CONCLUSIONS PAPERHow to Effectively Realize Data VisualizationGaining Insights from Your Data Faster than Ever and Sharing the Insights with OthersFeaturing:Justin Choy, Global Product Management, Business Intelligence,SASJennifer Marchi, Global Product Marketing, Business Intelligence,SASInsights from a Webinar in the Applying Business Analytics Webinar Series
1How to Effectively Realize Data VisualizationQuickly Visualize Big Data Analysis on the iPad®and the WebOrganizations are inundated with data – terabytes and petabytes of it. Data pours infrom every conceivable direction: from operational and transactional systems, fromscanning and facilities management systems, from inbound and outbound customercontact points, from mobile media and the Web. It is structured and unstructured; it ismessy and overwhelming; it flows at greater speed than ever.The optimist’s vision for this tidal wave of data is that organizations will be able to harvestand harness every relevant byte of it to make supremely informed decisions.However, traditional architectures and infrastructures are not up to the challenge. ITteams are burdened with ever-growing requests for data, ad hoc analyses and one-off reports. Decision makers become frustrated because it takes hours or days toget answers to questions, if at all. More users are expecting self-service access toinformation in a form they can easily understand and share with others.“Many challenges arise when working with this much data,” said Justin Choy, GlobalProduct Manager for Business Intelligence Solutions at SAS. Choy joined JenniferMarchi of SAS Business Intelligence Product Marketing for a webinar in the SASApplying Business Analytics Series. “One problem is that it takes a long time toaggregate all that data. To get around this problem, IT has to create summaries of thedata, or a cube with predefined hierarchies for better performance.”“Once you have a summary or a cube of the data, you can look at it more quickly,” saidMarchi. “But what happens when you realize you need to look at the data in a differentway than the summary or cube provides? You would typically have to turn to a dataadministrator or someone else in IT, and request another view of the data. In mostorganizations, accessing this new view will take some time, sometimes even a day,which, in turn, delays your analysis.”Another problem is that some business questions are best answered by using allavailable and relevant data, which might be too much data to process within thedecision window.Here is where high-performance computing and data visualization techniques come in.“Data visualization is shaking up the world of analytics, changing the way you work withdata,” said Marchi. “You’ll find insights from your data faster than ever and be able toshare those insights with others.”Learn MoreView the on-demand recordingof this webinar:sas.com/reg/web/corp/1838098Other events in theApplyingBusinessAnalyticsWebinar Series:sas.com/ABAWSFor more about SAS®VisualAnalytics:sas.com/visualanalyticsTo see a video demo ofSAS®VisualAnalytics:youtube.com/watch?v=1DUM4YdnzzARelated white papers:Big Data: Harnessing aGame-Changing Assetsas.com/reg/gen/corp/1583148In-Memory Analysis: DeliveringInsights at the Speed of Thoughtsas.com/reg/wp/corp/41962High-Performance AnalyticsInsights: Big Data, BiggerOpportunitiessas.com/reg/gen/corp/hpa-insights
2SAS Conclusions PaperIntroducing SAS®Visual Analytics“SAS® Visual Analytics is a high-performance, in-memory solution for exploring massiveamounts of data very quickly, using SAS’ industry-leading analytics,” said Marchi. “Itenables users to spot patterns, identify opportunities for further analysis and conveyvisual results via Web reports or an iPad®.”With SAS Visual Analytics, business users can explore data visually on their own, butit goes well beyond traditional query and reporting. Running on low-cost, industry-standard blade servers using Hadoop distributed processing, it delivers answers inseconds or minutes instead of hours or days. This kind of processing speed withmassive data sets makes it possible to find important insights quickly – insights thatwere not evident before.For example, marketing campaign optimizations that previously took eight to 10 hoursor more can now run in less than three minutes. Bank risk calculations that once took 18hours can now be completed in 15 minutes.High-performance computing completely redefines what’s possible. Analysts can usecomplete data sets instead of sample subsets. They can apply sophisticated analytictechniques, not just simple calculations, to generate descriptive and predictive insightsfrom all that data. And they can put this power into the hands of a broad range of usersthrough a dynamic, visual interface.Consider some possibilities. Retail marketing analysts are always looking for ways tooptimize the offers and promotions they make to customers. When they can includemore data from online sales and hundreds of stores – plus demographic information,purchased market data, social media data and any other relevant data source – theycan determine “next best offer” recommendations with greater accuracy and certainty.They are not limited to a subset of customers; they can get on-target recommendationsfor entire populations, quickly and easily.Consider fraud detection models for banking and finance. With SAS Visual Analyticsembedded in the analytics life cycle, analysts can look at more data – more often andmore quickly – for new insights that lead to better models that can be quickly adapted toaddress new and emerging patterns of fraud.Retail, telecommunications and financial services are showing the greatest early interestin SAS Visual Analytics because of its ability to analyze large customer and prospectpools at an individual level while easily managing a collaborative analytics environment.In time, data visualization capabilities will be extended across the SAS software portfolio.SAS Visual Analytics combinesan easy-to-use dynamicinterface and in-memoryprocessing to enable all typesof users to visually explorebig data, execute analyticcorrelations on billions ofrows of data in minutes orseconds, understand what thedata really means, and deliverthe results quickly whereverneeded via Web reports andmobile devices.Do you simply want to collectlarge amounts of data, or do youwant to understand and takeadvantage of its full businessvalue? What if you could easilyaccess more than a billionrows of data, and then veryquickly explore all of that datausing visualization techniquescombined with powerfulanalytics? You can.
3How to Effectively Realize Data VisualizationThe Six Components of SAS®Visual AnalyticsSAS Visual Analytics includes the following components.• The SAS®LASR™Analytic Server quickly reads data into memory for fastprocessing and data visualization, with direct communication to clients.• SAS Visual Analytics Explorer is a discovery and visualization tool for ad hoc dataexploration and analysis.• SAS Visual Analytics Designer provides a graphical, drag-and-drop environmentto create standard and custom reports and dashboards.• SAS Visual Analytics Mobile is a tool for viewing reports by connecting to serversand downloading information on the go.• SAS Visual Analytics Hub provides a central location to launch the variouselements of SAS Visual Analytics.• SAS Visual Analytics Environment Administration allows administrators tomanage users, security and data.SAS Visual Analytics is tremendously powerful for its in-memory and massive parallelprocessing capabilities, but it is still cost-effective, said Choy. “One of the ways we’vemade it cost-effective is to use commodity hardware, taking advantage of Hadoopfor data persistence on blade servers from HP and Dell, as well as dedicated dataappliances from our partners Teradata and EMC Greenplum.”SAS LASR Analytic Server has been tested on billions of rows of data and is extremelyscalable, bypassing the known column limitations of many relational databasemanagement systems (RDBMS). This processing power is coupled with SAS Analytics,which differs from other solutions that simply move data from a SQL database intomemory. Other solutions cannot support regressions or logistics models because suchcapabilities are not built into databases.“The speed of in-memoryarchitecture offers tremendousbenefit. Organizations canexplore huge data volumesand get answers to criticalquestions in near-real time. SASVisual Analytics offers a doublebonus: the speed of in-memoryanalytics plus self-serviceeliminates the traditional waitfor IT-generated reports.”Dan VessetProgram Vice President of BusinessAnalytics Research, IDC
4SAS Conclusions PaperFast and Easy Visual Data Exploration“One of the first things a data analyst wants to do when presented with a new set ofdata is to get some idea what it’s about,” said Jim Goodnight, CEO of SAS. “What arethe outliers? What variables are related to each other? Up until now, analysts would haveto spend hours and hours doing samples so they could actually get jobs to run. WithSAS Visual Analytics, you can cruise a billion records to create graphs and plots oneafter the other. It really allows you to understand your data better before you go into thehigh-performance analytics.”Marchi and Choy demonstrated how SAS Visual Analytics Explorer can conceptualize,visualize and investigate the data in different ways to find the best answer a particularbusiness question. To see SAS Visual Analytics in action, check out the four-minutedemo at youtube.com/watch?v=1DUM4YdnzzA.Visually Explore the Data“By dragging and dropping hierarchies or categories onto the visualization pane, I canquickly and easily see how my revenue expenses are doing by region,” said Choy,demonstrating the system. “I can hover over the bubbles and see that my West regionis doing better than other regions. I can double-click on the bubble and go into thatregion for more detail. It’s as simple as that, and all of the data being presented to meis based on a billion rows of geographic, product and financial information forthis manufacturing company.”Figure 1: The interface uses intuitive, drag-and-drop actions and visualizations.Users can explore all data,execute analytic correlationson billions of rows of data inseconds, and visually presentresults to the Web and mobiledevices. This kind of processingspeed with massive data setsmakes it possible to quicklyidentify patterns, trends andrelationships in data that werenot evident before.
5How to Effectively Realize Data VisualizationCreate Your Own HierarchiesIf you need the data organized a certain way for the business problem at hand, youdon’t have to go to your company’s data specialists to request a new view of the data.“With SAS Visual Analytics, you have access to all of the data, and based on all of thedata, you can create and modify your own hierarchies to explore the data, however andwhenever you want, without having to rely on someone else,” said Choy.“It is so easy to do. I can create a new visualization and then go into the ‘Create a NewHierarchy’ area, and then just double-click or drag and drop [from a menu selection box]the items on which I want to build a hierarchy. Once I’m satisfied with that, I can give it aname or just hit ‘OK.’ It’s that easy.”Choy demonstrated how the new hierarchy appears in the visualization. Double-click ona bar in a bar chart or on a slice of a pie chart, for instance, and you can drill down to adifferent level or go back up a level. All of these views are changing within seconds, yetdrawing on a billion rows of data behind the scenes.Choose the Best Visualization for the Data“When you’re working with a billion rows of data, it is really difficult to quicklyunderstand what’s happening in the data simply by looking at rows and columns,”said Marchi. “Even guessing what type of chart to use can be challenging. SASVisual Analytics simplifies all that by using intelligent autocharting to recommend anappropriate type of visual for the information you’re trying to view. It could be a line orbar chart, a scatter plot or box plot, heat maps or bubble charts – anything from theportfolio of available visualizations.”In the example shown in the demo, SAS Visual Analytics recognized that the data hadgeographic elements – revenue and expenses by geographic regions – and offered thedata as a bubble plot superimposed on a map of the regions. In another example, Choyshowed how SAS Visual Analytics chose a line chart as the best visual for a selection oftwo variables, then changed to a clustered bar chart when a third variable was added.Of course, users can always select the desired of visual – anything acceptable to themeasures and categories chosen.And remember, this speed-of-sight display is being calculated with 1.1 billion rowsand 47 columns of data.Build-it-yourself hierarchieseliminate the need for dataanalysts to constantly seek helpfrom IT. It is easy to drill up anddown through the hierarchies toslice and dice data on any level.Autocharting capabilities helpusers create the best possiblevisualizations, including thosespecifically designed to displaybig data.
6SAS Conclusions PaperRefine the ViewWhat if you only want to view data for a certain region, product line or some othervariable? “SAS Visual Analytics has filtering capabilities that make it easy to refine theinformation you’re viewing,” said Marchi. “Simply add a measure to the filter pane orselect one that’s already there, and then select or deselect the items on which to filter.”What if the filter isn’t meaningful, or it skews the data in undesirable ways? A histogramon the right of the screen provides a visual cue about the distribution of the data,showing how the data is affected by filtering a particular measure, said Marchi, whoused expenses as an example. “The histogram shows that the majority of the data ison the left, so if I filter from the right, it will have a minimal impact on the informationI’m viewing in the visualization pane. However, if I filter from the left, it will have a moresignificant effect on what I’m viewing, because the majority of the data is distributed inthis area. Histograms allow you to save time by giving you an idea what effect the filterwill have on the data before you apply it. Rather than relying on trial and error or gut feel,you can use the histogram to help you decide what areas to focus on.”Understand the Distribution of the DataUnderstanding the distribution of the data is now as simple as creating a new visualand dragging the measure or category onto the visualization pane.“By default, the system automatically calculates the best distribution for the data, butthe user can go under the ‘Properties’ tab and change that,” said Choy. “A histogramshows how the data is distributed, but a better visual for this purpose is a box plot[which graphically depicts numerical data through summary calculations such asminimum, maximum, upper and lower quartile, and median]. I can create a new box plotby creating a new visualization, selecting that visual, and then dragging and droppingthe visual on here. You can hover over the box plot and not only see the distribution ofthe data, but also where the important 50 percent of your data is, as well as some basicstatistics about the data, such as average, median, standard deviation, minimum andmaximum, average standard deviation, whisker and quartiles information, and count.“I can even add a new measure onto here, and we can do a comparison over twodifferent measures in the box plot. I can then add another category in here, such asproduct line, for example, and now instead of doing 10 calculations on the fly, we’reactually doing 40 calculations over a billion rows. And we’re getting the results extremelyfast, especially considering that the median, the middle value of the data, requiresscanning all 1.1 billion rows of data.”
7How to Effectively Realize Data VisualizationFigure 2: Interactive box plots help users quickly understand the distribution of the data.Identify Relationships Among VariablesSAS Visual Analytics makes it easy to assess relationships among variables. Justselect a group of variables and drop them into the visualization pane; the intelligentautocharting function displays a color-coded correlation matrix that quickly identifiesstrong and weak relationships between the variables. Darker colored boxes indicatea stronger correlation, lighter boxes a weaker correlation. Hover over a box to see asummary of the relationship. Double-click on a box in the matrix for further detail.“Previously, this type of calculation would have taken many hours, but now it can bedone in seconds,” said Choy. “Think about it; we’ve generated a 10 by 9 correlationmatrix, executing 45 correlation calculations on over a billion rows of data, and theresults were displayed in seconds. By using box plots and correlation matrices, SASVisual Analytics can help speed up your analytics life cycle because analytical modelerscan now do variable reduction more quickly and effectively.”Understand – with Confidence – What It MeansDo your business users need help understanding what all this data exploration is tellingthem? No problem. “For business users or analysts who are not familiar with terms suchas ‘regression’ or ‘correlation,’ help is available,” said Marchi. “We’ve added a ‘WhatDoes It Mean’ feature to explain some of the terminology and help users understandwhat they’re seeing.” Click on the information icon, and a pop-up dialog box explainswhat the analysis has shown: for instance, that there is a correlation of -0.94, whichsuggests there’s a strong linear relationship between two variables.“By using box plots andcorrelation matrices, SAS VisualAnalytics can help speed upyour analytics life cycle becauseanalytical modelers can now dovariable reduction more quicklyand effectively.”Justin ChoyGlobal Product Management,Business Intelligence, SAS
8SAS Conclusions PaperCreate Your Own Visual Reports and DashboardsOnce you’ve had a chance to visualize and explore your data, you’ll likely see somethingthat you want to share with someone else. Or you might want to generate a reportbased on the data you have been exploring. The SAS Visual Analytics Designer providesthe tools to create and distribute Web-based reports.Through a graphical interface, report authors can get wizard-driven help for previewing,filtering or sampling data before creating visualizations and reports. A variety of formatsare available: standard and three-dimensional bar charts with multiple lines, standardand three-dimensional pie charts, scatter plots, heat maps, bubble charts, and tilecharts – all with the option for annotated reference lines.The reports are dynamic and interactive, as Choy demonstrated. “I’ve just opened areport with three sections, looking at gross margin for product lines and categories overa range of years. I can click on 2011 to zero in on that year. Click a bar in the yearlygross margin chart to filter product line and product category gross margin – the othertwo segments of the screen display. I can select various product categories to filter onand get different information – or select a geography from the global filter.”Choy’s sample report had multiple tabs, each with unique sets of visualizations, allof them clickable to explore up or down a level in the hierarchy. With drag-and-dropsimplicity, report authors can define the interactions among visuals in a report, specifythe type and appearance of the report page, and add labels and annotation.Figure 3: Business users can create their own reports and dashboards using a highlyvisual workspace.On-demand ‘What Does ItMean’ balloons give businessusers clear explanations ofcomplex analytic functions,correlations and linearregressions in a language thatthey can understand.
9How to Effectively Realize Data VisualizationPublish Information to the Web and Mobile DevicesDecision makers get the insights they need, when they need them, even when they’reon the go. Reports are easily read via the Web or on an iPad using the SAS Mobile BIapp, a free iOS app available from the iTunes®App StoreSM. Native iPad support usesthe most popular gestures and capabilities, such as zoom, swipe, drag and drop, andresizing objects on screen. Other mobile devices will be supported in the future.“Executives or any mobile user can easily benefit from the interactive report viewingcapabilities,” said Marchi, demonstrating on her iPad the reports created earlier inthe demo. “It is highly visual and very self-service for the user – and very simple. Justopen the SAS Mobile BI app to see your portfolio of reports. Click on the library andnavigate to a shared folder to look at reports and download new ones. Click ‘Subscribe’to download a report. The display shows thumbnails of the reports you subscribe to,which can be viewed at any time, even when offline.”The reports offer the same interactions between charts as Choy demonstrated in theDesigner toolbox. Reports can also be saved to PDF or PNG formats for printing.Figure 4: Get a quick, easy visual understanding of customers or operations on yourmobile device.“SAS’ strongest play withSAS Visual Analytics is tosupercharge its predictiveanalytics capabilities. The timeshift from hours to minutespromises to enable customersto do more analysis with moredata and greater accuracy thanever before.”Doug HenschenInformationWeek (SAS Introduces Big DataVisual Analytics Platform, March 23, 2012)
10SAS Conclusions PaperClosing ThoughtsEven the most common descriptive statistics calculations can become complicatedwhen you are dealing with big data. You don’t want to be restricted by column limits,storage constraints and the limited data type support of traditional data architectures.The answer is an in-memory engine that accelerates the tasks of data exploration and agraphical interface that displays the results in simple visualizations.“Dealing with billions of records on a regular basis is just a reality of doing businesstoday, and SAS understands that,” said Marchi. “SAS Visual Analytics allows youto explore all of your data using visual techniques combined with industry-leadinganalytics. Visualizations such as box plots and correlation matrices help you quicklyunderstand the composition and relationships in your data.”Large numbers of users, including those with limited analytical and technical skills, canquickly view and interact with reports via the Web or mobile devices, while IT maintainscontrol of the underlying data and security.The net effect is the ability to accelerate the analytics life cycle and to perform theprocess more often, with more data – all the data, if that’s what best serves thepurpose. By using all data that is available, users can look at more options, make moreprecise decisions and succeed even faster than before.“With SAS Visual Analytics, youcan explore your data, discovernew insights, generate reportsand deliver the information tothe people who need it, all froma single solution. Whateveryour industry – retail, insurance,health care and life sciences, orfinancial services – SAS VisualAnalytics can help.”Justin ChoyGlobal Product Management,Business Intelligence, SASStay InformedFollow us on twitter:@sasanalyticsLike us on Facebook:SASAnalyticsTo get fresh perspectives oncustomer analytics from marketingpractitioners writing on the SAS®CustomerAnalytics blog:blogs.sas.com/content/customeranalytics