, and sizes of objects andproperties in a graph or tabular report.4

Visual Design

1 Few, Stephen. “Dashboard Confusion.” Intelligent Enterprise, March 20, 2004.2 Gartner. “Q&A: Important Integration Considerations for Scorecards, Dashboards and Portals.” July 9, 2007.3 Few, Stephen, Information Dashboard Design: The Effective Visual Communication of Data. O’Reilly Media, Inc.

January 2006. 4 Few, Stephen. IBID

Information Builders3

Visual Design in ActionGraphs, tabular reports, and text can be manipulated to make important information stand out.Figure 1 shows a dashboard created with Information Builders WebFOCUS business intelligenceplatform. Note that all the text is gray except for the problems, which are black and slightly larger.Even the axes values and borders are displayed in gray, which makes the text in black moreapparent. Icons further draw the user’s eye to the data that needs attention so that observationscan be made.

Figure 1: Sample dashboard created with WebFOCUS from Information Builders that makes use ofvisual perception and design standards and principles.

Word-Sized GraphicsA common problem in dashboard design is how to deal with the limited amount of real estate.Among others, two solutions that Few advocates are sparklines and bullet graphs.5 These are graphsthat can be displayed in an area no larger than a word. Edward Tufte, the creator of the sparklinedescribes them as “…small, high-resolution graphics usually embedded in a full context of words,numbers, images. Sparklines are data words: data-intense, design-simple, word-size graphics.”6

Figure 2: An example of a sparkline graph.

Bullet graphs are Few’s “answer to the problems exhibited by most of the gauges and meters thathave become synonymous with dashboards.” Radial gauges waste a great deal of space. Thisproblem is magnified when you have many displayed in a single dashboard. Few describes bullet

5 Few, Stephen. IBID. 6 Tufte, Edward R. Beautiful Evidence, Graphics Press LLC. January 2006.

graphs as “…designed to display a key measure, along with a comparative measure and qualitativeranges to instantly declare if the measure is good, bad, or in some other state.”7 Bullet graphsreinforce the notion that a picture is worth a thousand words. They help the viewer quicklyunderstand comparisons made to targets via a graphical representation.

Figure 3: An example of a bullet graph.

Sparklines and bullet graphs both convey considerable meaning on their own, but whencombined along with text-based data in a tabular report, they can convey much more information.

WebFOCUS generates these word-sized graphics as well as other display mediums ideal fordashboards. It provides the ability to manipulate the elements of graphs and tabular reports inaccordance to dashboard visual design standards and principles.

By their very nature, word-sized graphics demand serious data integration considerations.Sparklines are typically rendered from detailed data and can have thousands of data points, whilebullet graphs typically use aggregated data. Generating a tabular report containing these graphscan be difficult, and some common challenges include:

n Coordinating the detail-data display containing potentially thousands of data values representedby sparklines and the aggregate data display containing a handful of values represented bybullet graphs into a single row

n Incorporating these graphs and reports along with others so that they can display data frommany different areas of the organization all on a single screen

The way to address these challenges is through data integration.

Business Intelligence Best Practices for Dashboard Design4

7 Few, Stephen. IBID.

Figure 4: This mobile dashboard createdwith WebFOCUS from Information Buildersshows how sparklines, bullet graphs, andother data elements tell more about thedata when used together than when usedon their own.

The challenges of designing dashboards does not end with knowing which hues to use and howto make information pop. The data in dashboards is used as the basis for making critical businessdecisions. Designers must consider what data to use and how to make it available and integrate itinto a dashboard solution.

The answers to the following questions help determine which data integration style should be implemented:

n What is the quality of the data targeted?

n How accurate is it?

n Should it be real time?

n Where is it coming from?

n Does information from systems outside the enterprise need to be included?

Before reviewing the integration styles that can address these concerns, some common elementsof data integration – including data access, data quality, and consistency – must be addressed.

Show Me the DataThe following aspects of data integration are paramount to the effectiveness of dashboards and arecommon to all styles of integration:

n Data access

n Data quality and consistency

n Data consolidation

n Data latency

n Impact on operational systems

n Implementation time and cost

Data AccessData access is the most fundamental property of dashboard data integration. It is not just aboutgetting access to data wherever it is; but also involves accessing the data in the most efficient waypossible without sacrificing data quality and consistency. Also along for the ride is the ability to jointhe data across disparate sources and platforms. Software systems such as Web services have openednew doors for data access by allowing applications to tap into previously unavailable informationsystems. Business intelligence applications can be made available via Web services, effectively turningthem into data sources that can be combined, joined, and reconciled with other enterprise data.

Data Quality and ConsistencyThe accuracy of information in dashboards affects business decisions. The Data Warehouse Institute(TDWI) reports that, “…data quality problems cost U.S. businesses more than $600 billion a year. Yet,most executives are oblivious to the data quality lacerations that are slowly bleeding their compa-nies to death. More injurious than the unnecessary printing, postage, and staffing costs is the slow

Dashboard Data Integration

5 Information Builders

but steady erosion of an organization’s credibility among customers and suppliers, as well as itsinability to make sound decisions based on accurate information.”8

Ensuring data quality and consistency provides a single version of the truth throughout the enter-prise and needs to be seriously considered when designing dashboards.

Data ConsolidationData consolidation involves combining data from multiple sources into a central system such as adata warehouse. Consolidating data includes many challenges, such as where the data resides, whichdata to combine, how often it should be combined, and whether or not it should be transformed.Since dashboards often have an amalgamation of information from across the enterprise, dataconsolidation is fundamental to making data available for a dashboard.

Data LatencyThe dashboard’s primary purpose determines how current its data must be. For example, a strategicdashboard used to help understand long-term business plans may not be concerned with the day-to-day transactions. Data for this dashboard can be current up to the week, month, quarter, or year.Operational dashboards, on the other hand, require real-time or near real-time data to make imme-diate decisions and solve problems or address opportunities as they arise. It is important that thesedashboards experience little or no data latency.

Impact on Operational SystemsBusiness intelligence solutions strive to minimize their impact on operational systems. Dashboardsused for strategic purposes typically do not require access to operational systems. Though it may seemthat operational dashboards absolutely need access to operational systems, it is not always required.

Operational dashboards can be fed data from a data warehouse instead of an operational system.The process is a variation of the traditional data warehouse style of integration known as the real-time data warehouse. There can also be hybrid approaches where parts of the dashboard use areal-time data warehouse and others pull data directly from the operational systems. Which approachis best depends on the dashboard requirements. The bottom line is that dashboards – as part of aBI solution – should minimize their impact on operational systems.

Implementation Time and CostThere are many ways to make data available to a dashboard. Some are faster than others, and costsvary. Which approach is best is driven by business demands, but should not be determined at theexpense of data quality and consistency because it can lead to bad decisions. An ideal approach todata integration might be compromised by making dashboards functional sooner rather than later.

Keep in mind that different integration styles demand different implementation times, whichimpact how fast a dashboard solution can be made available. Operational data access requiresconsiderably less time to implement than a traditional data warehousing style. The trade off isimpact on operational systems.

Business Intelligence Best Practices for Dashboard Design6

8 Eckerson, Wayne W. “Data Quality and the Bottom Line: Achieving Business Success Through a Commitment to HighQuality Data.”TDWI Report Series. 101 Communication, LLC. January 2002.

The cost to integrate data for use in a dashboard depends on whether the integration solution isbuilt or bought. This decision is determined by the level of customization required and the long-term volatility of the IT infrastructure. Buying a custom solution might mean having to change thebusiness to work with the solution. Building a solution might be necessary when a custom solutionsimply does not exist.

Integration StylesThere are many ways to address the fundamental challenges of data integration. They all revolvearound building the right architecture and selecting an appropriate integration style. For dashboardsthis means choosing one or more integration styles in order to satisfy the needs of users andensure that the integration solution can change and adapt as the business changes. iWay Softwaretechnology from Information Builders along with WebFOCUS supports many integration styles:

n Data warehousing

n Real-time data warehousing

n Operational data access

n Enterprise information integration (EII)

n Web services

n Process-driven business intelligence

Data WarehousingData warehousing involves extracting data from operational systems, transforming it into a universaldata model, and making it available to applications such as business intelligence dashboards.

Dashboards used for long-term strategic direction commonly use data that does not changefrequently – at most on a weekly basis. Since data latency is not a concern in these cases, datawarehousing is a common option. Data warehousing reduces the unnecessary load put on opera-tional systems, especially when the content of a dashboard demands data from multiple sourceson multiple platforms. Dashboards commonly include calculations on or transformations of theoriginating data. A data warehouse reduces the redundancy of data consolidation processing thatwould tax an operational system.

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Combine data from multiple systemsinto a data warehouse

Data Warehouse

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Figure 5: A data warehouse reduces the load dash-boards have on operational systems by extractingoperational data, transforming it, and loading itinto a separate area dedicated for other applica-tions like business intelligence dashboards.

Real-Time Data WarehouseOperational dashboards frequently require real-time or near real-time data. In these cases, datalatency is a primary concern. One of the benefits of a real-time data warehousing approach todashboard data integration is zero data latency.

The key is feeding the data warehouse in real time or near-real time. Transactions and events arecaptured as they occur, cleansed on the fly, and loaded into the data warehouse. The obviousdifference here from traditional data warehousing is that the extraction step occurs as thetransactions come in. This further reduces the impact on operational systems, by minimizing thefrequency and volume of scheduled extract, transform, and load (ETL) jobs that load and refreshthe data for a traditional data warehouse. Even though real-time data warehousing is conceptuallycomplex it still uses straightforward integration technologies like enterprise service buses, real-timetransformations, adapters, and transaction processes.

Figure 6: Real-time data warehousing addresses data latency concerns in dashboards by tricklefeeding the data warehouse with operational transactions as they come into the enterprise.

Operational Data AccessBusiness intelligence users often want a single view of enterprise data. This requirement sometimesoverlaps into the world of dashboards where users want to monitor what pertains to their specificresponsibilities. Operational data access can provide dashboard users with a single view of the data,but it greatly impacts the operational systems. For that reason, some take a conservative positionand recommend more traditional integration styles such as data warehousing and real-time datawarehousing. However, access to detail data from within a dashboard helps users make betterdecisions, which is where operational data access can help.

Since dashboards cannot always provide all the information users require, it is useful to provide amethod for getting more details. Rolling over a bar in a graph or drilling down on an element in atabular report can bring up context-specific information that enhances dashboard-spawnedobservations. This analysis event can tap into operational data when necessary, further reinforcingthe quality and accuracy of the observation. As long as this on-demand pulling of operational dataimproves decision-making, it will outweigh the negative impact on operational systems.

Business Intelligence Best Practices for Dashboard Design8

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Transaction Transaction

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Operational Systems

Figure 7: Dashboard designers can help enhance the understanding of observations by includingdrill-downs or rollovers that pull data from operational systems.

Enterprise Information IntegrationIn a perfect world a dashboard uses a single enterprise data warehouse that has all the informationit needs. In reality, this is rarely the case. A dashboard often uses multiple data warehouses to getthe data it needs. How are these other sources tied together for use in a dashboard? What happenswhen users need additional or new content from operational systems? What is done while IT workson integrating that data into the data warehouse? Should dashboard users wait until IT catches up?

EII helps solve these dilemmas by providing the ability to link multiple data warehouses andoperational systems. EII helps minimize the delay in getting the right information into the hands ofdecision-makers. This is an important integration solution for the timely delivery of dashboards asthe demands of business change. EII is particularly valuable when companies go through mergersand acquisitions, helping multiple systems from different companies rapidly integrate and getinformation to management.

Figure 8: EII lets designers get data into a dashboard faster by linking multiple data warehouses andoperational systems.

Web ServicesIntegrating data from the enterprise with applications hosted outside the organization is possiblewith Web services used as an information resource. For example, you can reconcile data from a datawarehouse in your enterprise with a Web service that is available via an application hosted by a

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Operational Access

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third-party vendor as if they were a single data structure. This extends the possibilities of what canbe delivered in a dashboard.

Another way Web services make more information available to dashboards is by exposing theintelligence built into existing reporting solutions as reusable Web services. For example, let’s say areport exists that produces the lifetime value of customers. That information might be useful in adashboard, but how can it be displayed without bringing along the entire report that produces it?Through Web services, this type of information can be exposed as data and integrated into thedata warehouse or used directly within a dashboard.

Figure 9: Web services provide a way to get information from outside the enterprise into a dashboard.They can also expose existing BI reports as data for integration into a dashboard.

Process-Driven Business Intelligence “Work smarter, not harder” is a common axiom in the business world. It is also what process-drivenbusiness intelligence does for an organization through the automaton of decision-making. Thisautomation is accomplished by embedding event-driven business intelligence functions intobusiness processes to reduce the need for a physical action or increase the timeliness of a response.Some key business intelligence elements that can be embedded are data visualization, analytics,alerts, and reports.

Supply-chain management is a common area where business processes can be automated. Forexample, inventory levels can trigger an event that parts need to be ordered from suppliers. Anevent can be automated to start reordering parts as part of a process flow. A report can show howmany parts are needed and include price quotes and delivery dates acquired from suppliers viaWeb services. The automated system can also use the quotes to select a supplier by determiningwhich supplier has the best price and then generate an order.

Dashboards can be used to monitor, improve, and streamline process-driven business intelligence.In the supply-chain example, there might be room for improvement. A dashboard can be used toshow that on-time delivery of parts has improved, but profits are flat. Further analysis might indicatethat profits are flat due to manufacturing costs. Though intelligence was added to the automationof the supplier price-evaluation process, additional intelligence could be added to factor in turn-over history for a part. Instead of re-ordering popular parts often, what if a higher volume was

Business Intelligence Best Practices for Dashboard Design10

Access appearing to be from a relational table

WebService

WebService

WebService

Web Services

ordered less often? That might result in a better price from suppliers, which in turn means lowercosts and higher profits. The dashboard is where this type of observation is made. Analysis andaction resulted in improvements to the process-driven business intelligence solution.

Operational dashboards can also provide feedback on bottlenecks in the business process, whichcan help IT decide where to concentrate efforts when implementing or improving a process-drivenbusiness intelligence solution. For example, problem resolution time could be displayed in adashboard to help operations understand where delays exist, how long they last, and which onesare the most adverse. A more targeted and strategic approach can then be used to improveefficiency. Thus, business processes can drive business intelligence and business intelligence can beused to drive the business process.

Figure 10: Process-driven business intelligence helps organizations work smarter, not harder, byautomating decision-making. Dashboards can help monitor, improve, and streamline the process-driven business intelligence solution.

Integration and Information BuildersiWay Software’s technology supports over 280 native interfaces on any platform and empowersdashboard designers to use any data from any source – within the enterprise and beyond.Flexibility and agility are recognized by both iWay and WebFOCUS as integral parts of any dataintegration strategy. Support for packaged applications as well as the ability to create custominterfaces lets organizations choose the optimum solution for their business needs and ITinfrastructure requirements. Organizations can pull data from any source, transform it, and load itinto any target on any platform. iWay supports all brokers, message queues, and transactionprocessing monitors. Its ability to access legacy systems gives organizations the flexibility to use theintegration style of their choice, from connecting dashboard users to data warehouses andoperational data, to hybrid approaches that combine access to traditional data warehousingsolutions as well as the ability to drill through to operational systems.

WebFOCUS and iWay enable enterprises to build and manage their business processes end to end.This service-oriented approach to process-driven business intelligence means that organizationscan create and deploy business intelligence as part of any process or service. This approach allowseach service to be managed independently in a plug-and-play manner, minimizing applicationmaintenance efforts and cost.

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Dashboards help organizations make better business decisions. The way in which they are createdis not trivial and attention must be paid to the details. Employing visual design standards andprinciples are important, but are only part of the journey. The way in which data is integrated fromthe enterprise is just as important. It requires proper planning to address what users need to see,where the data is coming from, how soon it can be delivered, and ensuring that it is accurate and consistent.

Information Builders’ iWay technology provides the options necessary for integrating enterprisedata for use in dashboards. WebFOCUS lets designers build dashboards that take advantage ofaccepted visual design standards. From its support of over 280 native adapters to its ability toautomate business processes, these solutions provides organizations with the luxury of being ableto select an integration style that meets the needs of their dashboard users while adapting to theirenterprise infrastructure.

Business Intelligence Best Practices for Dashboard Design

Conclusion

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