UKISUG2014 Big Data Presentation

The Big Trends in Big Data

Timo Elliott, Global Innovation Evangelist, SAP @timoelliott

© 2014 SAP SE or an SAP affiliate company. All rights reserved. 1

Agenda

Big Data Directions

Using Big Data to Improve The Customer Experience

Using Big Data to Empower Employees

Using Big Data to Optimize Resource Use

Using Big Data for Business Networks

Wrap-up


Big Data Directions


The World Has Turned Upside-Down

Transient, flexible

Permanent, fixed

OPERATIONS

ANALYTICS


What Is Big Data? The Google Summary …


Big Data Is Not Only About “Big” Data

“My analytics are becoming more difficult because of the variety and types of

data sources (not just the volume)”

Source: Paradigm4 data scientist survey 2014

www.paradigm4.com/wp-content/uploads/2014/06/P4-data-scientist-survey-FINAL.pdf

http://www.paradigm4.com/wp-content/uploads/2014/06/P4-data-scientist-survey-FINAL.pdf


Process data

Human data

Machine data

Big Data Adds New Data Opportunities


Big Data is “Signal” Data


Descriptive:

What happened?

Diagnostic:

Why did it happen?

Predictive:

What will happen?

Prescriptive:

How can we

make it happen?

Hindsight Insight Foresight

Predictive Reaches Maturity


Companies Don’t Use Most of Their Data Today

Source: Forrsights Strategy Spotlight: Business Intelligence And Big Data, Q4 2012. Base: 634 business intelligence users and planners

Unstructured

50TB

Semi-

structured

2 TB

Structured

12 TB

Only

12%used today

Average data volume

per company

9 TB 75 TB

0.6 TB 5 TB

4 TB 50 TB

SMBs: LEs:


Transactions Are Still a Big Part of Big Data

“Which types of data do you anticipate using in the next year?”

Source: Paradigm4 data scientist survey 2014

www.paradigm4.com/wp-content/uploads/2014/06/P4-data-scientist-survey-FINAL.pdf

http://www.paradigm4.com/wp-content/uploads/2014/06/P4-data-scientist-survey-FINAL.pdf


Big Data Is Heading for the “Trough of Disillusionment”

Source: Gartner, August 2014, www.gartner.com/newsroom/id/2819918

http://www.gartner.com/newsroom/id/2819918


Benefits from Big Data Initiatives

# 5 Identified new product opportunities (6%)

#4 More reliable decision making (9%)

#3 Improved operational efficiency (11%)

#2 Identified new business opportunities (31%)

#1 “DON’T KNOW” (51%)

Source: Information Difference Research Study Dec 2013: “Big Data Revealed” http://helpit.com/us/industry_articles/big_data_revealed.pdf

http://helpit.com/us/industry_articles/big_data_revealed.pdf


Hadoop and Other “NoSQL” Technology

Enterprise “Data Lakes” and “Data Hubs”


Hadoop is Complementary, Not a Replacement

Source: Gartner


A Typical Example of DW and Hadoop Integration


OLTP + OLAP = HTAP

“Hybrid transaction/analytical processing will

empower application leaders to innovate via greater

situation awareness and improved business agility.

This will entail an upheaval in the established

architectures, technologies and skills driven by use

of in-memory computing technologies as enablers.”

Gartner, 2014

Source: Gartner 2014, “Hybrid Transaction/Analytical Processing Will Foster Opportunities for Dramatic

Business Innovation”

HTAP = Hybrid transaction/analytical processing

A single system for both OLTP (operational) and

OLAP (analytical) processing. Data is stored once, in-

memory, and so instantly available for analytics.

https://www.gartner.com/doc/2657815/hybrid-transactionanalytical-processing-foster-opportunities


With HTAP, the Operational Schema Looks Like a DW

SAP HANA

SAP HANA

Live (Virtual

Data Model)

Customer

Service

Risk Management

Team

Finance and

Operations

Account

Administration

Executive

Management

Customers Channel Suppliers Accounting ForecastingInventory Products Pricing Planning


Data

Warehouse

HTAPHadoop

Big Data Architecture Directions: Short Term

Where does data arrive?

When does it need to move?

Where does modeling happen?

What can users do themselves?

What governance is required?

BI

Tools


Metadata abstraction

Increasingly automated

Learning algorithms

Content & Process IncludedData

Warehouse

HTAPHadoop

Big Data Architecture Directions: Long Term






Integrated Data “System” (cloud & on-premise)

BI

Tools

Metadata abstraction

Increasingly automated

Learning algorithms

Content and Process Included

HTAPHadoopIntegrated Data “System” (cloud and on-premise)

BI

Tools







Opportunity Areas for Innovation

Big Data initiatives are typically in one of the following areas:

Hyper-personalize

Customer Experience

Plan & optimize

Resources in

Real Time

Engage & empower

Workforce of the

Future

Harness the intelligence of

Networked Economy


Using Big Data to Improve the Customer Experience


80% of CEOs think they deliver a superior customer

experience

Source: The New Yorker

– but only 8% of customers agree.


Personalized Service

27

Simplifying Systems

The benefits of the

SAP HANA platform

are significant with a

hugely simplified

footprint.

We’re putting the

whole business on

the SAP HANA

Enterprise cloud

”

“


Real-Time Retail Insights


Social Data


Unstructured Data

“The improved information flow allows Medtronic to address product performance issues

efficiently, accurately, and effectively and to detect trends at an earlier stage.”


New Products and Services

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Network Analysis

Churn model accuracy

improved by 47% with

social


Sharing Data with Customers



Using Big Data to Empower Employees


Worldwide, Only 13% of Employees Are Engaged at Work

30%

17% 16%9%

52%

57%

70%

65%

18%26%

14%

26%

0%

25%

50%

75%

100%

USA UK Canada France

Actively Disengaged

Not Engaged

Engaged

Source:

Gallup State of the Global

Workplace Report 2013


Empowering Individual Performance

Adapting to the analytics

needs of your employees


“Self-Service” Analytics


Analytics Collaboration


Collaborative Analytics


Using Big Data to Optimize Resource Use

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Unilever

“if we knew then what we know now, we would have started deploying

SAP HANA much earlier, because it’s so important for business... We

think it’s even more disruptive than we initially thought — we’ve only

just started”

Marc Béchet, VP Global IT ERP, Unilever


Nope


Textile Rubber & Chemical Company

500 Employees, 4 internal IT staff

Business Suite on HANA

Why in-memory?

Because it

simplified our IT

Landscape

In 5 minutes we

could see more

information than

we could in the

last 7 months

”

“


Big Data Process Mining

Wearable devices have grown by 2x month over month

since October 2012.

Source: Mary Meeker’s Internet Trends, 2013

Photo: Intel Free Press

http://www.slideshare.net/kleinerperkins/kpcb-internet-trends-2013

http://www.slideshare.net/kleinerperkins/kpcb-internet-trends-2013


The “Datafication” of Daily Life


Unexpected Uses of Existing Data

Source: https://jawbone.com/blog/napa-earthquake-effect-on-sleep/


Data, Data, Everywhere


Sensors Allow Tracking of the Previously Untrackable


Sensors + Cloud + Mobile + Analytics

1. Install flow sensors on your beer lines

2. The sensors beam data to box

plugged into the internet

3. Data sent to HANA in

the cloud

4. Mobile interfaces to

analyze consumption

http://weissbeerger.com/


Sensors + Cloud + Mobile + Analytics (cont.)


Networked Crane Safety


Sensors + Analytics + Predictive Maintenance


Making It Easier to Add Sensors


Using Big Data for Business Networks

© 2014 SAP AG or an SAP affiliate company. All rights reserved.

Networked economy: the next economic revolution

All figures are in Trillions; 1990 international dollars; Source: Department of Economics, UC Berkeley, BAIN 8 MacroTrends Brief.

1850

Industrial

economy

$0.36T

IT

economy

1970

$12.10T

1990

Internet

economy

$27.50T

2020

Networked

economy

$90.0T

Gross

world

product


Information Ecosystems

60


Business Networks Are Becoming Information Networks

SuppliersBuyers

Procurement

Sales

Finance

Logistics

Supply Chain

Sustainability

Compliance

Partners

Ariba Network

More than 1M suppliers in

more than 190 countries

around the world

Transact with suppliers – The

Network handles over $460

billion per year in commerce

Reduce supply costs –

Customers save a combined

total of $82M daily


The SAP Big Data Strategy


SAP Big Data Architecture

Data

Connectors

ETL

Streaming

Analytics

Advanced

Analytics

Line of

Business

Apps

BI &

Reporting

Visualization

& Exploration

Industry

Apps

Big Data

Development

Tools

In-memory &

petabyte-scale


Big Data Platform

Data Science

Accelerate

Apply Achieve

Big Data

Analytics & Apps

Three Core Areas of Big Data Strategy

Big Data Platform

Data Science

Accelerate

Apply Achieve

Big Data

Analytics & Apps


Da

ta In

ge

sti

on

\A

cq

uis

itio

n

Processing Engine

Application Function Libraries & Data Models

Database Services

(OLTP + OLAP)

Extended Application Services

Integration Services

SAP HANA PLATFORMIn-memory processing platform for real-time transactions + end-to-end

analytics that offers massive simplification.

Unified

AdministrationApplication

Development

Custom Apps Mobile Apps Big Data

AppsERP Apps SAP Analytics

Smart Data

Access

Transfer

Datasets

SAP IQ

Web /

Sensor

Call

Center

Other

Data Sources

SAP SLT /

Rep Server

SAP Data

Services

SAP SQL

Anywhere

SAP ESP

Hadoop

Adapter

Hadoop

Hive

SAP ERP

BW

Hortonworks Data

Platform

Intel Distribution

for Hadoop

Partner Hadoop

Distributions

The SAP HANA Platform and Hadoop


Front-End Tools Adapted to Different Needs

DECISION MAKER

DESIGNER

Explore Monitor

Design

Govern DATA Enrich Explain

Plan People

DATA ANALYST/SCI

ENTIST

PREDICTAdvanced Analytics

ENGAGEEnterprise BI

VISUALIZEAgile Visualizations


Big Data Applications — E.g., Risk, Sensing, …


Design Thinking


Wrap-Up


7 Key Points to Take Home

1. Big Data is a huge opportunity

2. Get closer to your customers through better insight and hyper-

personalization

3. Use “datafication” to make better use of resources

4. Empower your employees to make better decisions

5. Leverage your business networks

6. Big data is the heart of your next IT platform — simplicity and flexibility

are essential

7. The biggest barriers are ideas and culture — use design thinking to help

© 2014 SAP SE or an SAP affiliate company. All rights reserved.

Thank you

Timo Elliott, SAP

[email protected]

Twitter: @timoelliott

Blog: timoelliott.com


© 2014 SAP SE or an SAP affiliate company.

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Date post:	04-Jul-2015
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UKISUG2014 Big Data Presentation

Data & Analytics