Download - Big data voor Sociale Secretariaten
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www.realdolmen.com
BIG DATAINSPIRATION SESSION
7/2/2014
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AGENDA
Setting the scene.
Defined.
Avoiding pitfalls.
Practical approach.
Open discussion. Use cases & reality.
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BIG DATA
interaction datatransaction data
data integrationdata processingdata analytics
?
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BIG DATA
interaction datatransaction data
data integrationdata processingdata analytics
Social Media
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BIG DATA
interaction datatransaction data
data integrationdata processingdata analytics
Call Detail Records
ClickStream Data
Scientific/Genome
Machine/Device
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BIG DATA
interaction datatransaction data
data integrationdata processingdata analytics
Online Transaction Processing
Online Analytical Processing & Datawarehouse Appliances
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BIG DATA
interaction datatransaction data
data integrationdata processingdata analytics
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BIG DATA
interaction datatransaction data
data integrationdata processingdata analytics
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BIG DATA
interaction datatransaction data
data integrationdata processingdata analytics
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BIG DATA & YOUR MARKET REACH
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BIG DATA & YOUR MARKET REACH
Marketing Mix
Direct Retail ATL Online
+Big Data = Better insight & Value
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USE CASE #1 – SOCIAL TV ANALYTICS
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USE CASE #1 – SOCIAL TV ANALYTICS
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USE CASE #1 – SOCIAL TV ANALYTICS
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USE CASE #1 – SOCIAL TV ANALYTICS
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USE CASE# 2 – RETAIL CUSTOMER ANALYTICS
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USE CASE# 2 – RETAIL CUSTOMER ANALYTICS
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USE CASE# 2 – RETAIL CUSTOMER ANALYTICS
Brand preferencePolitical learningsReading habitsCharitable givingNumber of cars
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USE CASE# 2 – RETAIL CUSTOMER ANALYTICS
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USE CASE# 2 – RETAIL CUSTOMER ANALYTICS
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USE CASE# 3 – PERSONAL LIFE PREDICTION
Data patterns
Interactions
People
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USE CASE# 3 – PERSONAL LIFE PREDICTION
Relationship StatusChanges
Data patterns
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USE CASE# 3 – PERSONAL LIFE PREDICTION
Data patterns
Interactions
People
Type of relationshipFriendship historyLove history
Friends’ network
Relationship status changesWall-writing patternsrelationship strenghtFlirtation index
Photo tagsCheck-in
Page & photo viewsMessaging history
33% accuracy
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Big Datadefined
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Transactions
Interactions
2011 2,7ZB 2015 8ZB 2020 35ZB
Source: An IDC White Paper - sponsored by EMC. As the Economy Contracts, the Digital Universe Expands.
.
VOLUME
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VARIETY
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VELOCITY
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Big Data Integration enables an
Organization to:
Do things they could not do before
Do things that they have been doing much more cost effectively
1Business Expects Big Benefits
2Traditional Paradigms
cannot support all of Big Data Challenges
3A New Big Data
processing Platform
emerged to support Big Data requirements
4Complimentary to other
technologies
Variety Complexity
Velocity Volume
BIG DATA OPPORTUNITIES
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Volume
Source: IDC
LatencyYears Sub-Second
Data Volume
Across Time Scales
Bu
sin
ess V
alu
e
DEFINING BIG DATA
EXPLOSIVE GROWTH OF DATA – VOLUME, VARIETY, VELOCITY
Velocity
Variety
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Based on traditional
relational database
technologies
PAST GENERATION TECHNOLOGIES WERE NEVER DESIGNED FOR BIG
DATA VOLUMES AND TYPES
What happened?
Why did it happen?
• Data mining
• Data analysis
• Business Intelligence
Data warehouse
What will happen?
Social Media, Web Logs
Machine & Device Data
Documents and Emails
Mainframes, Apps
Payments, Trade
Customer
Entities
Reference Data
Other
Securities
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GROWING ADOPTION IN HADOOP
• Highly scalable: Any data volume/size
• Flexible: Any Data Type (Structure and
Unstructured)
• Cost effective: Leverages commodity
hardware
Social Media, Web Logs
Machine & Device Data
Documents and Emails
Mainframes, Apps
Payments, Trade
Customer
Entities
Reference Data
Other
Securities
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INVESTMENTS IN DATA ANALYTICS, DATA MINING,
DATA VISUALIZATION TECHNOLOGIES
• Improve User Experience vs. previous generation offerings
• Flexible Delivery (On-premise and Cloud)
• Pre-packaged Analytics and Rules
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Real-time Data
Visualization
Sentiment Analysis
Data Mining, Predictive
Analytics
Next Gen. Data
Warehouse
BIG DATA TECHNOLOGIES AT WORK
Process, Score,
Analyze All Data
Consume Results
Social Media, Web Logs
Machine & Device Data
Documents and Emails
Mainframes, Apps
Payments, Trade
Customer
Entities
Reference Data
Other
Securities
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More Data Volumes
Requires Scalable
Data Integration
Capabilities
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INTEGRATING DATA WITH HADOOP REQUIRES DEEP
PROGRAMMING EXPERTISE
• Hadoop Programming language is complex to integrate data
• Requires significant knowledge and expertise
• Development costs can significantly lower expected business value
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Real-time Data
Visualization
Sentiment
Analysis
Data Mining,
Predictive
Analytics
Data Warehouse
BIG DATA MANAGEMENT
Process, Score,
Analyze All Data
Consume Results
Big
Da
ta I
nte
gra
tio
n &
Ma
sk
ing
Business User
Social Media, Web Logs
Machine & Device Data
Documents and Emails
Mainframes, Apps
Payments, Trade
Customer
Entities
Reference Data
Other
Securities
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More Data Sources
and Types Increases
Risk of Data Quality
Errors
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Real-time Data
Visualization
Sentiment
Analysis
Data Mining,
Predictive
Analytics
Data Warehouse
BIG DATA MANAGEMENT
Process, Score,
Analyze All Data
Consume Results
Big
Da
ta I
nte
gra
tio
n &
Ma
sk
ing
Business User
Data Quality & Governance
Data Analyst Data OwnerData Steward Developer
Social Media, Web Logs
Machine & Device Data
Documents and Emails
Mainframes, Apps
Payments, Trade
Customer
Entities
Reference Data
Other
Securities
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Managing More Data
Increases the Risk of
an Unwanted Data
Breach
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Real-time Data
Visualization
Sentiment
Analysis
Data Mining,
Predictive
Analytics
Data Warehouse
BIG DATA MANAGEMENT
Process, Score,
Analyze All Data
Consume Results
Big
Da
ta I
nte
gra
tio
n &
Ma
sk
ing
Business User
Data Quality & Governance
Da
ta P
riva
cy E
nfo
rce
me
nt
Data Analyst Data OwnerData Steward Developer
Social Media, Web Logs
Documents and Emails
Mainframes, Apps
Payments, Trade
Customer
Entities
Reference Data
Other
Securities
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Dealing with Big Data
Requires an Effective and
Efficient Archiving
Solution
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Real-time Data
Visualization
Sentiment
Analysis
Data Mining,
Predictive
Analytics
Data Warehouse
BIG DATA MANAGEMENT
Process, Score,
Analyze All Data
Consume Results
Big
Da
ta I
nte
gra
tio
n &
Ma
sk
ing
Business User
Data Quality & Governance
Big Data Archiving and Retention
Da
ta P
riva
cy E
nfo
rce
me
nt
Data Analyst Data OwnerData Steward Developer
Social Media, Web Logs
Documents and Emails
Mainframes, Apps
Payments, Trade
Customer
Entities
Reference Data
Other
Securities
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BIG DATA SUPPLY CHAIN – HOW TO MAKE IT WORK
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CHALLENGES
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BIG DATA ARCHITECTURE
The Power of Hadoop Store huge amounts of data
Scaling & cost advantage
Complex data analytics & Extensible
Online
Transaction
Processing
(OLTP)
Online Analytical
Processing
(OLAP) &
DW Appliances
Social
Media Data
Other
Interaction Data
Scientific, genomic
Machine/Devic
e
BIG TRANSACTION DATA BIG INTERACTION DATA
BIG DATA PROCESSING
Call detail
records, image,
click stream data
Big Data Processing• Extract & Load Data from & into Hadoop (HDFS/Hive)
• Parse Complex files in Hadoop framework (Map & Reduce )
BIG DATA INTEGRATION
Access Discover Cleanse Integrate Deliver
Product &
Service
Offerings
Social Media Customer
Service Logs &
Surveys
Marketing
Campaigns
Account
Transactions
Sales &
Marketing
Data mart
Customer
Service
Portal
Operational
MDM
BIG DATA PROCESSINGBIG DATA ANALYTICS
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SOLUTION FLOW FOR BIG DATA
REFERENCE ARCHITECTURE
EDWDimensions
FactsBI Reports and Dashboards
Analytic
Applications
and Portals
Sources
DW
Operational
MDM
Push-down
Transformation
AccessVirtualization
Transformation
Data
Marts
Proactive Alerts
Low Latency Update
& Distribution
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APPROACH
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10 WAYS BIG DATA IS USED TODAY
Understanding and Targeting Customers
Understanding and Optimising Business Processes
Personal Quantification and Performance
Optimisation
Improving Healthcare and Public Health
Improving Sports Performance
Improving Science and Research
Optimising Machine and Device Performance
Improving Security and Law Enforcement
Improving and Optimising Cities and Countries
Financial Trading
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BIG DATA OPPORTUNITIES
BROAD SPECTRUM OF OPPORTUNITY
Enterprise Functions Use Cases Benefits
Marketing • Brand Monitoring & PR
• Gain Customer Insight
• Campaigns & Events
• Competitive analysis
• Increased campaign effectiveness
• Better Brand recall
Sales • Gain Sales Insight
• Referrals Mining
• Lead Capture
• Lead Generation
• Increased Lead conversion rates
• Increased revenue from “Native Social”
leads
Service & Support • Gain Support Insight
• Rapid Response
• Peer-to-Peer Support armies
• Better control of online “epidemics”
• Lower support costs due to community
Knowledge base
Innovation & Collaboration • Customer-led innovation
• “Exterprise” collaboration
• Effective product launches
• Collaborative R&D with 3rd parties
• Employee and partner productivity
Loyalty & Customer
Experience
• VIP Experience
• Loyalty & Incentives
• Increased loyalty
• Unpaid Brand Evangelism
Finance • Risk Management
• Fraud Detection
• Additional channels for risk
forecasting/modeling
Human Resources • Recruitment
• Background Verification
• Cost-effective recruitment
• Better fitting candidates
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Q&A
Dimitri Maesfranckx
Division Manager Business Insights
+32 479 730131
Luc Delanglez
Solutions Manager Business Insights, MDM
+32 474 309053
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REALDOLMEN BUSINESS INSIGHTS –
TURN DATA INTO MEANINGFUL INFORMATION
BUSINESS
INFORMATION