How AnalyticsChanged inFive Years

How AnalyticsChanged inFive Years

Industry thought leaders andvendors strive to explain that new thing called "big data."

IDC projects big data technology will generate

Even Bigger Big Data

The greatest development in analyticsin the past five years?

Then and Now

Four Keys to Help Your AnalyticsTeam Succeed

The Technologies Advance

IoT transforms whole industries and makesbig data even bigger

Information is just as important,if not more important than informationtechnology

for a

2011

2015

$48.6B

by 201923.1%

CAGRSource: IDC

Source: SAS and Kellogg School of Management, Understanding the Mobile Consumer, Realizing the Opportunities with Analytics

Source: Gartner

The size of the global big data hardware, software, and services market in 2011

new things are being connected using IoT concepts every day.

The same big data market in 2017$50.1 billion

$7.3 billion

Source: Wikibon

Source: MIT Sloan Management Review, Beyond the Hype: The Hard Work Behind Analytics Success

"Realization that analytics is neededeverywhere and that there are hugegaps that need needs filling every-where: talent, technologies, tools."

— Kirk Borne, Principal Data Scientistat Booz Allen Hamilton.

“Information is the oil of the 21st century. Enterprises are generating an unprecedented amount of informationof enormous variety and complexity.The need to leverage this data for greater business value is leading to a change in data management strategies known as ‘big data.’ ”

"The commoditization of platforms that allow analytics to be used by anyone. Cloud platforms, such as AWS, Azure, and others with pay-as-you-consume, elastic services that have a consumer-friendlyUI, have changed the game in analytics. They provide great opportunities for all to use data to benefit their business and society."

• Establish career advancement goals.

• Make continuous training a priority.

• Develop an incentive program

• Create liaisons between IT and the business.

The greatest development in analytics in the pastfive years?

— November 2011

— ExpertS echo those same thoughts today

From founding All Analytics Editor Beth Schultz's second blog, June 28, 2011

Principle No. 1in Gartner's New CIO Manifesto

Earliest talk of data lakes

Analytics and BI were oftenused interchangeably

Transactional data ruled

Data visualization was "promising" Predictive analytics in action was the exception 2011: Analytics grows as a source of competitive advantage.

Data lakes are real, not everywherebut not rare We strive to know and supportcustomers in an omnichannel world

Unstructured data extends our viewfarpast transactional boundaries Great visualizations let data tell a story Prescriptive analytics is the brass ring

2016: Analytics are used byorganizations to stay competitive..

2016 2011 2011

– Robert Plant, department vice chair, business technology, University of Miami.

Most people were still trying to figure out how to pronounceHadoop and what it was.

2011

Yahoo, where Hadoop first spread its roots, had 600 petabytes of dataspread among 40,000 Hadoop nodes.

• A twin-engine Boeing 737 aircraft produces 333 GB of data per minute per engine. For a flight from Los Angeles to New York, that aircraft will generate roughly 200 TB of data.

• In the oil and gas industry, an IIoT-ready drilling rig produces 7–8 TB of operational data per day.

• In the U.S., connected automobiles already generate over 1 petabyte (PB) of operational data per day. For context, 1 PB equals 1 million GB. That works out to about 62,500 16 GB iPhones.

2015

$5.5million

Five years ago mobile analytics were little more than monthly counts of phone apps. Today, pioneering retailers use web activity, phone apps, and in-store beacons to gain a single, omnichannel view of customer activity, and more than ¾ of consumers actively use mobile devices in interacting with businesses (including showrooming)

Fighting Fraud:A Slow,Uphill Battle

Fighting Fraud:A Slow,Uphill BattleExecutives generally areconfident in their organizations' ability to spot and respond to fraud, but best efforts alonearen't necessarily enough.

When Your BestIsn'tGood Enough

What is your level of confidence in yourorganization’s ability to detect and preventfraud before it results in a serious business

impacton your enterprise or your customers?

Ever-evolvingsophisticated schemes and "lack of awareness"raise the bar for fraud fighters

34%

50%

14%2% High confidence

we have top-notch anti-fraud tools and professionals fighting fraud

Moderate confidencedespite our best efforts, we occasionally miss a fraud scheme

Low confidenceour anti-fraud tools and team justcannot keep pace with evolvingfraud schemes

No confidence our customers are more apt to discover a fraud scheme before we do

The percentage of respondents who say ittakes one day or moreto uncover a fraudincident once it occurs

The percentage not currently deploying advanced data analytics tools

Base: 240 C-level security and technology leaders at financialand government organizations42%

67%

"More than half also say that today'sfraud schemes are too sophisticatedand quick-changing to keep pace,and their own customers, employeesand partners lack the fraudawareness to avoid falling victim topredatory scams."

Wherethe Risks

Lie

What do you believeto be the top threevulnerabilities in your fraud defenses?(select three that apply)

Holding the Fort74% of respondents say the

number of fraud incidents has

Source: 2016 Faces of Fraud Report:The Analytics Approach to Fraud Prevention,developed by SAS and Information SecurityManagement Group (iSMG)

Today's fraud schemes are too sophisticated and evolvetoo quickly for us to keep pace

Our employees lack sufficient awareness to protectthemselves from socially engineered fraud schemes

Our customers and/or partners lack sufficient awareness toprotect themselves from socially engineered fraud schemes

56%

42%33%

30%29%

56%

52%

Lack of staff expertise

The percentage oforganizations usingadvanced analytics

to help predict likely fraud

Lack of tech tools

Lack of financial resources

Lack of management/board support

Through automateddata analysis or

transactionmonitoring software

Third-partynotification

Internalwhistleblower

Third-partyinvestigation

46%

Who's Raisingthe Red Flags?How is a fraud incident involving your organization typically detected? (select all that apply)

66%48% 39%

20%

As Days Go ByWhile almost a third of respondents say they take careof fraud incidents within 8 hours, most organizationstake longer, sometimes much longer.

On average, how long do you estimate it takes your organizationto react, respond and resolve the incident after it occurs?

24%14%

13%13%

1-8 hours

1-2 days

3-5 days

More than 5 days

I don't know

31%

increased or remained

steady

41% 33%

54%The percentage

of responding

organizations

that are not

currently deploying

advanced

data analytics

tools.

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Advanced Anti-Fraud Analytics Would Be Nice If...Most Common Barriers to Use of Those Analytics: