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HP Experts: Tom Norton, Torsten Herkel, presentation deck from HP Discover 2012 Frankfurt “Infrastructure positioning to underpin a big data strategy"
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© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
Tom Norton, TC WW Big Data Strategy lead Torsten Herkel, TC EMEA Storage Service Line Manager
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
Infrastructure positioning to underpin a big data strategyTom Norton, and Torsten Herkel, / December, 2012
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.3
Agenda
1. Big Data: What are key IT Infrastructure transformation
2. Big Data and impact on Storage
3. Where to start?
4. HP approach supporting your Big Data Initiative
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
Big DataWhat are key transformation on IT Infrastructure
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.5
Todays Silo’ed Data Infrastructure
Central Internal Managed ContentCentral Internal Unmanaged
ContentExternal Content or Discarded Content
Document Managem
ent
Messaging Data
IM and VOIP O
pera
tion
/ G
overn
an
ce /
Secu
rity
Multi-Media
Op
era
tion
/ G
overn
an
ce /
Secu
rity
Sensors Data
Audio
Video
Business Transactions & Interactions CRM – ERM – SCM FMS – HRM
Op
era
tion
/ G
overn
an
ce /
Secu
rity
Social Media Data
Forum
Blog
Feeds
Web
Clicks
Images
GPS
Sensors devices
RFID
Other events
Business Intelligence & Analytics
Classic ETL Processing
Op
era
tion /
Govern
ance
/
Secu
rity
Op
era
tion /
Govern
ance
/
Secu
rity
Messaging System (example Exchange
/ Office 365 on cloud or on site)
Content Manageme
nt
File Sharing
File Hosting
Collaboration
Analytical, Dashboards, Reports, Visualization
Enterprise Data Warehouse
$ € ¥ Transaction Data
Op
era
tion
/ G
overn
an
ce /
Secu
rity
Search
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.6
Transformation Variables
Variety
Velo
cit
y
Vora
city
Volume
Big Data Transformation
Variables
Data creation & transport
Streaming data, milliseconds to seconds to
respond
Data quantityScale from terabytes to petabytes to zettabytes
Data in many formsStructured, unstructured,
text, multimedia
Data consumption Ingestion and
processing of Data
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.7
Big Data Integrated Model
Message Data
Document Management
Social Media Data
Multi-Media
Sensors Data
Operation, Support, Governance, Protection
Big Data Refinery Business Transactions and Interactions
Business Intelligence
Enterprise Data Warehouse
Analytical, Dashboards
Reports, Visualization
CRM – ERM – SCM FMS –
HRM
Web, MobileCapture
Store
AnalyzeDevelop
Search
Value Creatio
nShare and
refine
Big Data Architecture Framework
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.8
Business Case drive functionalities
Police Department On-Line Retailer Financial Institution
Big Question: What causes and deters crime?
Big Question: Why can big box stores cause our customer churn?
Big Question: Why do customers close their accounts?
Functional Architecture SolutionAcquire the functional requirements to drive the development of a comprehensive Reference Architecture (RA) that is used to build-out their Big Data Initiative.
Create a conceptual model to socialize the need and estimated investment required to build-out a Big Data solution. Process validates data velocity and volume assumptions.
Define disparate data sources that could yield insight from customer behaviors that portend of an account closure. Data sources used to estimate variety and voracity requirements.-----------
-----------------------
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.9
Big Data Functionalities impacts
Information Flows
Related Services
Related Infrastructure Systems
Variety Velocity
Voracity
Volume
Information Structure
Users & Organization
s
Servers Storage NetworkManagem
ent
Value
Related Services
Search Develop Analytics Security
Capture Store IntegrateGovernanc
e
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
Big Data and impact on Storage
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.11
Understand Data sources - exampleData Why we need Where are they Who Own
Financial Data transactions Transaction (SAP) load SQL Structured
Manufacturing Test data Tests cycle Photo & stream data
Customer feedback
Blogs and support calls Download
Semi-structured videos & photos
$ € ¥
Blog
$ € ¥SQL
!
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.12
Big Data Classification
!Class
Retention Period
Recovery Time Objective
(RTO)
Recovery Point Objective
(RPO)
Forensic Window
Vital / Critical 7 Yrs. 30 Mins. <10 Mins. 6 Mos.
Sensitive 5 Yrs. 90 Mins. < 1 Hr. 3 Mos.
Non critical 6 Mos. 48 Hrs. < 48 Hrs. 1 Mos.
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.13
Big Data Management Lifecycle
Protection WorkflowRecords
Mgt.
Legend:
Capture
Backup & Restorati
on
Storage
Protection
Retention
Archival
Destruction
Movement
Governance
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.14
Big Data Backup & Restoration
Backup & Restorati
on
Copying of Big Data to restore the original
Backup Mediums
Backup & Restoration
Policy
Technologies
Technologies
HP Data Protector
HP StoreAll
HP StoreOnce
Restoration Target
Restoration Time
Backup Mediums
Electronic Vaulting
Tape Backup
Storage Backup
!
Fire
Storm
Virus
Attack
Flood
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.16
Big Data Archival
Archival
Extreme Data Reduction
Scalable Storage
Archive Medium
Archival PolicyMoving Big Data no longer actively used
for long-term retention
Calendar
Data Classification
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.17
Big Data Destruction
Destruction
Removing Big Data making it
unrecoverable
PurgingHD
Shredding
HD Wiping Degaussing
Stored Internal
Data
HD Big
Data
HD Big
Data
Tape Big
Data
HD Big
Data
Data Classification
Archival Policy
Confidential
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.20
Big Data Storage
Capture Movement Storage The placing of
information at rest
Big Data Storage
Data De-duplicatio
n Hyperscale storage
Clustered Design
High Speed Query
High-Speed
Ingestion
Core Big Data Storage Requirements
HP Data Protector
StoreOnce on the server1
Integrated storage, solutions not only attach
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
Where to start
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.22
Deriving IT Big Data Architecture
Assess your capabilities and
actual infrastructure
Identify Business Case and Analytics
Identify Data Sources
IT BIG Data Architecture
-------------------------
------------------
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.23
Determining Service catalog sourcing
• Choose provider
• Negotiate pricing/service
• Setup access
• Same as cloud• Determine flow of data• Determine IT Services
(IaaS, Paas, SaaS)• Determine platform &
infrastructure
• Determine IT Services (IaaS, Paas, SaaS)
• Determine platforms & infrastructure
InternalProcessing
internal
Data is internal
HybridData is internal
& external
Processing internal & external
CloudCan process
data via cloud service
Data is external
Determine Data Accessing methods
Determine all services / Storage / Develop/
Determine Data Protection and
Governance
Determine integration with
Internal data sources
Determine ownership / governance
Determine integration with management
services
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.24
Platform characteristics supporting Big Data Refinery
Infrastructure impact examples
Data Type: Structured or Unstructured
MPP Real-time Analytics
Storage Type
Server Type
Data Movement: Network Impact
Linux or Windows
HighAvailability
Vertica Structured Local, DAS Commodity(HP Moonshot), or BL, DL class
TOR: 10GBE (HP5920AF)NIC: 4x1GbE(HP331FLR)
Linux Redundancy in-built
Autonomy
Both For IndexNAS, DAS (SAN)(IBRIX, 3Par)
Enterprise(DL or BL class)
NIC: 4x1GbE(HP331FLR)
Both Mirroring in-built
Hadoop Both Local Commodity(HP Moonshot)
TOR: 10GBE (HP5920AF)NIC: 4x1GbE(HP331FLR)
Linux with HP CMU (Windows coming)
Redundancy in-built
EDW/SQL/SAP
Structured SAN(3PAR, P4000, EVA)
Enterprise(DL or BL class)
Both OS and Application Clusters
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
HP Approach supporting Big Data Initiatives
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.26
Solutions that combine best in class products and services
HP offers the shortest route to success
Complete solution offering, providing
value to your business and securing your
company intellectual
capital.
Leading Hadoop Distributions
Leading Storage and Network
solutionsFactory-integrated solution
Consulting Services
Advisory, architecture,
compliance and performance
Seamless Analytics
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.27
Architecture Strategy
System Infrastructur
e
Protection and
Compliance
PlatformPerformanc
eTuning
Generating Business Value from Data
HP Big Data Consulting Services
Providing Infrastructure services for Collection Consolidation
Consumption and Protection of Data
Governance and Protection
Making IT departments relevant to business by gaining value out of Big
Data
volume, variety velocity and voracity
Architecture for Big DataProcess and
ConsumptionAccess and
Storage
Analysis
Consolidation
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.28
Reducing implementation riskHP Big Data Service Offerings
Big Data IT Infrastructure
Transformation
Storage ServicesServer & Network Services
Data Protection, Compliance &
Security Services
HP Roadmap Service for
Hadoop
Autonomy Design &
Implementation Services
Vertica Design & Implementation
Services
Infrastructure to support Big Data
Unstructured Data Analysis with
Hadoop
Enterprise wide Meaning Based
search with Autonomy
Structure Database & Data Warehouse with
Vertica
HP Enterprise Design and Reference Architecture
Implementation for Hadoop
HP Implementation for Hadoop (Cloudera)
Storage Optimization
Services
Secured Optimized
Available Network
Backup & Recovery Continuity
Impact Analysis Service
HP EDW / Fast Track DW Infrastructure
Implementation Services
Planning and ensuring
Business Value
Accelerating time to results
Riskless Integration
and Protection
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.29
HP Big Data Infrastructure Transformation Workshop
Objectives
• Identify an IT strategy to provide Big Data services / value .
• Determine Big Data functionalities to determine integration Architecture and standards.
• Define A cross IT approach that span across security, management, operations and standards
• Provide IT leadership leading Big Data Initiative with business
• Define your unique roadmap and actionable steps to ensure success
Benefits • Unify internal team around scope and initiative• Set common vision and leadership • A unified Transformation Model as reference for
your transformation• Cross functions linkages : different IT functions
with common model • Understand Big Data transformation initiative
and implications
• Understand how your organization can successfully afford unprecedented challenges of Big Data
• Understand how and where HP could contribute to your success
The service to create your IT Strategy
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.30
• Limits, challenges, key success factors• Stress what you have.• What best about storage today?
Key takeaways• Are all your teams aligned?• Are you leading transformation• Principles and
Requirements leading execution
• Is today infrastructure ready
• Do my teams have right skills?
Be prepared Is your infra. Ready?
Roadmap
Scope and boundaries
Common visionand leadership
Your Big Data
Initiative
• Needs define your unique journey
• HP can help you on any steps and solutions into your Big Data journey
© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
Thank you