IQ intelligence quarterly

Journal of Advanced Analytics

2Q 2O13

1 Bringing big data to life 3 Why your brain needs data visualization

5 Visual analytics supports policy decisions

8 Gain greater customer insight with visual analytics

10 Envision the future with data visualization

12 Free access to valuable census data

14 Visualize this: Snap the big picture into focus

16 Visualizing data makes hearing it easier

18  Spark questions with visual analytics

20 Visual analytics helps solve public complaints

22  Secrets to big data computing 25  The sky is the limit 27  Data visualization made easy

IQ intelligence quarterly

Journal of Advanced Analytics

2Q 2O13

Editorial Director Mikael Hagstrom [email protected]

what’s in this issue?

Editor-in-Chief Alison Bolen [email protected] Managing Editor Lindsay Beth Gunter [email protected]

It’s time to really take a look at all of your data and see what you’ve been missing. Whether you’re a business user with limited technical skills, a statistician or a data scientist, powerful analytics are at your fingertips. Anyone – regardless of analytic background – can understand and benefit from complex data when sophisticated analytics are seamlessly integrated with visual display features such as on-the-fly forecasting, autocharting, “what does it mean” pop-ups, and drag-and-drop capabilities. With easy analytics, robust reporting, intuitive visual displays and mobile capabilities, you’ll see things you’ve never seen before, ask questions you never imagined asking, and easily share the answers with others.

Intelligence Quarterly is published quarterly by SAS Institute Inc. Copyright © 2013 SAS Institute Inc., Cary, NC, USA. All rights reserved. Limited copies may be made for internal staff use only. Credit must be given to the publisher. Otherwise, no part of this publication may be reproduced without prior written permission of the publisher. SAS and all other SAS Institute Inc. product or service names are registered trademarks or trademarks of SAS Institute Inc. in the USA and other countries. ® indicates USA registration. Other brand and product names are trademarks of their respective companies. SAS is the leader in business analytics software and services, and the largest independent vendor in the business intelligence market. Through innovative solutions, SAS helps customers at more than 60,000 sites improve performance and deliver value by making better decisions faster. Since 1976 SAS has been giving customers around the world THE POWER TO KNOW. ®

 opy Editors C Amy Dyson Chris Hoerter Amy Madison Trey Whittenton Editorial Contributors Deirdre Arnold Anne-Lindsay Beall Barry Gay Michi Johnson Jennifer Marchi Marcie Montague Stuart Nisbet Analise Polsky Chris Pope Stephanie Robertson Peter Schütte Taylor Sisk Mark Torr Raffaella Viadana Biondelli Ed Walker Art Direction Brian Lloyd Photography John Fernez Steve Muir

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Bringing big data to life Ask yourself, how is big data changing my life? The future of insight starts with making your big data assets work for you.

In past issues of this magazine, we’ve discussed the concepts of hyperconnectivity, big data and real-time analytics. Hyperconnectivity allows us to expand our networks far beyond our geographic locations and gives us access to new possibilities for work and value creation. Big data lets us recapture the best of what we had before globalization, when the citizens of communities felt their mutual dependence in every moment, and human connections were deep. Real-time analytics introduces the ability to live in the present instead of the past, moving from hindsight to insight. How is the convergence of these three megatrends changing your life? A big question, I know, but the future of business will be fueled by big data. And unlike the diminishing resources of an

IQ industrial economy, this new renewable resource grows at an exponential rate. Taking charge of our common future starts with our ability to liquidize big data. But how? Just as coal gets liquidized to turn it into fuel oil, big data requires a final liquidation step that makes it usable too. For big data, that final step is visual analytics, which makes big data portable, transferable and easy to share. Data visualization brings big data to life by liquidizing virtual knowledge assets in your day-to-day interactions with colleagues. It helps you anticipate what’s coming, challenge assumptions and make decisions that align with organizational goals. Further combining data visualization with high-performance speed is opening the world of big data like never before. This

2 revolutionary technology helps organizations convert raw data – from financial market data, consumer spending trends, climatological readings, geographic coordinates and countless other sources – to pure value.

dislikes, and other qualitative data. By merging qualitative data with quantitative data, you see a fuller, more complete picture that you wouldn’t get from analysis of one-dimensional strands of structured, static data.

Why your data must be liquidized Let’s face it, many managers are uncomfortable working with data, let alone big data. They see it as something reserved for analysts or IT specialists. In this issue of the magazine, we’ll show how visual analytics removes that roadblock and puts information into the hands of decision makers.

Take the Hong Kong government, which is using visual analytics to better understand and serve its citizens. The Hong Kong Efficiency Unit analyzes hundreds of thousands of public complaints that come in the form of calls and emails. Paired with population data from the Census and Statistics Department, the Efficiency Unit can develop greater insights and find innovative solutions to address citizens’ needs in a timely manner. (Read more on page 20.)

This interaction between the right people and the right information is where real value lies. And by allowing users to visually explore massive amounts of data in real time, visual analytics shows what rows and columns can’t: connections among data that you never dreamed were linked. Connections that spur the next question and the next, until your view on your company’s business is informed by a completely new wavelength of light. This is bringing big data to life. This very point is illustrated at XL Group, a global insurance and reinsurance company that has used visual analytics to help its analysts and underwriters ask more questions and explore new ways of analyzing risk. Visual analytics is also providing a broader user of analytics throughout the company, putting the power of knowledge directly into the hands of decision makers. (See page 18 to learn more about XL Group.) Not only does visual analytics bring big data to life. It also brings life to big data. As valuable as it is to have new tools for analyzing objective data, the next frontier is the convergence of this data with the world of social intelligence – things like opinions, reviews, evaluations, likes and

The Hong Kong Efficiency Unit is bringing big data to life by using high-performance analytics in a social context to respond in real time. This can be achieved in organizations of all sizes and across all industries. Just consider: • By evaluating numerous scenarios simultaneously, banks can spot opportunities, detect emerging issues and respond in real time to market conditions. • Retailers can personalize offers in real time based on structured and unstructured data from sales and social media, boosting sales. • Public health organizations can prevent or mitigate outbreaks by analyzing and mapping tweets and other social media for mentions of disease symptoms in real time.

• Government groups can better respond to natural disasters; by combining traditional data and social data, they can prioritize resources and relief efforts based on areas of greatest need. In each of these scenarios, visual analytics is the key to unlocking the power of big data. The other organizations featured in this issue – from retailers to airlines – will demonstrate how visual analytics broadens the reach of analytics across the organization and provides an effective way to share insights. It makes data exploration and visualization a possibility for anyone, from analysts to business users. And the information and insights it generates can be shared on mobile devices with the push of a button. With visual analytics, we no longer need to struggle to overcome or work around constraints that belong in the past. By treating data as the asset class it is and connecting it with qualitative information, you can derive greater insights that enable you to challenge, decide and align. Whose hands is your future in? It’s time to take charge, liquidize your big data assets and bring life to your data with visual analytics. IQ

online Read more on Mikael Hagstrom’s blog: blogs.sas.com/mikaelhagstrom

As head of an expanding global team of 4,500 professionals in 48 countries, Mikael Hagstrom is passionate about providing a culture where innovation can flourish, resulting in market leadership for the organization and its customers. He leads SAS’ Europe, Middle East, Africa (EMEA) and Asia Pacific regions, which accounted for 53 percent of SAS’ 2012 revenue, or $1.52 billion.

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Why your brain needs data visualization The benefits of processing information through pictures

According to Research Scientist Andrew McAfee and Professor Erik Brynjolfsson of MIT, the amount of data that crosses the Internet every second is greater than all the data stored in the Internet just 20 years ago. This amounts to exabytes of data being created on a daily basis. If you tried to picture each individual data value that is being generated just in your company, your head would spin. The human brain is incapable of processing hundreds and thousands of variables at once, let alone millions and billions. Yet information can inform and enlighten your business practices, direction and vision. Fortunately, there is something to help your brain not only imagine your corporate information, but consume it. Enter data visualization.

Data visualization is the representation of data in a pictorial or graphical format. The purpose of data visualization is to simplify data values, promote the understanding of them, and communicate important concepts and ideas. Visualizations are the single easiest way for our brains to receive and interpret large amounts of information. Data visualization gives business users the ability to use information intuitively, without deep technical expertise. Even novice users can create data visualizations that are meaningful, such as pie charts, line graphs, bubble charts and heat maps. Advanced data visualizations support more in-depth and complex analytics. A visual tier that sits on top of the analytics program lets users view the results

IQ of complex algorithmic processing. Not only can they get insight into what’s happened, they can forecast what might happen, using rich graphics to quickly derive business actions. The fact is, when people transition from spreadsheets to data visuals, they are able to register the values they are seeing as a whole. Consider the manufacturing director of product reliability for an international company that produces small motors, like the ones you find in toothbrushes, toys or cell phones. Each year the company makes millions of vibrating cell phone motors. One of the director’s principal responsibilities is to determine how reliable the cell phone motors will be with each year of age. If the product’s reliability falls short of the standards set

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common visuals, inviting new conversations around data usage and decisions. In the long run, this collaboration can save time and help bridge some of the decision gaps between business areas.

Figure 1: Multidimensional data about the cell phone motors can be sliced and diced by applying filters on any level of a hierarchy, and forecasts can be generated on the fly.

forth by the cell phone manufacturers who use the motors, his company could lose major contracts. A traditional electronic spreadsheet cannot visually represent the amount of data that is collected on the age and reliability of the cell phone motors. In print, the spreadsheets would look like small mountains on the director’s desk. In both cases, the director would lose countless hours poring over millions of rows of data, and he would still be none the wiser about his original question of the age of the motor and its reliability. Data visualization represents the data in a way that the director can easily interpret, saving him time and energy. For example, Figure 1 shows the number of units that correspond to each age (represented by the color gradient) as well as the reliability as the age of a unit increases. In a matter of seconds, he can see that units approaching 10 years

of age are approximately 40 percent reliable. This visual simplifies the totality of the data, instantly clarifying what is happening with the reliability of the cell phone motors. Regardless of his computer expertise, the director can quickly derive meaning from the data that supports his job function. When the visuals are generated only by a technical user, on the other hand, it can leave a lot open for interpretation. Whether they work at the corporate headquarters or in the field, employees can use data visualization tools to unite around

Mobile applications for tablets increase the sharing and dissemination of data visuals among business users. Web-based applications unchain us from traditional desktop applications and encourage mobility and real-time interaction. Managers, account representatives and executives can all access visual reports and see key performance indicators from anywhere. Having a centralized access point for important reports and indicators minimizes the endless paper and email trails that often result in miscommunication and misinformation. There is no going back. The flow of data will not shrink in the near future; in fact, it will continue to grow exponentially. Time is doing us no favors, and we may not always have access to, or the resources for, all the technical experts that we think we need. Today we can use data visualizations and the advanced analytics that supports them to meet these challenges head on. IQ

online Building reports with SAS Visual Analytics (video): sas.com/iq-vareports ®

Analise Polsky is a thought leader on the SAS Best Practices team. The focus of her work is developing and delivering data quality, data stewardship, culture and change management, and data visualization best practices. She has also created training materials for database and application products, which she has presented to a wide variety of clientele in multiple languages.

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Using visual analytics to support evidence-driven policy decisions A discussion with the Australian Institute of Health and Welfare

What types of injuries result in hospitalization? How does dental care in remote areas compare with that available in urban regions? Is Australia’s medical workforce growing to meet the demands of society? When Australian policymakers ask these types of questions, the Australian Institute of Health and Welfare (AIHW) supplies the answers. As the country’s national agency for information and statistics about health and welfare, AIHW aims to improve the well-being of citizens through better use of information and statistics. Governments and community leaders use information from AIHW to discuss, debate and design policies for health, housing and community services. Warren Richter, Senior Executive for ICT and Business Transformation at AIHW,

IQ recently took some time to discuss the importance of visual analytics in the policy development process, and to describe how big data is affecting the agency’s work. Why is data exploration important for the Australian Institute of Health and Welfare? Warren Richter: Our mission is clear: Provide authoritative information and statistics to promote health and well-being. That’s what we’re all about. We collect, analyze, and disseminate information in the areas of health, age-care services, child-care services, housing assistance, child welfare, and other communityrelated sectors. We have also produced some performance indicators and targets for national agreements.

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Today, it’s not so much what we do with analytics; it’s a question of what we want to do. We have a long history of linking large and complex data sets for research and statistical purposes, and we have recently become one of the first two organizations accredited as an integration authority under the very strict Australian government arrangements for integrating data sets containing sensitive information about individuals. That means, after approval by an independent ethics committee, we are able to produce detailed information for research and analytical purposes. We take this role and our responsibility to preserve privacy and confidentiality very, very seriously. We undertake around 90 data integration operations every year, some of which are extremely complex. These accreditation arrangements enable the Australian government to make more data available for research and analysis. This is going to be of great benefit to the community over time. We are using SAS and SAS Visual Analytics to explore this data.

to make more data available for analysis under strict conditions. But getting data from the Internet is also going to be relevant to us, because we are starting to explore opportunities to access real-time data as a byproduct of administrative operations as they occur, not just as they occurred in the past 12 months or so. Some statistical agencies around the world are taking direct feeds from point-of-sale terminals, for example, so you’re measuring the economy as it’s happening. We think there will be opportunities to do similar things in the health sector. Why did you select SAS for visual analytics? Richter: It boiled down to value for us: whether SAS Visual Analytics could handle the size and complexity of the data sets, whether it was easy to use, and then, of course, whether it supported the analytical techniques and visualization approaches that we require.

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There is a neat convergence of data and capability here – a rigorous confidentiality and accreditation arrangement to free up data combined with the very exciting capabilities of in-memory analytics packages such as SAS Visual Analytics. How does big data influence your work? Richter: Statistical agencies like ours have dealt with big data for a long time, and we can continue to do the traditional analyses with existing tools. But the availability of large and more complex data sets is transforming what we are able to do. In our case, it’s come about not through the Internet, but through the willingness of the Australian government

Instead of focusing on every last whizbang, push-button feature, it was more important for us to be able to use SAS as an extended platform so we can manipulate the underlying data sets and expose the analyses behind the visualizations. It’s about the value for money and enhancing our existing data exploration capabilities. Increasingly, we’re being asked by government agencies to develop such things as clearinghouses of information – not exactly data warehouses but dashboards – that expose a particular sector or area within a sector for access by decision makers. SAS supports that vision. We also want to support decision makers and policy analysts in our client agencies, such as the Department of Health and

7 “We think we can help formulate better policy proposals by giving a much more intimate relationship with, and a better understanding of, the data. The ability to access a very large and complex data set easily and to do a what-if train of thought analysis together with our clients is very exciting.” Warren Richter, Senior Executive for ICT and Business Transformation at AIHW

Ageing. We need to work with agencies on policy problems, providing them with the data they need, when they need it, and helping them draw insights from that data with visualizations. We don’t want to continue just doing what we’ve traditionally done, which is to report on something. We’re getting ready to support them as they explore and understand the data and to help them apply the right analyses. We want to provide even more value than we currently do. Essentially, we aim to help analysts to get the information they need in real time as they do their jobs, rather than make them wait 18 months for a report, which may not even fully answer the question at hand. Can you give a few specific examples of policy areas that will be using SAS Visual Analytics? Richter: Increasingly, we’re supplementing more of our publications and cubes with visualization. And we plan to extend it to develop some new service offerings for our clients to support their decision making. One area in which AIHW is already using visual analytics is the development of new approaches for presenting decision makers with information about mental

health services. We are very excited about the way we can quickly and easily produce dashboards with rich visualizations from very complex and rapidly changing data sets and make them available online. We will be extending this capability to other subject areas very quickly. How might visual analytics be used to identify new types of questions and explore data differently? Richter: You know, if you have a small data set and you want to do some visuals using old-fashioned, run-of-the-mill analytical techniques, you can do that fairly easily. Even in a spreadsheet, you can run a simple regression on a small data set, but it’s not as easy when you’ve got a very large and complex data set to explore. It’s very valuable to be able to say, “Here’s the data – bang – you’ve got it. Let’s start to look at it without having to determine what sampling or subsetting technique to use, and determine if that is valid.” We just don’t have to worry about that now. Before visualization, you had to know exactly what analysts were looking for before you could build your cubes. Now we can make the whole data set available to everyone all of the time, subject to privacy and confidentiality considerations of

course. It’s terrific to be able to get something going very quickly across large and complex data sets as they are created. In conclusion, can you summarize your long-term goals for visual analytics? Richter: We want to use the data that we currently have to shed more light on issues, to describe the real world better by using visualizations, and to support our key clients directly via visual analytics as they make policy recommendations and formulations using real-world data as it is created. We think we can help them formulate better policy proposals by giving them a much more intimate relationship with, and a better understanding of, the data. The ability to access a very large and complex data set easily and to do a what-if train of thought analysis together with our clients is very exciting, and we are looking to develop this as an ongoing high-value service. IQ

online SAS Australia: sas.com/australia Looking at correlations in SAS Visual Analytics (video): sas.com/iq-vacorrelations

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Retail group gains better customer insight with visual analytics SM-MCI analyzes loyalty data to pinpoint key trends that help boost merchandizing and promote customer loyalty

“We’re delighted that SAS continues to be ever mindful of our needs and commits these into the development of new technologies in analytics.” Baldwin C. Golangco, SM-MCI President and Chief Executive Officer

IQ SM Marketing Convergence Inc. (SM-MCI), an affiliate of SM Retail Group, operates one of the largest customer loyalty programs in the Philippines. The loyalty program enables customers to earn reward points when they shop with the SM Group – and it also garners massive quantities of customer purchase and spending data for SM-MCI. In fact, SM-MCI’s current data exceeds a billion transactions. Big potential for key insights With so much customer data at the ready, SM-MCI knew it was sitting on a gold mine that could yield tremendous business insight – but the sheer size of the data proved to be challenging when it came to delivering useful customer knowledge. The company needed a better way to uncover and analyze the information and then put it to use.

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SM-MCI sought a solution that could help boost merchandizing, improve store operations and promote customer loyalty. It chose to implement SAS Visual Analytics, a powerful high-performance solution providing in-memory analytics and advanced data visualization for business intelligence. With the technology in place, SM-MCI could look at patterns in spending, rewards redemption and customer loyalty. The resulting insight would be delivered to affiliate partners, who could then better plan their sales and loyalty strategies. A fast, intuitive solution SM-MCI was faced with a huge undertaking: It wanted to fully analyze the more than 200 million customer transactions that were generated on a yearly basis across more than 500 stores. Once SM-MCI learned what SAS Visual Analytics could do, the retailer knew it was the right solution for the job. SAS not only has unmatched statistical computing power and speed, it also offers an intuitive interface that makes visualizing the information even easier. Plus, it could scale effortlessly from 200 million to more than 1 billion transactions using commodity hardware. SAS Visual Analytics helped SM-MCI analyze customer data and deliver in-depth reports based on SM-MCI’s big data insights. The technology could get the job done without the burden of extensive data planning or ETL reprocessing whenever new variables

needed to be added. It was fast, efficient – and delivered the in-depth analysis that SM-MCI needed to meet its goals. Better analysis leads to better service With data compiled from its customer loyalty program, SM-MCI uses SAS Visual Analytics to understand buying patterns and identify trends, which leads to better service – and greater customer satisfaction. Armed with this insight, SM-MCI improves the customer experience with relevant, timely offers and promotions. It also can work to acquire new members, reduce churn and identify new up-sell opportunities. “We have always regarded SAS as a valuable business partner with the dedication and support your team has shown us over the years,” says SM-MCI President and Chief Executive Officer Baldwin C. Golangco. “We’re delighted that SAS continues to be ever mindful of our needs and commits these into the development of new technologies in analytics.” IQ

online SAS Philippines: sas.com/philippines See it for yourself: Demo SAS Visual Analytics now: sas.com/iq-vademos

Four ways retailers can use visual analytics 1. Drive innovation. Visually explore data to identify previously unseen correlations and patterns that can spark innovative ideas for attracting new customers, growing existing customers’ wallet share, and retaining valuable customers. 2. Localize offers, pricing and assortments. Explore sales, demographic and customer loyalty data to uncover hidden insights that can be used to cater to individuals with localized pricing and assortments. 3. Enhance customer experience. Share analytical insights with store managers and associates who can use the information to offer personalized experiences to customers via preferred channels. 4. Identify and solve supply chain issues. Find hidden supply chain problems by visualizing supply chain data, sales transactions, call center complaints, etc.

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Envisioning the future with data visualization SAS Visual Analytics offers Euramax Coated Products faster access to predictive decisions

The leadership team at Euramax Coated Products knows that the company’s success can depend on understanding and sometimes even redefining the future. One example of this vision? The extraordinary color performance of the world’s largest pre-coated aluminum roof at Ferrari World in Abu Dhabi, United Arab Emirates. The massive, red, logo-shaped structure looks almost like a futuristic ship has landed gracefully in the desert terrain. Another example is the company’s commitment to business analytics and data exploration. “Exploring data helps both our analysts and our decision makers in gauging the dynamics of our industry,” says Peter Wijers, Euramax Business Support Manager. “We’re consistently

striving to improve our processes and detect root causes for discrepancies in results. “Confidence in the quality of our data leads to more rapid and fundamentally sound decisions.” SAS Visual Analytics helps Euramax experience that confidence.

IQ architectural products, transportation and corporate identity design. Euramax’s pre-coated metals cover all kinds of products, from building facades to household appliances, working with some of the most prominent brands in the world.

“With the completeness and the speed of data that SAS Visual Analytics provides,” Wijers says, “combined with its intuitive interface, our analysts can, and will, push themselves to get answers to their questions.”

The company’s objectives in employing visual analytics were to:

More dynamic exploration Euramax Coated Products is a premium coil coater, serving the European, Middle East and Asian markets. Its three coilcoating lines manufacture pre-coated aluminum and steel for applications in

• Enhance mobility, including the ability to carry data out into the field and share it with customers.

• Gain more dynamic reporting and exploration capabilities. • Provide for more probing research.

“We wanted to have our data available at any time, to gain quicker insights and

1 1 “With the completeness and the speed of data that SAS Visual Analytics provides, combined with its intuitive interface, our analysts can, and will, push themselves to get answers to their questions.” Peter Wijers, Euramax Business Support Manager

make better decisions, anywhere,” Wijers says, and to be able to present data in a variety of easy-to-grasp formats. Euramax now employs SAS Visual Analytics in multiple countries to improve production operations and broaden its research and for financial reporting, with more applications being added on an ongoing basis. Drilling down The most common problem with static reporting, Wijers says, is that you can see deviations in the end result but still don’t know the causes. Requests to analysts for detailed information take time and, generally, the more detailed the results, the more questions that are raised. “Often an analyst’s gut feeling is right, but he doesn’t have the means to easily verify it,” he says. “SAS Visual Analytics reporting tools allow users to quickly and easily add filters or drill down to a more detailed level of information.”

“Sticking to those gut feelings can hinder employees in their search for improvement,” Wijers says. “While identifying outliers, visual analytics allows you to see correlations that weren’t expected, and the focus can be put on the real causes.” Road warrior-worthy Equally important to Euramax is the mobility of SAS Visual Analytics. Many Euramax employees travel the world and are regularly confronted with the need for information instantly on their mobile devices, often with no Internet connection available. “With SAS Visual Analytics, the key data is stored with the reports, so access is ensured 24/7, anywhere,” Wijers says. Reports are also designed for the individual user level, allowing Euramax to set up a safe structure for access. “Our people now have what they need, when they need it,” he says.

Focusing on the real causes But sometimes those gut feelings are wrong – and here, as well, SAS Visual Analytics comes in handy.

Wijers is confident of the response as Euramax continues to make SAS Visual Analytics available to more employees: “They’re going to be thrilled to have it.”

Euramax uses Lean Six Sigma teams to analyze and solve issues in processes in a structured manner. While productive, this process often reveals that expectations and gut feelings can’t be proven.

Freedom and flexibility of analysis Wijers sees visual analytics as opening up the opportunity to explore new areas of efficiency and innovation – to answer questions that haven’t previously been posed.

“It’s a common fact that when analysts take a lot of time in offering findings, management’s motivation to request different approaches to the analysis wanes,” Wijers says. “But with SAS Visual Analytics, once the data is loaded, analysts are off and running, without the need for any specialized support. With that level of freedom and flexibility of analysis, answers can be found much faster, and with a higher degree of quality. “The power and ease of use of SAS Visual Analytics will allow our employees to analyze data in a much more efficient way. Now, knowing that all of the reporting is based on detailed flat data, editing a report and searching for root causes in deviations will be easy to do. “Once users understand the power that SAS Visual Analytics offers, they’ll be much more highly motivated to explore the data and offer new insights.” IQ

online SAS Netherlands: sas.com/netherlands Explore manufacturing data in the SAS Visual Analytics demo area: sas.com/iq-mfgdata

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Free access to valuable census data The Statistics Center – Abu Dhabi makes data available to constituents

“This will lead to better use of resources and greater efficiency.”  hanem Al Mehairbi, G Section Head of Statistical Information Systems at SCAD’s Dissemination Department

The Statistics Centre – Abu Dhabi (SCAD) was a newly created agency with a big challenge – conducting a full population census for the Emirate of Abu Dhabi, and making large amounts of that census data publicly available online. SCAD needed a software solution that could allow a broad range of users – experts and otherwise – to access and analyze the data. They decided that the best software to meet their requirements was SAS. “SAS is recognized as an analytics provider of choice for many statistical offices globally,” says Ghanem Al Mehairbi, Section Head of Statistical Information Systems (SIS) at SCAD’s Dissemination Department.

IQ “With the release of the SAS tools, many users will have access to a large amount of valuable census data. Users can now customize statistical data to meet their specific needs, which enables them to make better-informed decisions – leading to better use of resources and greater efficiency.” Adopting proven methods, embracing new ideas SCAD is an independent entity established in 2008 as the main authority handling official statistics in the Emirate of Abu Dhabi. SCAD collects, classifies, stores, analyzes and disseminates statistics for the compilation of social, demographic, economic, environmental and cultural indicators.

1 3 SCAD has been able to adopt best practices from international bodies and leading national statistical organizations. It uses the United Nations Economic Commission for Europe’s Generic Statistical Business Process Model as the underlying framework for its statistical system, but is eager to explore and implement new and cost-effective methods to become a world leader in statistical analysis. SCAD has four main objectives: to develop and organize a statistical system for Abu Dhabi, to contribute to the UAE’s national statistical system, to provide official statistics related to the conditions of Abu Dhabi society, and to support decision makers in the Emirate. “The end result is to make useful information freely available and easy to use,” says Al Mehairbi. The role of this department is to reach out to external users (including other government agencies, businesses and the public) with statistics that help answer their questions. The SIS team facilitates this by providing efficient ways to access and analyze detailed data through the use of specialized software applications. The 2011 census In October 2011, SCAD conducted its first census. It identified several features to incorporate into the online statistical tools that would be available to the public, including: • Ease of use/access. The solution should not require training. It should be intuitive and easy to understand by a range of users. Users should not be required to register or log in. • Spatial representation. The census data outputs needed to incorporate some form of spatial representation. • Sense of community. The ability to learn more about local communities

through census data was a priority. The chosen solution needed to be able to “tell a story” about a self-defined community. • Extract and takeaway. As the Census 2011 data would be made available electronically for the first time, SCAD wanted to make it easy for users to extract and take away the data for further analysis. • Confidentiality. The census must protect the privacy and anonymity of individuals, according to internationally recognized standards. • User skill levels. SCAD recognized that people with different skill levels would use the tools. Therefore any solution would require a layered approach. Better use of resources SCAD used SAS software in the micro and macro analysis of census data, and as the primary tool for statistical dissemination. In addition to using innovative enumeration technologies such as iPads, SCAD developed innovative online tools in SAS for thematic mapping and table building. With thematic mapping, users can select census data and display it over a selected geographical area (such as region, district or sector level). “Spatial views of population characteristics can support many types of decision making,” says Greg Pole, Manager of the Dissemination Department. With community tables, users can go on to create rich tabular information based on the geographical census data. For example, a property developer might want to identify areas with a large concentration of elderly residents in order to decide where to situate new retirement villages; a retail chain might want to identify areas with large numbers of family households to help decide where to locate new stores.

“With the table builder, users can decide how to present the information in a meaningful way for decision makers, with simple drag-and-drop functionality, in English or in Arabic,” Pole says. “There is an additional benefit from the development of the SAS tools, and that is the re-use of the applications for other non-census data sets such as foreign trade and the annual economic survey.” In recognition of its effective and innovative use of SAS software, SCAD was the first government entity in the Middle East to be awarded the prestigious SAS Excellence in Government Award in the Middle East. The award was presented in person by SAS CEO Jim Goodnight. “It was very generous of Jim to visit us,” said Al Mehairbi. “He has had a positive influence on staff in the SIS team and across SCAD generally.” IQ

online SAS Middle East: sas.com/middleeast Celebrate the International Year of Statistics with SAS: sas.com/statistics2013

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Visualize this How do you harness all of your data sources, make sense of billions of rows of data and display it in a way that snaps the big picture into focus and brings trends to life? Answer: SAS Visual Analytics. Designed with business users in mind, this new data visualization technology allows you to spot trends, explore big data and go mobile. See for yourself in these examples or learn more about visualizing data for your industry and your role at sas.com/iq-va

1. Spot trends and opportunities – instantly. Your exploration uncovers a surprising trend: In three regions, sales of Product A are up sharply, and now you want to forecast demand. No need to call IT – just click on “Forecast” and get an answer in moments, not days. Want to add in sales information for other regions or products? You can create hierarchies on the fly.

2. Explore big data. Not an analyst? Not a problem – simply drag and drop data categories onto the visualization pane. In seconds, billions of records are analyzed and intelligent auto-charting displays the best visual for your data.

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3 ways to instantly analyze billions of rows of data.

IQ What can you do with SAS® Visual Analytics? BANKING: Calculate risk across entire portfolio: Analyze risk factors at every transaction level – in milliseconds instead of hours or days. RETAIL: Next best offer recommendation: Look at all sales data, purchase history, social media data and more to quickly create well-targeted offers. MANUFACTURING: Drive better yield, utilization and satisfaction: Proactively identify and resolve product defects, production issues and inefficiencies. TELCO: Faster action against churn: Quickly identify customers at the exact moment they consider switching to a competitor, and take the best action for retention. Bring m-commerce to life through mobile marketing and advertising, payments, transactions, loyalty programs and coupons.

3. Go mobile. You’ve compiled your findings; now drag and drop your charts into a dashboard and simply publish to the Web and mobile devices. Your colleagues can access and drill down into your reports, collaborate using comments, and receive updates seamlessly – anytime, anywhere.

 SAS Visual Analytics: sas.com/iq-va

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Visualizing data makes hearing it easier Telecom Italia answers the call for speed with visual analytics

As Italy’s largest telecommunications provider, and with a notable presence in Latin America, Telecom Italia always looks for ways to improve customer experience. That means delivering the reliable service that subscribers expect today – and knowing which offers they will expect tomorrow. Listen to the data As part of a program to improve customer experience for its 32 million mobile subscribers, the company had to extend and reinforce its ability to monitor network service. To make sense of the enormous amount of unique and varied data at its disposal, Telecom Italia turned to SAS for a way to make wise decisions quickly based on up-to-the-minute trends.

IQ “We need to be able to respond quickly with new and improved offerings to our customers, and to analyze the impact of these offers for the foreseeable future,” says Fabrizio Bellezza, Vice President of National Wholesale Services and Head of Market Development at Telecom Italia. “Analysis that is valuable and makes sense today may be irrelevant tomorrow. And we need to see well beyond tomorrow.” Know the competition To understand how it stacks up to the competition, Telecom Italia needed to define and analyze key performance indicators for mobile network voice and data traffic. In a fast-changing market filled with devices and applications running on different generations of technology, what’s

1 7 relevant today might not be tomorrow. And beating the competition means always knowing the right offer for each customer at the right time. The solution With SAS Visual Analytics, business executives at Telecom Italia can compare the performance between all operators for a key indicator – such as accessibility or percentage of dropped calls – on a single screen for a quick overview of pertinent strengths and weaknesses. Using SAS, Telecom Italia adds in-memory analytics and advanced data visualization to the provider’s geomarketing system, simplifying the decision-support and operational processes that go into technical and commercial planning. “SAS Visual Analytics supports us in identifying network shortcomings and making fast improvements,” Bellezza says. “It also allows us to calculate the statistical correlations between various KPIs for more effective further analysis. “SAS Visual Analytics has allowed us to identify profitable areas that we can strengthen in terms of infrastructure and services to be marketed.” In-depth analysis of KPIs A company whose leadership has always understood the role of sophisticated analytics in monitoring network traffic and performance, in addition to spotting trends, Telecom Italia has used SAS since the 1990s. SAS Visual Analytics allows Telecom Italia to analyze a range of KPIs at different levels of aggregation for both voice and data traffic. These include accessibility, drop rate, call setup time and data throughput, and can be viewed on a single screen.

“This gives us a rapid overview of areas of competitive strengths and weaknesses,” Bellezza says. SAS Visual Analytics allows Telecom Italia to analyze coverage of specific areas and identify possible scenarios as “make” or “buy,” prioritized by cost and benefit. It helps analyze customer behavior and create a predictive model, forecast services and evaluate the profitability of a development area after an investment. A user-friendly format “When initially analyzing data, it’s impossible to predict the questions users may ask – and often even the users themselves are unaware of them,” Bellezza says. “SAS Visual Analytics helps us gain insights by simplifying the transformation of data and enabling us to put it into a user-friendly format.” As a result, decision makers get a more comprehensive understanding of what’s happening in the market, he adds. “We’re very impressed in terms of the usability and flexibility – and time to market, too – of SAS Visual Analytics,” Bellezza affirms. IQ

online SAS Italy: sas.com/italy See what you can do with SAS Visual Analytics: sas.com/iq-playlist

Top benefits of data visualization tools What benefits will you receive from a data visualization package? Respondents to a recent IDG research study cited the following benefits: • Improved decision making 77% • Better ad hoc data analysis 43% • Improved collaboration/ information sharing 41% • Provide self-service capabilities to end users 36% • Increased ROI 34% • Time savings 20% • Reduced burden on IT 15% Read more in the Market Pulse report, Data Visualization: Making Big Data Approachable and Valuable: sas.com/iq-datavizreport

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Sparking questions with visual analytics “Our success is about asking more questions and finding out the answers,” says head of analytics

Kimberly Holmes doesn’t want to put any limits on what analytics can accomplish at XL Group plc. As the Head of Strategic Analytics, Holmes recently selected SAS Visual Analytics to help the global insurance and reinsurance operations at XL Group meet that lofty goal. We spoke with her at a recent SAS event to learn more about the importance of asking questions of your data and to hear about the inspiration she receives from visual representations of her company’s data. “Data visualization will enable us to clearly communicate complex statistical insights to our colleagues and encourage more widespread use of analytics in business planning and decision making across XL,”

IQ she said. Read on to learn more about Holmes and her team at XL Group. How has the insurance industry changed recently? Kimberly Holmes: We’ve seen a major shift in the risk paradigm over the last few years. Risk is growing exponentially, and there are big changes in the information available, how customers operate, and technology. XL is responding by embracing advanced analytics. Do you think the term “analytics” is overused right now? Holmes: The word analytics has become ubiquitous over the last 10 years and is used to describe everything from raw data to management information, to traditional actuarial analysis, to cuttingedge advanced analytics. All of these are

1 9 “Our success depends on asking more questions, finding the answers and using that insight … What SAS Visual Analytics will do is inspire more questions than we ever would have asked before.” Kimberly Holmes, Head of Strategic Analytics, XL Group

important, but to me, analytics is about decision science and being innovative in the data we use and the methods of analysis we use to improve decision making. It’s about being “the chief pattern spotter” and developing creative feedback loops of continual learning. How does your group get “buy-in” for analytics? Holmes: One of the things we do from day one in model development is to work closely with the business. I actually think most of the businesses that work with us would say they had woefully underestimated the amount of time they would spend with us and the decisions they would have to make. We’re a facilitator for them. They make most of the decisions and use our guidance where needed. We work with the business to develop a portfolio approach to implementing analytics. It’s about finding where in the market certain types of risk are being overcharged compared to where the prices should be and creating a strategy out of that. Yes, there will probably be some tough conversations, some rate increases and some non-renewals, but when one door closes another opens. We create a model implementation strategy to generate more of the best business and less of the worst business. Why did you choose SAS Visual Analytics? Holmes: That was a very interesting day when I saw SAS Visual Analytics for the first time. I actually wished I had a tape recorder in my brain for all the ideas that

went through my thought processes as I was watching the demo. Going back to the question of how we can get business buy-in, SAS Visual Analytics embodies the saying, “A picture speaks a thousand words.” If we can show information visually and communicate advanced statistical concepts in a visual way, it will be much more effective than if we present charts and numbers and correlations. Just seeing the demonstration about a fake toy company made me think about a lot of questions we could ask about our business if we were using SAS Visual Analytics. This is key. Our success depends on asking more questions, finding the answers and using that insight. If you don’t ask the question, you’re not going to discover the insight. What SAS Visual Analytics will do is inspire more questions than we ever would have asked before. What types of unexpected outcomes have you experienced using analytics? Holmes: We rolled out four new multivariant predictive models in August for one of our businesses. Fifty percent of the variables in those models are totally new variables that we weren’t considering before, and these variables account for over half of the power of those models. What’s interesting is that sometimes the reaction of an underwriter who’s been underwriting for 20 years is “Well, I never thought of that before.” Or, “How could that be?” We send the message that even if we can’t articulate what the causal relationship in the variables is, the

correlation is there and we have to believe it because it was based on 70,000 policies. How might SAS Visual Analytics help improve your analytics processes even more? Holmes: With SAS Visual Analytics, we’re not going to be getting the abridged version, the CliffsNotes. We’re going to be getting the whole story, and it’s a big story, telling us the why. That’s the most important thing. Knowing what happened is important, but if you don’t know why things happened, you don’t know what to do to make things better going forward. IQ

online How visual analytics inspires more questions: sas.com/iq-vainspire

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Visual analytics helps solve public complaints Hong Kong government group gets faster results to better understand needs of its citizens

“We aim to serve citizens more efficiently. The less time we spend analyzing data, the more time we can spend better understanding things.” W.F. Yuk, Assistant Director, Hong Kong Efficiency Unit

IQ In an effort to keep improving the quality of public services, the Hong Kong Efficiency Unit created its 1823 Call Center to hear citizen complaints. With 300,000 complaints coming in each year, the call center stays busy routing public feedback to the right department for follow-up action. By the time the call center had collected a million complaints, the Efficiency Unit knew it needed a more efficient way to handle its big data. So the Efficiency Unit turned to SAS Visual Analytics for a high-performance, in-memory solution for exploring all its data quickly to spot patterns, identify opportunities for further analysis, and convey visual results via Web reports, iPad or Android tablet. ®

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visualize big data to anticipate, address public complaints Given the substantial volumes of complaints data the 1823 Call Center receives, visualizing the data is critical to drawing rapid insights that can enable more informed decisions.

• Uncover hidden relationships between words and sentences of complaints information.

Using SAS Visual Analytics in extension with SAS Text Analytics, the Efficiency Unit is able to:

• Produce high-quality complaints intelligence for the departments it serves.

“We aim to serve citizens more efficiently and timely,” says W.F. Yuk, Assistant Director at the Efficiency Unit. “The less time we spend analyzing data, the more time we can spend better understanding things.”

“With in-memory analytics, the Efficiency Unit gains faster calculations that return results in minutes – not the hours or days that it used to take. Now that we can run data with different combinations to analyze each possibility, we get more comprehensive results. Our staff no longer has to do any preparation work.”

From one month to a few minutes Of the Efficiency Unit’s 100 employees, 10 analysts have been dedicated for several years to using SAS to analyze government data. The onslaught of big data meant they needed a more effective and efficient way to do their job. “The traditional way of analyzing required a lot of preparations, such as choosing data and analyzing modules, and each execution takes a few hours, or even the whole day,” Yuk explains. “If the chosen data is not ideal, it wastes a lot of time. A larger analyzing module can even take up to a month for the results to be delivered.

• Spot emerging trends, patterns and public concerns.

As a result of the improved level of quality in decision-support data, the Efficiency Unit created the Barrier-Free Project to improve public accessibility for the elderly, disabled and children. Using population data and geographic information from the Census and Statistics Department, analysts can recommend the best locations to install elevators, for example.

Moreover, senior management can generate and interact with reports, charts and graphs via mobile devices to make more informed decisions from any location. This ultimately helps government departments improve service delivery and develop smart strategies that, in turn, help boost public satisfaction with the government.

“Our new analytic solution can simplify results and send reports via email and mobile devices, which means we do not have to print and deliver hard copies to each department,” Yuk says. “This technology can help us better understand the needs of our citizens.” IQ

online SAS Hong Kong: sas.com/hongkong Read thought leaders’ discussions on visual analytics: sas.com/iq-vavoices

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IQ

The secrets to big data computing How visual analytics plays a role

Oliver Schabenberger, Randy Guard and Jim Goodnight present SAS Visual Analytics. When SAS CEO Jim Goodnight talks about the development of SAS High-Performance Analytics, he always starts with the customer. After all, it was banking customer UOB in Singapore that first approached Goodnight three years ago about reducing the time it took to calculate risk factors on the bank’s full portfolio. ®

After that initial conversation with UOB, Goodnight came back to SAS headquarters in Cary, NC, and started experimenting with risk calculations. The risk problem he was addressing was analyzing 20,000 risk factors for thousands of possible market states. “Looking at how many computations had to be done, the rough estimate was about 200 trillion operations,”

says Goodnight. Three years ago, chips were running at 2 billion computations per second, so Goodnight knew he wasn’t going to solve the problem on a single processor. So he gathered 1,000 computers and told each one of them to build 20 rows. “Everything we do in statistics is a row operation. That can be done by taking the row you want to operate on to all the other processors,” says Goodnight. “That’s the secret to how you do big data computing. You simply scatter it out over 1,000 machines.” Goodnight likes to tell this story when he demos SAS high-performance and visual analytics products along with Oliver Schabenberger, lead architect for SAS

“Some business users have appreciated that both descriptive and predictive analytics are available in one easy-to-use solution. This gives customers the ability to expand the use of analytics in their organization to business users who don’t have advanced analytics degrees.” Jim Goodnight, SAS CEO

High-Performance Analytics and Randy Guard, VP of Product Management. “SAS has reinvented the way that we view data yet again,” says Goodnight while demonstrating some of newest developments that R&D is working on for big data and high-performance analytics. The UOB story is important not only for showing the thought processes behind developing SAS High-Performance Analytics but also because it shows the customer-driven aspects of the development efforts.

platform the same way that you would with Base SAS, and the results come back to you as if you had executed on your desktop.” And that’s doing logistic regression on a billion records in memory and in parallel. Visual analytics on not-so-big data After re-engineering most SAS procedures for the high-performance environment, Schabenberger’s team turned their attention to the next set of customer requests, including, “What if I don’t have a billion rows or 48 blades? Can you bring this down in size?”

During the presentation, it is clear that the same customer-driven philosophy continues today. Not only have the high-performance development efforts addressed problems that customers have brought to SAS, says Schabenberger, but the development has been done in such a way that customers can still work with SAS in the same ways they always have.

To that, Schabenberger says, “We went big first. But we can also scale down.” He then gave a demonstration of the scaled-down version of the product. New features for that release will include:

Instead of making customers learn new coding techniques to work with big data, SAS has re-engineered the highperformance products on the back end.

• A way to “bookmark” output statements and pass them in-memory to another location.

“SAS Visual Analytics uses an entire rack of blades and operates on a billion records by allocating a million records to each process,” says Schabenberger, “but you interact with this large in-memory

• The ability to partition data as you load it. • A new in-memory statistics procedure.

Guard concludes the demo with realworld examples of SAS Visual Analytics analyzing billions of records on the iPad. One example is a fictitious report of customers with drill-down capabilities to view high rollers. This type of report

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2 4 could be used by a customer service advocate to review purchase histories and preferences for top customers. (See figure 1.) Another example shows risk data, including a summary of all capital returns and a view of counterparty exposure via a heat map. Schabenberger concludes, “This is not an in-memory database. It’s a very well thought-out plan to deliver analytics as quickly as possible. It doesn’t just allow you to do things fast but to do things smart. And it lets you attack problems you could not do before.” IQ

online Watch Jim Goodnight demo SAS Visual Analytics: sas.com/iq-ceodemo

Figure 1: This mobile report shows the casino’s high rollers and displays revenue by source.

SAS CEO shares visual analytics with customers CEO Jim Goodnight has been showing demos of SAS Visual Analytics on stage at events and at customer sites over the past year. We checked in with him to see what the reactions have been. What is your favorite part of the product to demonstrate on stage? Jim Goodnight: I like to select a data set with 1.1 billion rows and about 50 variables and then show how to create plots and charts by just dropping variable names on the screen. And it only takes about 2 seconds, so I remind the audience that we just did that on 1.1 billion records. Next, to build charts and tables that you can drill down on, I show how simple it is to define a hierarchy, then build the charts and plots in seconds.

What are customers telling you about SAS Visual Analytics? Goodnight: The response from our customers has been tremendous. They really appreciate the ease of use and that SAS Visual Analytics makes them self-sufficient. They love the drag-and-drop interfaces, which make data exploration and visualization a possibility for anyone in their organization. How is it different from other products they’ve used for visualization? Goodnight: Many users have commented on how easy it is to design reports that look good and that show up well on mobile devices.

Some business users have appreciated that both descriptive and predictive analytics are available in one easy-to-use solution. This gives customers the ability to expand the use of analytics in their organization to business users who don’t have advanced analytics degrees. Hear more of what Jim Goodnight has to say about visual analytics: sas.com/iq-goodnightva

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The sky is the limit Fraport takes off with SAS High-Performance Analytics and SAS Visual Analytics ®

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“It’s as if they created SAS High-Performance Analytics with us in mind.”  ieter Steinmann, Senior Manager D of Business Systems, Fraport AG

With nearly half a million takeoffs and landings, more than 50 million passengers, and over 2 million tons of freight each year, Frankfurt International Airport is one of the largest air traffic hubs in the world. And all signs point to continued growth. A SAS Business Analytics solution has formed the backbone of the airport’s operations for many years now, providing real-time information on the status of all key processes and factors used in operational decision management. The system is used to help answer a range of questions such as: Are there any delayed flights, and if so, how can we keep the rest of the flight schedule from being affected? Which parts of the airport are running according to plan, and where have difficulties arisen? How will the weather affect operations?

IQ For quite some time, Frankfurt Airport owner and operator Fraport has taken full advantage of business intelligence and analytics, using the most advanced technology available to manage its business. Now, Fraport has decided to take things a step further. The company is planning to migrate its existing business analytics environment to SAS HighPerformance Analytics. Fraport is pursuing two major objectives with the migration: First, it is seeking to reduce the total cost of operation in part by eliminating existing third-party systems within the system environment. Secondly, Fraport wants to boost its analytics performance. “We have to analyze enormous quantities of data in real time. It’s as if they created SAS High-Performance Analytics with us

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Make analytics more approachable Visual analytics extends the use of sophisticated analytics to a broader range of individuals in your organization, from the expert to the amateur. Data scientists and other data handlers can explore all of their data and the relationships between data elements really fast. Billions of rows can be manipulated in seconds, and advanced analytics such as regression analysis can be performed. Business analysts, who are dependent on data scientists through much of the early stages in the analytics life cycle, can do their own data exploration because SAS Visual Analytics is easy to use and the results, as the name implies, are displayed visually in the most appropriate format. Nontechnical users can quickly view and interact with reports via the Web or mobile devices, while IT maintains control of the underlying data and security. Day-to-day insight for everyone: sas.com/iq-va

in mind,” explained Dieter Steinmann, Senior Manager of Business Systems at Fraport AG. “In addition to the increased speed, we were also pleased with the new ability to explore and visualize data with SAS Visual Analytics.” The airport presents an ideal application scenario for SAS Visual Analytics, since its biggest challenges involve analyzing very rapidly changing situations within very short amounts of time to make decisions quickly. Labor strikes, extreme weather or other natural phenomena require quick reactions, sometimes in response to situations that have never been encountered before. SAS Visual Analytics’ self-service approach – in combination with the integrated data exploration and visualization capabilities – plays a central role here. The larger the user base is, the greater the flexibility that can be attained for performing and evaluating analyses. Using data exploration, hypotheses can be quickly tested without the assistance of IT staff. Particularly in exceptional circumstances, this capability can be the difference between success and failure. Visualizing the results makes it possible to rapidly detect outliers, deviations and complex relationships, thus improving the decisionmaking process. In addition to the ad hoc analyses necessary for ongoing operations, Fraport also uses SAS Analytics for medium- and long-term strategic airport operations planning. How will passenger numbers change over the next few years? Which trends are visible for international routes? Which factors are affecting the efficiency of airport infrastructure utilization such as retail, restaurant and office space; what are the consequences? Using SAS, Fraport

can answer these types of questions so that it can prepare for the world of tomorrow, today. More data provides a more detailed view of performance In addition, Fraport benefits from being able to measure and evaluate considerably more sensor data with SAS Visual Analytics than was previously possible. “This gives us the ability to analyze the performance of the airport in unprecedented detail – as a result, we can manage it with much greater precision,” observed Steinmann. These capabilities help Fraport use its improved efficiency to further extend its competitive advantage in the highly competitive world of international air traffic. “I see Fraport AG as the poster child for an organization that lives and breathes analytics,” said Wolf Lichtenstein, Vice President DACH Region at SAS. “The decision makers at Fraport have recognized that analytics translates directly to a company’s future viability. Fraport is setting an industrywide benchmark.” IQ

online SAS Germany: sas.com/germany How-To: Effectively Realize Data Visualization webinar: sas.com/iq-datawebinar

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Data visualization made easy Learn to autochart and filter with visual analytics

“The greatest value of a picture is when it forces us to notice what we never expected to see.” John W. Tukey, Exploratory Data Analysis, 1977

John Wilder Tukey, a mathematician who first coined the term “exploratory data analysis,” was right when he suggested that the idea of visualization helps us see what we have not noticed before. That is especially true when you are trying to identify relationships and find meaning in huge amounts of collected data. Sure, analyzing the data can tell the story, but wouldn’t seeing the results help you more easily grasp the meaning? Analyzing data and displaying the results with graphs and charts makes patterns, trends and outliers easily visible. For example, what if you had data on cell phone use? Using basic bar chart techniques, you could likely spot some interesting correlations. You might notice that areas with certain types of networks experience more dropped calls. Another analytic visualization could show

IQ opportunities for growth in a particular region. Analytic visualizations are critical to gaining fast insights from your data. If sophisticated analyses can be performed quickly, even immediately, and results presented in ways that showcase patterns and allow for querying and exploration, people across all levels of your organization can understand and derive value from massive amounts of data faster than ever before. Drag and drop – it’s an autochart So, it’s clear to see the value offered by data visualization. But what about creating the visuals? Especially when working with large amounts of data, it can be difficult to decide which graph is best to use. In SAS Visual Analytics, intelligent autocharting produces the most

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Filter for added focus When working with massive amounts of data, being able to quickly and easily filter the data is important. What if you only want to view data for a certain region, product line or some other variable? Filtering makes it easy to refine the information you see. In SAS Visual Analytics, you simply add a measure to the filter pane or select one that is already there, and then select or deselect the items to filter.

Figure 1: This cash flow analysis is displaying revenue, profits and expenses – and forecasting each into the future. For more details, read the “What does this mean?” pane. appropriate visual based on what data you drag and drop onto the visual palette. If autocharting does not create the exact visualization you had in mind, you can select a specific visual to build. However, when you are first exploring your data, autocharts are useful because they provide a quick view of the data. This automation opens up the world of visualization to business analysts and nontechnical users, enabling them to interactively explore and drill through data and display it in many different ways to answer different questions. “What does this mean?” pop-up boxes also make visualizing your data easier by providing explanations of complex analytic functions that have been performed, as well as identifying and explaining the relationships between the data variables that are displayed. (See figure 1.)

But what if the filter isn’t meaningful or it skews the data in undesirable ways? One way to better understand the composition of your data is to use histograms. Histograms provide a visual distribution of the data with cues for how the data will change if you filter on a particular measure. This gives you an idea of the effect a filter will have on the data before you apply it to your entire analyses. (See figure 2.) Rather than relying on trial and error or instinct, you can use the histogram to help you decide which areas to focus on. Share what you see Creating data visualizations is all about communicating meaning. So share your ideas. Ask questions of others. Make observations. Easy-to-use collaboration capabilities promote idea sharing while saving valuable time. You can easily annotate screen captures of your visualizations and reports, then email them to others, who can add their thoughts as well. Or capture your comments via video and audio, and share them that way. Data visualizations are great for showing and sharing information.

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Figure 2: This visualization displays retail data by region. Histograms of the data appear in the right panel to provide a quick overview of product lines and distance. Visualizing your data can be both fun and challenging. If you are working with big data, it is easier to understand information in a visual instead of a large table with lots of rows and columns. However, with the many visually exciting choices available, it is possible that the visual creator may end up presenting the information using the wrong visualization. In some cases, there are specific visuals you should use for certain data. In other instances, your audience may dictate which visualization you present. In the latter scenario, showing your audience an alternative visual that conveys the data

differently may provide just the information that’s needed for them to truly understand what it all means. IQ

online Data Visualization Techniques white paper: sas.com/iq-datapaper

Stuart Nisbet is a Vice President of Research & Development for SAS. He directs the development of SAS Enterprise BI and SAS Visual Analytics products, iOS mobile application development, statistical and business graphics, device drivers, reusable component libraries for all SAS solutions, the SAS Output Delivery System, and the SAS Retail Space Management suite.

Tips for Generating the Best Visualizations for Your Data • Understand the data you want to visualize. • Determine what kind of information you want to convey. • Know your audience and how it processes visual information. • Use a visual that presents the information in the best and simplest form.

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Bringing big data to life blogs.sas.com/ mikaelhagstrom

Why your brain needs data visualization sas.com/iq-vareports

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Visual analytics supports policy decisions sas.com/iq-vacorrelations

Gain greater customer insight with visual analytics sas.com/iq-vademos

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Envision the future with data visualization sas.com/iq-mfgdata

Free access to valuable census data sas.com/statistics2013

Visualize this: Snap the big picture into focus sas.com/iq-va

Visualizing data makes hearing it easier sas.com/iq-playlist

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Secrets to big data computing sas.com/iq-ceodemo

The sky is the limit sas.com/iq-datawebinar

Spark questions with visual analytics sas.com/iq-vainspire

27 Data visualization made easy sas.com/iq-datapaper

Visual analytics helps solve public complaints sas.com/iq-vavoices

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