The document outlines the business challenge of becoming a digital data-driven company by enhancing omni-channel analytics capabilities. It discusses the transition from traditional web analytics to a 360-degree customer view, emphasizing data integration, self-service access, and personalized customer experiences. A reference architecture for digital engagement is also provided, detailing data movement, analytics, and the necessary technological components for effective digital transformation.

1. 1© Copyright 2016 EMC Corporation. All rights reserved. 1© Copyright 2016 EMC Corporation. All rights reserved.
THE CONNECTED CONSUMER
REAL-TIME CUSTOMER 360
MAY 04, 2016 Steve Jones
Global VP, Big Data and Analytics
steve.g.jones@capgemini.com

2. 2© Copyright 2016 EMC Corporation. All rights reserved.
THE BUSINESS CHALLENGE
Become a
Digital Data
Driven
Company
Position for the
Future
Enable Omni-
Channel
Analytics
Capabilities
Current State
• Traditional Web based analytics for website.
• Limited, and slow, combination of information between we and other channels
• Unable to integrate internal and external insight in a consistent way
Future State
• Omni-Channel Capability: Design, develop and implement a solution to more
effectively understand the omni-channel customer experience.
• 360 Customer Centric View: Enable the aggregation and analysis of online,
offline, customer characteristic, and third-party into an environment that is
accessible by analysts and business users, on a near real-time basis.
• Self-Service: Data democratization / Integration / On Demand Access -
Develop a trusted data source with extensive drill-down capabilities that enables the
users with ease of on-demand data access and addition of new sources
• Ease of Consumption: NRT Reporting / Analytics / Visualization - Design,
develop, and implement tools, processes and methods to enable the consumption of
data.

3. 3© Copyright 2016 EMC Corporation. All rights reserved.
As companies intends to be able to better analyze the customer omni-channel experience across all functions, it’s
important to understand that the Digital Divide depicted below is a limitation to become a full-fledge Digital company.
BECOMING A DIGITAL ANALYTICS COMPANY:
BRIDGING THE DIGITAL DIVIDE
Source: Capgemini Consulting-MIT Analysis – Digital Transformation: A roadmap for billion-dollar organizations; The Digital Advantage (c) 2012 and 2013
Analytics
• Target marketing
more effectively
• Personalize marketing
communications
• Optimize pricing
• Better qualify sales
prospects
Process Digitization
• Automating processes
• Monitoring operations
in real-time
• Adaptability to
external changes
Internal Collaboration
• Active knowledge sharing
• Use of internal social
networks and video conf.
• Working anywhere,
anytime, any device
Social Media
• Monitor reputation
• Promote products and services
• Sell products and services
• Provide customer service
• Build customer communities
Customer Experience
• Cross-channels consistency
• Personalize the customer experience
• Offer self-service
Mobile Channel
• Promote products and services
• Sell products and services
• Provide customer service
Data Integration
• Customer Data
• Other data (finance, supply-chain, operations)
Customer Engagement Operational Processes
D
I
G
I
T
A
L
D
I
V
I
D
E

4. 4© Copyright 2016 EMC Corporation. All rights reserved.
A STANDARD REFERENCE ARCHITECTURE FOR DIGITAL ENGAGEMENT
CAPGEMINI’S BLUEPRINT FOR BUSINESS DATA LAKE:
Data Movement
Design ETL/ELT processes for data
movement from heterogeneous data
sources to Hadoop and beyond
Data masking
Design masking process on write
(persistent data masking) or on read
(dynamic data masking).
Analyze
Provide data
Visualization and
Analytics tools, models
and frameworks for
analytics
Enrich
Design Enrichment processes
to prepare Hadoop Data And
Augment It With Descriptive
Metadata
Prepare Data for Analysis
Define strategy for data preparation and
provisioning to enable self service BI and
advanced analytics
Database
Design flexible and scalable
database to evolve with the
Omni-Channel requirements
Ingestion
Design Ingestion
process (batch and
near real-time) for
structured, semi-
structured, and
unstructured data
sources
Discovery
Design Data Discovery
process for Data
Catalogue, Data
Profiling and Data
Lineage.
Insights
Provide Analytics at the
Point of Relevance
through front to back
integration of tools
Customer 360
Design a trusted data
source for 360-degree
customer view
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10
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5. 5© Copyright 2016 EMC Corporation. All rights reserved.
ITS BIG, FAST AND CLEVER
Stream
Processing
Transform
Dashboard
Ambari
Interactive
Data
Storage
Streaming
Forwardto
spark
ETL
Informatica BIG
DATA Edition
Alerts
IngesttoHDFS
JMS
Fast and Batch
Ingest
Near Real-Time
Batch Interactive
Load to
HDFS
SOURCE DATA
Email,
Call Logs,
Documents
Click Stream
Policy, Quote,
Claim Data
Customer Account
Data/CRM/MDM
EDW
REST
Streaming
JMS
Analytics
Tableau /
Qlik /
SHINY
Distributed DB
Query Engine
NoSQL
HBase
SQL
Interface
Phoenix
ETL /
MDM
Customer
360
SQL on
Hadoop
Ad-hoc BI
Tableau / Qlik
Analytics
Engine
R / SAS
Informatica
BIG DATA
Edition
Near Real-
Time
Tableau / Qlik
Alerts
Machine Learning
Improved Models
Streaming
Role Based Dynamic
Data Masking
Adobe
Insights
(Online &
Offline Data)
Txt / Csv
Import
FTP

6. 6© Copyright 2016 EMC Corporation. All rights reserved. 6© Copyright 2016 EMC Corporation. All rights reserved.
DEMO

7. 7© Copyright 2016 EMC Corporation. All rights reserved.
Stream
Processing
Transform
Dashboard
Ambari
Interactive
Data
Storage
Streaming
Forwardto
spark
ETL
Informatica BIG
DATA Edition
Alerts
IngesttoHDFS
JMS
Fast and Batch
Ingest
Near Real-Time
Batch Interactive
Load to
HDFS
SOURCE DATA
Email,
Call Logs,
Documents
Click Stream
Policy, Quote,
Claim Data
Customer Account
Data/CRM/MDM
EDW
REST
Streaming
JMS
Analytics
Tableau /
Qlik /
SHINY
Distributed DB
Query Engine
NoSQL
HBase
SQL
Interface
Phoenix
ETL /
MDM
Customer
360
SQL on
Hadoop
Ad-hoc BI
Tableau / Qlik
Analytics
Engine
R / SAS
Informatica
BIG DATA
Edition
Near Real-
Time
Tableau / Qlik
Alerts
Machine Learning
Improved Models
Streaming
Role Based Dynamic
Data Masking
Adobe
Insights
(Online &
Offline Data)
Txt / Csv
Import
FTP
WHAT YOU SAW
12,500 clicks
a second
Sessionization
and
Tokenization
Customer
Records
Digital
Profile

8. 8© Copyright 2016 EMC Corporation. All rights reserved.
WHAT IT RUNS ON – WELL THE DEMO RAN ON
A SINGLE MACHINE BUT…Technical
Orchestration
Service
Orchestration
Vmware
V-Realize
Cortex
Client Specific Tools
Hortonworks Data Platform
Computer and Memory (EMC Big Data Systems)
Storage and Parallelization (Data Lake)
Software Defined Network
Monitoring&Logging
AuditReporting