Big Trends in Big Data & AnalyticsTimo ElliottGlobal Innovation Evangelist

@timoelliott

Analytics Takes Over The World…

BI and Analytics is the #1 Spending Priority for 2015 and beyond

Rank Technology 2014 2015

1 BI/Analytics 50% 41%2 Infrastructure and Data Center 37% 31%3 Cloud 32% 27%4 ERP 34% 26%5 Mobile 36% 24%6 Digitalization / Digital Marketing 11% 17%7 Security 11% 13%8 Networking, Voice, and Data Communications 12% 12%9 Customer Relationships 8% 11%10 Industry-Specific Applications 10% 9%

Enterprise Data Remains One of The Top Strategic Projects

IDC Futurescape: Worldwide CIO Agenda 2015 Top 10 Decision Imperatives

By 2020, information will be used to

reinvent, digitalize, or

eliminate 80%of business processes and products

from a decade earlier.

From The Back Office To The Business Models of Future

”

“

© 2015 SAP SE or an SAP affiliate company. All rights reserved. 6

The Rise of the Chief Data Officer“The CDO is a senior executive who bears responsibility for the firm's enterprise wide information strategy, governance, analytics control, policy development, and effective exploitation.”

© 2015 SAP SE or an SAP affiliate company. All rights reserved. 7

88%

How Do Executives Make Decisions?

Aspect Consulting, 1997

12%Hard Facts

Gut Feel

90%

10%Hard Facts

Gut Feel

Economist Intelligence Unit, 2014

Why the worst-practice shaded 3D donut charts? JUST TO ANNOY DATA VISUALIZATION EXPERTS!

Big Data On The Gartner Hype Cycle

Source: Gartner, August 2014

Innovation trigger Peak of Inflated Expectations

Trough of Disillusionment

Slope of Enlightenment

Plateau of Productivity

Big Data

Use AnalyticsToday

NeedAnalytics by 2020

Gartner, 2014

Still Lots of Opportunity to Do Analytics Better

Inability to see, understand, and optimize new opportunities

Inaccessible dataand technology Insights remain hidden

Complexity, cost, confusionSilos of approaches and analytic technologies

75%

10%

Slow decision making lacking future view

Rear view mirrorBI mentality

Four Big TrendsDashboards of Tomorrow

Prescriptive Analytics

Big Data Discovery

Analytics Culture

Predicting Prescriptive Analytics

Descriptive:What happened?

Diagnostic:Why did it happen?

Predictive:What will happen?

Prescriptive:How can we make it happen?

Taking Analytics To The Next Level?

Source: Gartner

DATA SCIENCE

QUIZ.

These numbers were found in two tax declarations. One is entirely made up. Which one?

EUR

127,-2.863,-

10.983,-694,-

29.309,-32,-

843,-119.846,-18.744,-

1.946,-275,-

EUR

937,-82.654,-18.465,-

725,-98.832,-

7.363,-4.538,-

38,-8.327,-

482,-2.945,-

1 2 3 4 5 6 7 8 9

30.1%

17.6%

12.5%

9.7%7.9%

6.7% 5.8% 5.1% 4.6%

Benford’s LawDistribution of the first digit of real-world sets of numbers that uniformly span several orders of magnitude

DATA SCIENCE

QUIZ.

These numbers were found in two tax declarations. One is entirely made up. Which one?

EUR

127,-2.863,-

10.983,-694,-

29.309,-32,-

843,-119.846,-18.744,-

1.946,-275,-

EUR

937,-82.654,-18.465,-

725,-98.832,-

7.363,-4.538,-

38,-8.327,-

482,-2.945,-

Benford's Law, also called the First-Digit Law

1999 to 2009

“Greece shows the largest deviation from Benford’s law with respect to all measures. [And] the suspicion of manipulating data has officially been confirmed by the European Commission.”

Fact and Fiction in EU-GovernmentalEconomic Data, 2011

Transport For London

Centerpoint Energy

Kaeser CompressorsEnabling Predictive Maintenance

A global leader in air compressors

≈€500 million, 4,800 employees, 50 countries, partners in additional 60 countries

Modeling Example

E.g. Total energy consumption

• Aggregation of 10 sec values

• Calculation of typical consumption patterns

• Pattern associated with each compressor and day

Repeat for temperature, pressure, vibration, etc.

Predictive Examples

Model combines sensor readings and ERP data (location, type of usage, last service, etc.)• Status alerts: “Oil change / oil analyze / no action”• Predict machine failure 24 hours in advance

Benefits

Customers• Less downtime• Decreased time to resolution• Optimal longevity and performance

Kaeser• More efficient use of spare parts, etc• New sales opportunities• Better product development

“We are seeing improved uptime of equipment, decreased time to resolution, reduced operational risks and accelerated innovation cycles.

Most importantly, we have been able to align our products and services more closely with our customers’ needs.” �

Kaeser CIOFalko Lameter

Kaeser Kompressoren – Just buy the air, not a compressor

24© 2015 SAP SE or an SAP affiliate company. All rights reserved.

Big Data Discovery

Big Data Discovery =

Big DataData DiscoveryData Science

Gartner Strategic Planning Assumption: By 2017, Big Data Discovery Will Evolve Into a Distinct Market Category

Big Data Discovery

• Volume, velocity, or variety of data

• Potential business impact

• Difficult to implement• Potentially expensive• Lack of skills available

• Ease of use• Agility and flexibility• Time-to-results• Installed user base

• Complexity of analysis

• Potential impact• Range of tools• Smart algorithms• Difficult to implement• Slow and complex• Narrow focus of

analysis

• Limited depth of information exploration

• Low complexity of analysis

BIGDATA

DATASCIENCE

DATADISCOVERY

Big Data Discovery

• Simpler to use than data science

• Accessible to a wider range of users

• Broad range of data manipulation features

• Able to handle new types of data sources

• With adequate performance for big data

BIG DATA

DISCOVERY

Potential impact per user

Potential user base

The Rise of the Citizen Data Scientist?

Business analyst

Data scientist

Citizen data scientist

Citizen Data Scientists

The Opportunity

New Business Opportunities

Traditional Analytics

Data Value

Volume / Variety / Velocity of Data

“Big Data Discovery” Data DiscoveryBig DataData Science

The Dashboards of Yesterday And

Tomorrow

“Intricate calculations of sales by territories will appear as if by magic in the digital age ahead”

Decision Cockpits

Analytics Culture

Culture Clash Around Analytics

Internally-orientedCosts

GovernanceEfficient reuse

Customer-facingOpportunitiesFlexibility & speedExperimentation

IT Business

Business vs. Corporate IT: “It’s Not You — It’s Your Data”

“We found, on average, that 45% of the data business people use resides outside of the enterprise BI environments.

An astonishingly miniscule 2% of business decision-makers reported using solely enterprise BI applications.

This is undoubtedly connected to 76% of business respondents indicating they continue to resort to spreadsheets and other homegrown BI applications to analyze BI data. ”

Source: Forrester

55%

45%

In enterprise systemsNot in enterprise system

Central IT is like Taxi companies vs Uber

Create a Community

Source: Gartner

Design Thinking

Dashboardsof Tomorrow

Prescriptive Analytics

Big Data Discovery

Analytics Culture

See, understand, and optimize new opportunities

Conclusion

Thank You!Timo ElliottVP, Global innovation Evangelist

timo@timoelliott.com @timoelliott