WHITE PAPER

How Governments are Using the Power of High-Performance AnalyticsFaster, smarter decisions for better outcomes

SAS White Paper

Table of Contents

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Survey Highlights . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

Respondent Profile . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

Summary of Findings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Emerging Trends Revealed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

Government Can Seize the Opportunities Big Data Presents . . . . . 13

Benefits of High-Performance Analytics . . . . . . . . . . . . . . . . . . . . . . . 13

Integrating and managing information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

Making faster decisions through integration with Hadoop . . . . . . . . . . . . . . . . 14

Visualizing big data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

Government Big Data in Action . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

Fraud, waste, abuse and improper payments . . . . . . . . . . . . . . . . . . . . . . . . . 15

Cyber security . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

Making the Case for Change . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

SAS in Government . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

For More Information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

1

How Governments are Using the Power of High-Performance Analytics

IntroductionTo better understand the maturity level of analytics use in the US federal government, SAS and the Government Business Council (GBC) conducted a research study, with the goal of providing insight into how federal managers are using analytics in their decision-making processes .

The results of this study revealed that overall, government is complying with data-driven, decision-making requirements; but is doing so with simple reporting and querying techniques . And while a small percentage of agencies are using more advanced analytic techniques like predictive modeling and optimization, a larger percentage are not .

As the federal government acquires and engages with more big data, it is adopting analytics as a means to glean insight from this abundance of data . Big data is now at a higher magnitude than it was in the past – and far more complex . It’s digital, geographic or sensor; and it’s no longer just structured rows and columns – it’s unstructured, semistructured and requires different approaches .

Given the potential, why isn’t a larger percentage of government doing more analysis with big data? “Operational data, a byproduct of everyday government activities, is a treasure trove of data,” according to Dominic Sale, Senior Policy Analyst at the Office of E-Government and Information Technology, Office of Management and Budget (AFCEA Big Data Symposium, 2013) . “We should be using data to identify problems in programs long before they fail .”

Some agencies have been proactive by using extreme information management and high-performance analytics to dig deeper into their data . By doing so, they gain new insights to achieve their missions and greatly increase operational efficiencies and effectiveness . Subsequently, they’ve been able to reduce costs and where relevant, increase revenues . This is a move from reactive to predictive . There are instances where agencies are taking advantage of huge volumes of data by processing it incredibly quickly through parallel processing that utilizes in-memory and in-database technology to avoid delays caused by moving data from place to place . These agencies are creating best practices for agencies to follow when it comes to choosing the best data for decision making .

The study summarized in this paper was conducted in September 2012 . Since then, automatic budget cuts (“sequestration”) have already permanently affected the way the US government operates . Government must become leaner – and using big data with analytics is a means to more efficient government . After reviewing the survey data, this paper provides an explanation of the technologies to make all this possible .

2

SAS White Paper

Survey Highlights

Methodology

From Sept . 17, 2012 to Sept . 28, 2012, GBC launched a survey to a sample of federal managers, targeting a wide array of GS levels and areas of responsibility . This included respondents identifying themselves as either “consumers” or “producers” of data analysis . More than 140 federal managers responded to the survey .

Respondent Profile

• TheGBCdivisionreleasedasurveyinSeptember2012toasampleofGovernment Executive print and online subscribers from defense and civilian agencies .

• Atotalof144federalmanagers,fromGS-11toSeniorExecutiveServicegradelevels completed the survey .

• Almostthree-quarters(71percent)ofrespondentsareGS/GM-13oraboveand69percent oversee at least one direct report .

5%

22%

22%

22%

22%

6%

1%

SES

GS/GM-15

GS/GM-14

GS/GM-13

GS/GM-12

GS/GM-11

Other

71%

of respondents are GS/GM-13

or above.

Figure 1: Job/Grade Rank.

3

How Governments are Using the Power of High-Performance Analytics

69%

of respondents oversee at least 1 direct report

31%

22% 25%

11% 10%

1%

None 1-5 6-20 21-50 51-200 Over 200

Figure 2: Oversees/Reports

• Respondentsincludeexecutivesfromvariousareasofresponsibility.Thelargestgroup of managers work in operations, followed by agency leadership, technical and human capital occupations .

• Inrelationtoproducingorconsuminganalytics,most(51percent)respondentsindicate they are managers or decision makers . More than a third (34 percent) note they are analysts or data miners .

39% of

respondents indicated they

were in operations.

1%

4%

8%

12%

12%

13%

15%

19%

39%

Legislative

Information Technology

Facilities and Fleet Management

Other

Finance

Human Capital

Technical

Agency Leadership

Operations

Figure 3: Area of Responsibility.

4

SAS White Paper

13%

28%

2%

6%

Other

Manager

Analyst

IT systems/ management

Data miner/statistician

51%

Figure 4: Role in Producing Analytics.

Departments and agencies represented (in order of frequency):

• DepartmentoftheArmy

• DepartmentoftheAirForce

• DepartmentofDefense

• GeneralServicesAdministration

• DepartmentofAgriculture

• DepartmentofTreasury

• DepartmentofHomelandSecurity

• DepartmentoftheNavy

• DepartmentofVeteransAffairs

• DepartmentoftheInterior

• OtherIndependentAgency

• EnvironmentalProtectionAgency

• DepartmentofCommerce

• DepartmentofEnergy

• DepartmentofHealthand HumanServices

• DepartmentofHousingandUrbanDevelopment

• DepartmentofJustice

• DepartmentofJustice

• DepartmentofState

• DepartmentofEducation

• DepartmentofTransportation

• NationalAeronauticsand Space Administration

• NuclearRegulatoryCommission

• SmallBusinessAdministration

• USAgencyforInternationalDevelopment

• USGovernmentAccountabilityOffice

• UnitedStatesMarineCorps

5

How Governments are Using the Power of High-Performance Analytics

Summary of Findings

Despite a renewed emphasis in government on performance metrics and data analytics, both managers and analysts report challenges in the time it takes to create meaningful analysis.

Data analysts and federal managers differ in their decision-making practices . Management notes that they use prior experience while analysts indicate that they rely ondata-drivenanalysistomakedecisions.Amajorityofanalysts(55percent)notethat their agency has trouble turning data into useful information, which may delay the process of delivering data analysis to government leadership . In fact, two-thirds of managers report that they receive data too late to be helpful .

Simple methodologies dominate current analytics capabilities. But a faster solution could open the door to more use of advanced analytics.

Seventypercentofanalystsand67percentofmanagersindicatedtheyrelyheavilyonsimple reporting, thus not taking advantage of more sophisticated techniques . And 50percentofmanagersreportedthattimeisachallengetoleveragingthepowerofanalytics . Advanced analytics can provide agencies the insight they need to not only assess performance, but also make data-driven decisions .

Agencies may lack the skills necessary to implement more complex analytic methodologies.

Of those managers using analytics, the simplest methodologies are most commonly used.Forexample,96percentofthefederalmanagerswhousepredictiveanalyticsuse it for simple forecasting purposes . More complex analytics methodologies, such as social network analysis, text mining and optimization models were used less frequently . This may be explained by a lack of analysts with the requisite skills, as half of federal managersnotethisasachallengetousinganalytics.High-performanceanalyticsareanimportant potential resource for federal managers who need to make decisions smarter and faster .

Managers rely on prior experience in decision making

“... Data is a powerful tool to determine results. We can’t ignore facts. We can’t ignore data.”

-President Barack Obama (July 24, 2009)

• Althoughmanagershavebeentoldtofurtherincorporatedataintodecisionmaking, managers still place higher importance on prior experience than on data-driven analysis . Despite this, analysts (which include data miners and statisticians) prefer data-driven analysis to make decisions .

6

SAS White Paper

Management Analysts

1 Prior Experience 1 Data-Driven Analysis

2 Data-Driven Analysis 2 Prior Experience

3 Advice or Direction of a Superior 3 Advice or Direction of a Superior

4 Intuition 4 Intuition

Figure 5: Comparing Factors in the Decision-Making Process. Percentage of

respondents, n = 144.

Both analysts and managers have trouble turning data into useful information

• Asthefirstgraphshows,amajorityofbothmanagers(64percent)andanalysts(55percent)agreedthattheiragencyhastroubleturningdataintoinformationtheycan use .

• Afulltwo-thirdsofmanagers(67percent)notethatthetimeittakestoreceive data analysis is a challenge . The majority of respondents indicated that they don’t receive data analysis, receive it too late to be useful, or have to wait for it to be provided .

“Agree or Strongly Agree”

55%

Managers

Analysts

64%

Figure 6: Trouble Turning Data into Useful Information. Percentage of respondents, n = 144.

Combined 67%

of managers have to wait for data analysis to

be provided

5%

I receive data analysis in

plenty of time

14%

I don't receive data analysis

28%

I receive data analysis when I

need it

44%

I have to wait

for data analysis to be

provided

9%

I receive data analysis too

late to be useful

Figure 7: Timeliness of Data Analysis. Percentage of respondents, n = 144.

7

How Governments are Using the Power of High-Performance Analytics

Despite challenges, managers and analysts rely on data analysis for performance assessments

• Withregardtothemanyusesofdataanalysis,managersmostcommonlyuseperformancemetrics(69percent)andanalysistosupportprograms(62percent).

65%

67%

69%

48%

43%

24%

11%

69%

62%

56%

59%

50%

24%

5%

Performance metrics/set benchmarks and goals

Analysis to support programs or initiatives

Reports based on historical data

Forecast based on historical data

Day-to-day operations

Advanced statistical analysis for program-level reporting or strategy

Assess bureaucracy

Analysts Managers

Figure 8: Uses for Data Analysis. Percentage of respondents, n = 144.

8

SAS White Paper

Managers don’t take advantage of sophisticated analysis techniques

• Thesimplestanalyticprocessesaretheonesmostcommonlyusedbymanagers.Thehighestnumberofmanagersreportusingsimplereporting(67percent),statisticalanalysis(59percent),andquery(54percent).

• Moreadvancedorcomplexanalysismethodsareusedlessfrequently,suchaspredictive analytics, optimization models, social network analysis and text mining .

70%

67%

65%

48%

20%

15%

19%

67%

59%

54%

32%

18%

10%

4%

Simple reporting

Statistical analysis

Query

Predictive analytics/data mining

Optimization models

Social network analysis

Text mining

Analysts Managers

Figure 9: Common Methodologies. Percentage of respondents, n = 144.

9

How Governments are Using the Power of High-Performance Analytics

Respondents report limited commitment to analytics

• Only19percentofrespondentsnotedthattheiragencyusesanalyticsregularly.

• Morethanhalfofallrespondents(56percent)donotfeeltheiragencyisworkingtoward a culture of analytics .

56% of respondents note leadership is

not fostering a culture of analytics

19%

•  Limited interest in analytics by senior leaders

27%

•  Management pushes for analytics only when needed

10%

•  Senior leaders are planning a broad analytics capability

8%

•  Agency-wide analytics is under development as a priority

19%

•  Agency routinely uses analytics and is constantly improving capabilities

Figure 10: Agency Commitment to Analytics. *Don’t know/none of the above – 17%. Percentage of respondents, n = 144.

10

SAS White Paper

Forecasting dominates use of predictive analytics

• Thoserespondentswhoreportedthattheyusepredictiveanalyticsordataminingin their agency were further asked about their specific uses .

• Almostallfederalmanagers(96percent)usepredictiveanalyticsforforecastingpurposes,comparedtoasmallermajorityofanalysts(69percent)whousepredictive analytics for forecasting . Federal managers may prefer forecasting in their predictive analytics toolkit more than analysts as it may help with mission goal-setting .

35%

27%

8%

23%

96%

69%

52%

24% 28%

8%

Forecasting Root cause analysis

Fraud detection

Web analytics

Behavioral targeting

Analysts Managers

Figure 11: Uses for Predictive Analytics. Percentage of respondents, n = 51.

11

How Governments are Using the Power of High-Performance Analytics

Analysts and managers differ significantly in challenges to using analytics

• Decisionmakersandanalystshavedifferentopinionswithregardtowhathinderstheir organization from using data to guide decisions .

• Analystsaremorelikelytociteinsufficienttechnicalandsystemresourcesasabarrierthanmanagers(46percentvs.35percent).Moreimportantly,analystsare more than twice as likely to state that use of data is not a leadership priority comparedtomanagement(46percentvs.22percent).

50%

48%

35%

46%

46%

46%

28%

35%

35%

50%

40%

50%

45%

35%

22%

36%

32%

28%

Lack of employees with relevant skills and training

Difficulty interpreting data

Not enough time

Complicated processes and restrictions

Insufficient technical and system resources

Not a leadership priority

Lack of dedicated data analysts

Insufficient funding for this specific function

Colleagues reluctant to act on information

Analysts Managers

Figure 12: Challenges to Using Analytics. Percentage of respondents, n = 144.

12

SAS White Paper

More access to quality data and automated processes likely to improve performance

• Amajorityofmanagers(68percent)andanalysts(69percent)feelmakingdataavailable and more accessible to users faster would improve performance .

• Inadditiontogreateraccesstodata,managersandanalystsbelievetheirperformancewouldbeimprovedbygreaterautomatedprocesses(58percent,50percentrespectively),andamajorityofanalysts(52percent)feelincreaseddatavisualization capabilities would also improve performance .

69%

50%

52%

46%

26%

30%

17%

68%

58%

46%

36%

33%

26%

9%

Making data available and more accessible to users faster

Less manual intervention/more automated processes

Data visualization

Faster responses to requests

Create my own output/reports

Access it from Web or mobile device

Incorporating the analysis of unstructured data from new types of media such as Twitter or Facebook

Analysts Managers

Figure 13: Improving Performance Through Analytics. Percentage of respondents, n = 144.

Emerging Trends Revealed

Three key considerations emerged from the survey data to imply that the time is now for government to harness relevant data and use it to make the best-informed decisions it can to better serve and protect citizens and the country:

1 . With regard to data analytics, time is of the essence. Both federal managers and analysts indicate that the time it takes to deliver data analytics is impeding their ability to turn analysis into useful information .

13

How Governments are Using the Power of High-Performance Analytics

2 . Agencies would benefit from predictive analytics. When agencies are conducting data analysis, it’s often through reactive methodologies such as simple queryandreporting.High-performanceanalytics,however,canhelpagenciesmake more accurate and proactive decisions .

3 . Agencies should utilize insights gleaned from high-performance analytics to achieve mission goals.High-performanceanalyticsoffersagenciesthecapacityto see trends in near-real time, granting new insights and the ability to predict with greater accuracy and certainty . Such insights can also help managers fill resource gaps, operate more efficiently, and make more proactive decisions about how to accomplish mission goals .

The constant pressures to improve service and stay within budget require that government agencies not only understand big data to decipher the information that counts, but also – more importantly – the possibilities of what can be done with it using big data analytics .

Government Can Seize the Opportunities Big Data PresentsThe US federal government collects data on just about everything, and it is one of the largest repositories of structured and unstructured data on earth . Many agencies are drowning in data that they can’t get sufficient value out of because there is just so much of it . But buried within this national asset of data is valuable insight into a variety of issues government is challenged with on a daily basis .

All of that data isn’t worth anything unless it can be put to good use to help agencies achieve their missions efficiently and effectively . In terms of program budgetary issues and the need for resource optimization, government agencies cannot afford to put off exploring and analyzing their big data . They must take advantage of the value that big data and its attendant insights can bring . And the time is now .

Currently, the Obama administration has created a data-driven decision-making policy and supports open data and transparency initiatives . IT reform is well on its way and “cloud first” is no longer rejected as a passing trend . Computing costs have decreased significantly . Storage and memory costs have plunged and the cloud offers many alternatives.Open-sourceinitiativeslikeHadoopandMapReducearenowcommonlyaccepted . In fact, technologies today not only support the collection and storage of large amounts of data, they also provide the ability to understand and take advantage of its full value, which can help government run more efficiently and effectively .

Benefits of High-Performance Analytics

For more than 37 years, SAS has worked with government agencies, seeking innovative solutions to their most pressing issues . The complexity of the analyses required has never been a barrier, but processing speed has . As the need to solve larger problems and tackle more complex scenarios evolves, high-performance analytics can be the enabler to fact-based decision making .

TheWhiteHouseOfficeofScienceand Technology Policy (OSTP)—in concert with several Federal departments and agencies—created the Big Data Research and Development Initiative to:

- Advance state-of-the-art core technologies needed to collect, store, preserve, manage, analyze, and share huge quantities of data .

- Harnessthesetechnologiestoaccelerate the pace of discovery in science and engineering, strengthen our national security, and transform teaching and learning; and

- Expand the workforce needed to develop and use Big Data technologies .

Whitehouse .gov

14

SAS White Paper

Integrating and managing information

Traditional data management strategies will not scale to effectively integrate and govern big data for high-performance analytics . As a result, many government organizations are evolving their enterprise information architectures to be able to quickly answer their complex questions . The ability to combine, cleanse and transform huge quantities of data using a range of data integration technologies can be enabled by a variety of high-performance analytics options like grid computing, in-database processing and in-memory processing . SAS® enables you to prepare big data (e .g ., including the Hadoop distributed file system) to make analytical discoveries, create models and deploy them to quickly operationalize insights .

Making faster decisions through integration with Hadoop

Managing large amounts of data with complex analytical processes to solve difficult problems is not new to SAS . Over the years, SAS has extended advanced analytics capabilitiestoavarietyofdatabaseandstoragesystems,includingHadoop.SAS’supportforHadoopiscenteredonasingulargoal:helpingyouknowmore–faster–soyou can make better decisions . Beyond accessing tremendous amounts of structured and unstructured data, SAS products and services create seamless and transparent accesstomoreHadoopcapabilitiessuchasthePigandHivelanguagesandMapReduceframework.SASprovidestheframeworkforarichervisualandinteractiveHadoopexperience,makingiteasiertodiscoverpatternsandbuildanalyticalmodels. ItisallpartofalargerSASstrategytoroundoutHadoopcapabilitiestomanagetheentire analytics life cycle, from big data preparation and exploration, to modeling and deployment .

Visualizing big data

UsingSASVisualAnalytics,governmentagenciescangetlightning-fastinsightsthroughdata exploration, analytical visualization, robust reporting and flexible information sharing via Web and mobile devices . SAS broadens the use of descriptive analytics, enabling everyone – from nontechnical users to analysts – to visually explore all available data to look at more options, identify key relationships, patterns and trends that were not evident before .

Government Big Data in Action

There are several areas where government can address big data challenges with SAS High-PerformanceAnalyticssolutions,whichallowsyoutodevelopanalyticalmodelsusing complete data, not just a subset . You can develop and process models that use thousands of variables and millions of documents, test more ideas and quickly evaluate complex scenarios to produce more accurate insights and take timely decisions . It includes offerings for statistics, data mining, text mining, forecasting, optimization, and econometrics, all available in a highly scalable, distributed in-memory processing architecture .

“SAS Visual Analytics helps

business users to visually

explore data on their own. But

it goes well beyond traditional

query and reporting. Its high-

performance in-memory

architecture delivers answers in

seconds or minutes instead of

hours or days.”

Jim Goodnight CEO of SAS

15

How Governments are Using the Power of High-Performance Analytics

In homeland security and intelligence analysis, timely and accurate identification of threats is critical and urgent . Analysts must review billions of rows of data looking for that nugget of relevant information . In other agencies, billions of tax dollars paid by hardworking citizens are lost each year to improper payments due to fraud, error, waste and abuse . But to move from a pay-and-chase approach to a predict-and-prevent environment, agencies must be able to quickly access and analyze every bit of relevant data . Consider also the federal government’s role in the supervision and regulation of the US banking system . To actively prevent another major financial crisis, the government needs the ability to derive insights from information quickly – insights that could provide early warnings to help prevent the next economic meltdown or egregious fraud scheme .

There is a trend toward sharing data that can be harnessed to solve these complex challenges by integrating data systems and taking advantage of high-performance analytics capabilities . Intelligence and cybersecurity are areas that are ripe to benefit from extreme information management and advanced analytics – specifically, big data analytics . Some specific examples using SAS are described below .

Fraud, waste, abuse and improper payments

SAS can help stem the flow of taxpayer dollars being lost to fraud and improper payments(anestimated$115billionin2011)byanalyzinglargevolumesofdatato spot hidden patterns of behavior and trends that can indicate fraud, waste or abuse . This enables agencies to take proactive measures to stop improper payments before money goes out the door, such as:

• A US Federal Agency: As the provider of state-of-the-art human resources management leadership, services and tools, a US government agency oversees a variety of employee benefit programs, such as retirement, life insurance, long-term care and health insurance . The agency also conducts nationwide audits on morethan400healthinsurancecompaniesthatservemorethan9millionfederalemployees and their families . Determining which claims represent instances of fraud, waste or abuse in an efficient way amidst all the disparate data is a primary challenge .

The agency uses SAS to combine, analyze and share claims information with speed it never had before . Therefore, auditors and agents can search for fraud and payment errors, and identify duplicate payments, claims not coordinated with other insurance, overpaid assistant surgeons and a variety of other types of claim payment errors . As a result, the agency recovered millions of dollars in overpaidclaimsinfiveyears;experienced50percenttimesavingsonbenefitclaim reviews; and freed auditors’ time to perform more reviews and more comprehensive analyses .

• US Internal Revenue Service:TheIRStappedintothepowerofSAStoquicklyanalyze legislation and tax-code changes, predict the tax-revenue impact of eventslikeHurricaneKatrina,andformulatelong-rangecollectionsforecasts for the US Treasury .

16

SAS White Paper

Forinstance,theIRSestimatesthatbetween21-26percentofallclaimsfortheEarned Income Tax Credit (EITC) are paid in error . Due to the complexity of the law, manysucherrorsareclearlyunintentional.However,someclaimsreflectintentionaldisregard for the law, potentially costing the government billions of dollars in fraudulentclaims.IRSEconomistDanHowarexplainstheresultsofusingSAS to solve this challenge:

“We’re sifting through tens of millions of EITC claims . SAS is helping us identify likely candidates for further investigation . That’s enabling us to identify and educate filers and tax preparers to correct the improper returns . And, we’re using the same techniques and models to perform similar analyses of telephone tax refunds, and fraudulent tax filings among prisoners . Given the volume of claims involved, it’s safetosaythatSASisplayingakeyroleinIRSeffortsthataresavingtaxpayersmany millions of dollars in inappropriate claims that might otherwise go undetected .”

Cybersecurity

Cyberdata continuously flows into federal agencies at a fast pace . SAS helps uncover patterns and correlations buried in the data that could provide the early warnings of chicanery and mitigate the threat faster with speed and efficiency .

For cyber security, timely identification and accurate depiction of emerging threats are essential, and analysts review vast amounts of data daily looking for that needle in the haystack . SAS lets analysts visually explore billions of rows of data all at once to identify previously unknown correlations between entities and events, and then share critical information quickly through a variety of mobile platforms .

Making the Case for Change

The need for government to transform its data into an information asset is more important than ever . The volume, velocity and variety of data entering into government has created big data – including unstructured data – which requires big data analytics to identify the relevancy of it all .

The value of big data can improve government performance for the public, but this requires collaboration across agencies and sharing information resources . The need to realize information as a strategic asset is critical . It really is not about the amount of data you have, or how much you can process – it is about capitalizing on all information assets that are available to provide the insights that drive fast and accurate decisions to serve the public .

“We use SAS to examine 15

years of weekly data in our

Compliance Data Warehouse

and make recommendations

about what cases should have

which processes for collection.

In this way, SAS will help us find

smarter ways to allocate our

field resources.”

Dan HowarEconomist, US Internal Revenue Service

17

How Governments are Using the Power of High-Performance Analytics

SAS in GovernmentSAS has helped the US government in its most data-intensive challenges and continues to do so today with powerful analytic solutions . And with big data analytics, we are more committed than ever . To help government agencies better achieve their missions, we have invested in high-performance analytic solutions that help our government in myriad ways – including fraud detection and prevention, risk, and cybersecurity .

SAS is the global leader in the high-performance analytics market . SAS helps remove the limitations arising from trying to analyze big data with current analytical modeling tools and eliminate the restrictions imposed by existing infrastructures . In the public sector,morethan90federal,stateandlocalgovernmentagenciesrelyonSAStohelpsolve their most complex problems . With more than three decades of experience with government, SAS understands the importance of giving decision makers more time to question and collaborate, allowing them to be proactive rather than reactive .

For More InformationTo learn more, visit sas.com/hpa .

About SASSAS is the leader in business analytics software and services, and the largest independent vendor in the business intelligence market . Throughinnovativesolutions,SAShelpscustomersatmorethan60,000sitesimproveperformanceanddelivervaluebymakingbetterdecisions faster.Since1976SAShasbeengivingcustomersaroundtheworldTHEPOWERTOKNOW® . For more information on SAS® Business Analytics software and services, visit sas.com .

SAS Institute Inc. World Headquarters +1 919 677 8000To contact your local SAS office, please visit: sas.com/offices

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. Copyright © 2013, SAS Institute Inc. All rights reserved. 106474_S106266_0613