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How Big Data Shapes Technology Strategies and Drives Business Transformation
Timo ElliottSAP
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Agenda
Big Data Directions
Using Big Data to Improve The Customer Experience
Using Big Data to Empower Employees
Using g Big Data to Optimize Resource Use
Using Big Data for Business Networks
Wrap-up
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Big Data Directions
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Information Becomes a Profit Center
Real-time, highly
personalized
Business Ownership
Product Customer Experience
Iterative, ever-changing
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Analytics Moves to the Core
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Process data Human data
Machine data
Big Data Adds New Data Opportunities
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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
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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
Unstructured50TB
Semi-structured
2 TB
Structured12 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:
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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 2014www.paradigm4.com/wp-content/uploads/2014/06/P4-data-scientist-survey-FINAL.pdf
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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 2014www.paradigm4.com/wp-content/uploads/2014/06/P4-data-scientist-survey-FINAL.pdf
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What Is Big Data? The Google Summary …
nonsense
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Big Data Is Heading for the “Trough of Disillusionment”
Source: Gartner, August 2014, www.gartner.com/newsroom/id/2819918
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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
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Hadoop and Other “NoSQL” Technology
Enterprise “Data Lakes” and “Data Hubs”
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A Typical Example of DW and Hadoop Integration
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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” www.gartner.com/doc/2657815/hybrid-transactionanalytical-processing-foster-opportunities
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.
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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
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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
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Metadata abstraction
Increasingly automated
Learning algorithms
Content & Process IncludedData Warehouse
HTAPHadoop
Big Data Architecture Directions: Long Term
Where does data arrive?
When does it need to move?
Where does modeling happen?
What can users do themselves?
What governance is required?
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
Where does data arrive?
When does it need to move?
Where does modeling happen?
What can users do themselves?
What governance is required?
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Opportunity Areas for Innovation
Big Data initiatives are typically in one of the following areas:
Hyper-personalizeCustomer Experience
Plan & optimizeResources in
Real Time
Engage & empowerWorkforce of the
Future
Harness the intelligence ofNetworked Economy
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Using Big Data to Improve the Customer Experience
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80% of CEOs think they deliver a superior customer experience
Source: The New Yorker
– but only 8% of customers agree.
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Real-Time Retail Insights
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Social Data
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Unstructured Data
1 patient every 4s = 7M/year
Combine structured and unstructured data for complaint handling and patient
experience reporting
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OmniChannel
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Sharing Data with Customers
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Experience Intelligence Center
Event Interception Business Transformation
Optimizing the Customer Experience
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Optimizing the Customer Experience (cont.)
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New Products and Services
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Using Big Data to Empower Employees
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Worldwide, Only 13% of Employees Are Engaged at Work
USA UK Canada France0%
25%
50%
75%
100%
30%
17% 16%9%
Actively DisengagedNot EngagedEngaged
Source: Gallup State of the Global Workplace Report 2013
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Getting Data into the Hands of Employees
Adapting to the analytics needs of your employees
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“Self-Service” Analytics
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Analytics Collaboration
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Collaborative Analytics
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Using Big Data to Optimize Resource Use
01011011000101010101010010101001111010101010010111010101010101010010010100100100101110110101010
Wearable devices have grown by 2x month over monthsince October 2012.
Source: Mary Meeker’s Internet Trends, 2013
Photo: Intel Free Press
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The “Datafication” of Daily Life
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Unexpected Uses of Existing Data
Source: https://jawbone.com/blog/napa-earthquake-effect-on-sleep/
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The Datafication of Reading
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Sensors Allow Tracking of the Previously Untrackable
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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/
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Sensors + Cloud + Mobile + Analytics (cont.)
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Using Sensors to Gather Logistics Data
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Aggregating Information and Providing to Customers
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Sensors + Analytics + Predictive Maintenance
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Making It Easier to Add Sensors
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Using Big Data for Business Networks
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Network Analysis
Churn model accuracyimproved by 47% withsocial
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Network Analysis (cont.)
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Business Networks Are Becoming Information Networks
SuppliersBuyers
ProcurementSales
FinanceLogistics
Supply ChainSustainabilityCompliance
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
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Creating Information Communities
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Information Communities
• Interact with consumer in the field• Run mobile marketing campaigns
based on consumer profile and location
• Interact with consumer in real-time anywhere, anytime.
• Design and run mobile marketing campaigns based on consumer profile and location
• Analyze consumer behavior in the field
SAP Precision Retailing
• Receive information, discounts & Special offers
BI
CRM
Merchants
Outings
Transports
Partners
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How It Works
Valid at this time
For my profile
(segments)
In the store(s) nearby
Eligible offers
Top x
What time is it ?Where am I?
What is my personal profile?What is my CRM profile?
Select Rate & Order Deliver & Learn
What are my preferences ?Where am I?
What is my personal profile?What is my CRM profile?
The rating is based on the learning engine and on the characteristics of the shopping context, the consumer preferences, and the frequency of presentation.
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The SAP Big Data Strategy
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SAP Big Data Architecture
Data Connectors
ETL
StreamingAnalytics
AdvancedAnalytics
Line of BusinessApps
BI &Reporting
Visualization&
Exploration
IndustryApps
Big DataDevelopment
Tools
In-memory &petabyte-scale
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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
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Dat
a In
ges
tio
n\ A
cqu
isit
ion
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 Administration
Application Development
Custom Apps Mobile Apps Big Data Apps
ERP Apps SAP Analytics
Smart Data Access
Transfer Datasets
SAP IQ
Web / Sensor
CallCenter
Other
Data Sources
SAP SLT / Rep Server
SAP Data Services
SAP SQL Anywhere
SAP ESP
Hadoop Adapter
Hadoop Hive
SAP ERPBW
Hortonworks Data Platform
Intel Distribution for Hadoop
Partner Hadoop Distributions
The SAP HANA Platform and Hadoop
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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
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Big Data Applications — E.g., Risk, Sensing, …
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Wrap-Up
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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
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Thank you
Timo Elliott, SAP
[email protected]: @timoelliottBlog: timoelliott.com
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