The Executive View on Big Data Platform Hosting - Evaluating Hosting Services for Big Data Computing Cloud Expo 2013

1. Hitachi Consulting The Executive View on Big Data Platform Hosting
Evaluating Hosting Services for Big Data Computing
Better
Authors:
Chad M. Lawler, Ph.D.
Director of Consulting, Cloud Computing Practice - Hitachi Consulting
Art Vancil, CCP, CCSK
Senior Manager, Big Data Architect - Hitachi Consulting

2. Todays Purpose:
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•
Evaluate Big Data Hadoop Hosting Services
Considerations for Big Data POCs
Presentation Overview
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•
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The Solution Requirements & The Solution Stacks
The Application Development Process & The Platform Environment
The Evaluation and Decision Process & Hitachi Big Data Solutions & POC Approach
Today’s Presentation Available at:
•
http://www.slideshare.net/chadmlawler
Hitachi Consulting The Executive View on Big Data Platform Hosting
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| © Copyright 2013 Hitachi Consultingv a l u a t i n g
Hosting Services for Big Data Computing

3. Chad M. Lawler, Ph.D.
Director of Consulting, Cloud Computing Practice - Hitachi Consulting
• Advising Cloud Service Providers – Working with leading CSPs providing consulting services for
CSP strategy, planning, marketing analysis & research, product & service development, go-to-market
planning/ launch and internal process assessment optimization and automation
• Enabling Cloud Adoption - Providing an extensive portfolio of cloud adoption consulting services
to help businesses and organizations adopt, develop and implement cloud services and enable cloud
transformation.
• Cloud Service Brokerage & Multi-Cloud Governance – Delivery consulting and solutions to
positions CIOs to become Cloud Service Brokers for their organizations to centralize and streamline
management of multiple cloud services use, providing a single point of transparency, accountability,
sourcing and governance control
•
•
•
•
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Cloud Consulting, Executive Strategy & Planning
Cloud Product & Service Development
Cloud Competitive Market Analysis
Cloud Go-to-Market Strategy & Product Launch
Cloud Marketing & Sales Messaging, IP & Collateral
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•
•
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Chad M. Lawler, Ph.D.
Director of Consulting Services
Cloud Computing
14643 Dallas Parkway, Suite 800, Dallas, Texas 75254
Cloud Service Provider Advisory & Service Development
Cloud Business Case Development & Financial Modeling
Public, Private & Hybrid Cloud Computing
Cloud Service Governance Frameworks Consulting
Cloud Service Broker Solution Consulting
Office: 469.221.2894
Email: chad.lawler@hitachiconsulting.com
www.hitachiconsulting.com/cloud
www.linkedin.com/in/chadmlawler
www.cardcloud.com/chadlawler

4. Big Data Solution Requirements
Classes of Big Data Challenges
• Data set sizes that pose
significant challenges to
traditional data management
infrastructure
Volume
• Peta Bytes, Zetta Bytes
• Ability to create
Complexity
flexible analyses
• Ability to evolve analyses to
meet future needs
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• High velocity data that is
increasingly being used in
agile decision making
Velocity
Variety
• Data that is naturally
unstructured and/or rich in
structure that require
extensions of traditional
data management tools

5. Big Data Management
Fundamental Improvements
Unconventional
• Structural constraints to
performing new
Analytics – Prediction
analyses
& Sentiment Analysis
Larger Data Volumes
(petabytes)
Analysis of
Unstructured Data
• Data volumes and
velocity exceed
processing capacity
•Relational data
infrastructure is constrained
in handling Unstructured &
Rich Structured data
Integrate and Leverage • BI Capabilities
optimized for traditional
Existing BI
BI, not Big Data
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• Low cost Data Storage & Management Capacity
• Framework/platform driven high performance allowing creation of ondemand analytic structures
• Software Managed Recovery & Graceful degradation
• Minimized data movement within the environment
• On-line Component Recovery
• Capture data in raw form and process to meet evolving integration &
analytic needs
• Ability to overcome relational database limitations to handle rich structure
• Data Science discipline helps meet business demands
• Extension of BICC framework to manage Big Data class of problems

6. The Solution Stacks
Hitachi Innovation Platforms Aligned to Each Big Data Problem Class
• High Data Volume Solutions (Volume)
• Real-time Analytics Solutions (Velocity)
Hadoop and related
tools
Stream Data
Monitoring and
Analysis tools
Velocity
Volume
• Unified Information Access Solutions (Variety)
• Advanced Analytics (Complexity)
Text Parsing /
Taxonomy / Video
analysis / Indexing
tools
Variety
Statistical algorithms
Complexity
Choose the tools that align to your particular class of Big Data problems
Ex: High Data Volumes,
Mechanical Sensors,
Machine to machine
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Ex: Real Time Traffic,
Stock/Financial
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Ex: Social Media &
Marketing
Ex: Predictive
Analytics, Process
Optimization

7. The Big Data Application Development Process
Assessing the Capabilities to Deliver New Analytics Applications
Depending upon the enterprise and its requirements, the IT department will need to
develop capabilities and services in one or more of the Solution Stacks. The new
architectures are particularly demanding in a variety of ways:
•
Skills Development
•
Time to Market
•
Disaster Recovery
•
Operations and Maintenance
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8. The Big Data Platform Environment
How Does Cloud Delivery Impact Big Data Applications?
Some applications are easily migrated to the cloud and others strain under remote network
conditions, multi-tenancy security risks, virtualization performance overhead, or other cloud
model characteristics. Some of these characteristics are particularly troublesome for big
data solutions, while others are particularly advantageous:
•
Performance in the Cloud
•
Governance in the Cloud
•
Security in the Cloud
•
•
Data Growth in the Cloud
Termination of Services in the
Cloud
•
Business Continuity in the Cloud
•
Costs & TCO
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9. The Big Data Evaluation and Decision Process
Weighing the Delivery Options
Depending upon the rigor and maturity of their IT processes, an enterprise may or may not
have the opportunity to formally present their requirements and to evaluate various
platform options. For those teams who are able to do so, they may follow a simple
evaluation process outline:
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State the Prioritized Requirements
•
Measure the Options
•
Weigh the Options in terms of time, cost, and organization impact
The ultimate choice of a Big Data architecture and its components will be dependent upon
the solution class, the infrastructure site, and the infrastructure platform . These choices
will impact the feasibility, cost, and the success of the Big Data application.
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10. Big Data Solution Class & Infrastructure Platforms
Infrastructure Platform Suitability Varies by Solution Class
Infrastructure Platform
Supported sites
Single tenant
dedicated
• Customer site
• Managed Hosting
Multi-tenant
shared
• Managed Hosting
Virtualized
Multi-tenant private
cloud
• Managed Hosting
Virtualized
Multi-tenant
public cloud
• Public Cloud
Big Data Solution Class
High Volume
High Velocity
Unstructured Data
Advanced Analytics
Managed Services
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Production Performance
Platforms
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Lower Performance Platforms

11. Big Data Solution Infrastructure Platform Considerations
Infrastructure Platform Suitability Varies by Success Criteria
Success
Criteria
Infrastructure
Platform
Single tenant
dedicated
Multi-tenant shared
Virtualized
Multi-tenant
private cloud
Virtualized
Multi-tenant
public cloud
Security / Privacy
Internal Infrastructure Data
Movement
Performance impact
dependent upon
configurable bandwidth
Performance impact
dependent upon job mix from
all tenants
Performance impact dependent
upon job mix from all tenants
Performance impact dependent
upon job mix from all tenants
Data location control
Close proximity data is
practical
Some impact to data access
due to job mix
Some impact to data access
because of job mix
Least control over data location
User access network
configuration cost/effort
Network connectivity must
be configured
Network connectivity must be
configured
Network connectivity must be
configured
Connectivity is available
Performance Control
Performance throughput
Attainable
Impacted
Degraded
Degraded
End-user demand pattern
Consistent, steady demand
and loads
Inconsistent with idle and/or
high demand periods
High variability, extreme peaks
and lulls
High variability, extreme peaks
and lulls
High availability
Highest cost and effort
Shared cost and effort
Shared cost and effort
Readily available at lowest cost
and effort
Cost
Production Performance Platforms
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Lower Performance Platforms

12. Big Data Solution Platforms…. So What…?
Prepackaged Big Data Platforms are Not One Size Fits All!
Different Big Data Problem Classes
A single Big Data Platforms will likely not meet all the different requirements
Different Big Data Solutions
For Volume, Velocity, Variety & Complexity
Different Big Data Platform Tools
Different stacks of tools and applications for each class of problem
Different Big Data Infrastructure Options
Multiple infrastructure choices with different advantages and drawbacks
Different Big Data Delivery Options
Choices in how you manage the infrastructure, platform and tools
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13. Hitachi Consulting
Big Data Analytics Solutions
Global Center for Innovation Analytics
Better

14. Big Data Analytics Solutions - The Solution Stacks
Hitachi Analytics Platforms Aligned to Each Problem Class
Hadoop and related
tools
Stream Data
Monitoring and
Analysis tools
Volume
Velocity
Hitachi Innovation Platform for High
Data Volume Solutions (Volume)
Hitachi Innovation Platform for Realtime Analytics Solutions (Velocity)
High Volume Data storage/processing
Solutions
Hadoop HW and SW – optional cloud
management system
Hadoop Management tools
Ingestion tools
Search tools
Calculation tools
In-memory Solutions
Custom server appliance – optional
cloud management system
Near-line storage
HANA or equivalent software
Etc.
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Data Streaming Real-time Solutions
Hitachi’s HSDP (Hitachi Stream Data
Platform) and CQL (Continuous Query
Language)
Storage platform – optional cloud
management system
BI Analytics tools
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Text Parsing /
Taxonomy / Video
analysis / Indexing
tools
Variety
Hitachi Innovation Platform for
Unified Information Access
Solutions (Variety)
Document Processing Solutions
Document storage solution – optional
cloud management system
Document index and search solution
Taxonomy
Unified Information Access tool for
integration with structured analytics
Audio/ Video Processing Solutions
Data object storage solution – optional
cloud management system
Speech recognition and translation tool
Video recognition and identification tool
BI Analytics tools
Statistical algorithms
Complexity
Hitachi Innovation Platform for
Advanced Analytics (Complexity)
Pattern-matching Solutions
Data storage solution – optional cloud
management system
Statistical algorithm software
BI Analytics tools
Predictive Modeling Solutions
Data storage solution – optional cloud
management system
Statistical algorithm software
BI Analytics tools

15. Big Data Analytics Solutions
Hitachi Business Solution Focus
Business Solution Focus
Human
Capital
Customer,
Sales &
Marketing
Financial
Performance &
Risk Mgmt.
Advanced analytics to
help organizations
understand the causal
relationships that
influence productivity,
safety and employee
performance to
improve hiring,
training /
development,
promotion and
retention practices
Advanced analytics
to help businesses
and agencies to
build deeper
understanding of
customer
preferences &
behaviors to expand
their customer base,
improve customer
satisfaction, and
drive customer
profitability
Advanced analytics to
enable businesses and
agencies to gain more
visibility, control, and
understanding over
financial processes and
performance and to
more effectively
manage risk, fraud, and
compliance across an
organization
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Operations
Advanced analytics to
provide companies the
deep insight and
analysis needed to
become more
responsive
operationally by
anticipating and
responding to changes
aligning organizational
decision making with
operational and
strategic objectives
ADVANCED
ANALYTICS
Descriptive
Analytics
“What Happened
and Why”
Predictive
Analytics
“What Will Happen”
Prescriptive
Analytics
“What Should I Do”

16. Big Data Analytics Solutions
Hitachi Consulting & Hitachi Data Systems Trusted by Leading Organizations
FORTUNE® GLOBAL 500 COMPANIES
82%
OF FORTUNE
GLOBAL 100
9/10
3/4
>1/2
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OF TECHNOLOGY FIRMS
OF HEALTHCARE AND
TELCO
OF ENERGY, RETAIL,
MANUFACTURING,
INSURANCE,
TRANSPORTATION,
FINANCIAL SERVICES

17. Big Data Analytics Solutions
Hitachi Breadth of SAP HANA Services
THE HITACHI DIFFERENCE
Hitachi HANA Breadth of Services
Strategy
Converged
Platform®
HANA
Appliance
Accelerators
 Value Analysis
 Hardware
 Sizing
 Proof-of-Value
 Software
 Configuration
 Investment
Strategy
 Storage
 Scaling
 Rapid
Deployment
Solutions
 Services
 Implement
 Roadmap
 SAP and Hitachi
Accelerators
Solutions
 Services
 Demand Signal
Management
 Managed
Services
 Integrated
Planning
 Hosting
 Custom
Development
 Equipping
 Cloud Services
Hitachi is equipped to support every aspect of a HANA solution. We
are one of the very few SAP Partners who can provide this level of
support.
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18. Big Data Analytics Solutions - SAP HANA Live in Five
Value for Enterprise and BW on SAP HANA
1. Workshop




Use Case development
Metrics, goals for project
Scope, data sources
Develop Project timelines
 Standard Content and Modeling
 Data integration development
 Reporting and analytics development
 Knowledge transfer
 1-2 day Workshop to define
use case(s) / scope
 5 weeks from start to finish!
2. Blueprint to
execution
3. Tuning and
testing
 User testing
 Technology testing & validation
4. Validation
 Rapid use case(s) solution development
 Defined project metrics and ROI
 Rapid time to value for phase 1
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 Business and IT Metrics
 Goals
5. Acceptance
 Solution signoff
6. Develop plan to
move into
production

19. SAP HANA Analytics Customer Use Cases and Value
How are our Customers using SAP HANA?
1. Enterprise Data Warehouse
2. Agile Marts
3. Near Real-Time SAP Operational Reporting
4. Near Real-Time Data Hub
5. Big Data Analytics platform
6. Demand Signal Repository
7. Custom Web and Mobile Application platform
8. Advanced Analytics and Predictive Modeling platform
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20. There is a Great Deal to Consider to get Started with Big Data
So how do you Choose?
The way you get started in Big Data will impact what you end up doing in your enterprise
production deployment down the road.
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Data Model Complexities
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Agility, Flexibility & Configurability of the Environment
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Data Consistency
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Reliability, Availability, Performance, Security
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Operations & Management
So, it’s important to be proactive and make the right decisions and choices for your Big
Data solution stack, infrastructure and hosting environment. We recommend starting with
a Proof of Concept (POC) to explore and validate your business requirements.
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21. Big Data Analytics Solution POCs
Big Data POC & Governance Process
Scoping Workshop
-
1
2
Licensing
Delivery Execution
POC Platform
POC Services
3
4
5
Qualification &
Approval
Results Acceptance
by Customer Signs
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Solution Stack
HDS
HCC
Customer Signs
for POC
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Services Delivery
License
Implementation Platform
Implementation Services
6
7
HDS Big Data
Platform Delivery

22. Big Data Analytics Solution POCs
Big Data POC & Governance Process
1
2
3
4
Scoping
Workshop
Qualify
Approve
Delivery
Execution
Acceptance
Introduce
opportunity
Further qualify
and approve
POC
Provide
Licensing
HDS Roles
Propose
platform solution
Further qualify
and approve
POC
Deliver platform,
install, and
config
Demonstrate
Technical
Platform results
HCC Roles
Propose
application
solution
Further qualify
and approve
POC
Deliver design,
develop, and
demonstrate
results
Offer use case
and
requirements
Execute POC
Agreement
Provide facility
(optional),
coordinate,
support
Evaluate results
Execute
Implementation
Agreement
6
Demonstrate
Application
Solution results
Big Data
Platform
Roles
Customer
Roles
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5
License
Platform
Implementation
Implementation
7
Services
Implementation
Provide
License
Plan,
Coordinate,
Deliver
Implementation
Platform, install
and config
Plan, Coordinate,
Deliver
Implementation
Services
Receive and
accept
Maintain
support,
integrate, and
accept
Change
management
support, integrate,
and accept
Change
management

23. Big Data Analytics Solutions
Advanced Analytics Customer Centers, Client Service Teams, and Big Data Labs
Manchester
Denver
Santa
Clara
NYC
London
Dallas
- Advanced Analytics Customer Center
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- Client Teams
- Big Data Lab

24. Get Started with a Hitachi Big Data Analytics POC Today!
Hitachi Can Help You Explore Big Data Analytics with a POC
Explore Big Data Problem Classes
For Volume, Velocity, Variety & Complexity
Discover Hitachi Big Data Solutions
Determine how Hitachi Big Data Analytics Solutions Can Meet your Business Needs
Leverage Big Data Platform Tools
Implement the Right Stack of Tools & Applications for your Specific Big Data Needs
Implement on the Right Big Data Infrastructure
Leverage the Best-fit Infrastructure to meet your Business Analytics Requirements
Select the Big Data Delivery Option
Make the Right Choices for Manage Dig Data Infrastructure, Platform & Tools
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25. Hitachi, Ltd. – Global Technology Leader
Hitachi, Ltd. ranks 40th on the 2011 FORTUNE Global 500®
• Founded in 1910
• Invested $4.8 Billion in R&D (2011)
• $117.8B FY11 Revenue
• Strategic focus on Social Innovation Business
• 939 Companies
• More than 100 years of product and service
innovation, engineering and quality
• 323,540 Employees
Hitachi delivers innovations that answer society’s
challenges. With our talented team and proven
experience in global markets, we can inspire the world.
Society Changes, Hitachi Transforms It.
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26. Hitachi Consulting – Quick Overview
Delivering Business Transformation Services
Management
Consulting
Technology
Solutions
Managed
Services
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•
•
•
•
•
•
Operational Strategy & Implementation
Business & Operational Improvement
Organizational Transformation
Enterprise Performance Management / Analytics
IT Advisory
Environmental Sustainability Solutions
•
•
•
•
•
Enterprise Applications
Enterprise Technology
Application Development and Integration
Cloud & Big Data Solutions
Technology Infrastructure – Cloud, Premise, Mobile
•
•
•
•
Application Maintenance Outsourcing
Outsourced Product Development
Business Process Outsourcing
IT Outsourcing

27. Hitachi Consulting - Global Capabilities and Backing
Hitachi Consulting
North America
SEATTLE
PORTLAND
SAN FRANCISCO
LOS ANGELES
IRVINE
Hitachi Consulting
Europe
MANCHESTER
PHILADELPHIA
BOSTON
EDISON,NJ
BETHESDA
ATLANTA
CHICAGO
DALLAS
DALLAS
HOUSTON
MADRID
LISBON
Hitachi Consulting
Japan / China
LONDON
BEIJING
BARCELONA
GUANGZHOU
TOKYO
SHANGHAI
MIDDLE EAST
HYDERABAD
PUNE
BANGALORE
SINGAPORE
Hitachi Global
Delivery Centres

Assurance and backing of a global brand:

Hitachi Consulting Global capabilities and reach:

23rd largest Global Corporation

Revenues of over $600M

943 companies; 400,000+ employees

4,400+ employees

Global Delivery Centers in India and China
Integrated business with “one team”
approach:
30 Offices Worldwide



Consistent competencies and
structure across three continents

Design-build-run through a global
delivery model

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Ability to deliver global solutions
through global teams

28. Chad M. Lawler, Ph.D.
Director of Consulting Services
Cloud Computing
14643 Dallas Parkway, Suite 800, Dallas, Texas 75254
Office: 469.221.2894
Email: chad.lawler@hitachiconsulting.com
www.hitachiconsulting.com/cloud/
Connect with Me:
www.linkedin.com/in/chadmlawler
Today’s Presentation Available at:
http://www.slideshare.net/chadmlawler
Hitachi Consulting The Executive View on Big Data Platform Hosting
28
| © Copyright 2013 Hitachi Consulting
Evaluating Hosting Services for Big Data Computing

29. Hitachi Consulting The Executive View on Big Data Platform Hosting
Evaluating Hosting Services for Big Data Computing
Better
Authors:
Chad M. Lawler, Ph.D.
Director of Consulting, Cloud Computing Practice - Hitachi Consulting
Art Vancil, CCP, CCSK
Senior Manager, Big Data Architect - Hitachi Consulting