tom norton, torsten herkel – bb1691 - infrastructure positioning to underpin a big data strategy

© 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


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


Big DataWhat are key transformation on IT Infrastructure


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


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


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


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.-----------

-----------------------


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


Big Data and impact on Storage


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

!


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.


Big Data Management Lifecycle

Protection WorkflowRecords

Mgt.

Legend:

Capture

Backup & Restorati

on

Storage

Protection

Retention

Archival

Destruction

Movement

Governance


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


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


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


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


Where to start


Deriving IT Big Data Architecture

Assess your capabilities and

actual infrastructure

Identify Business Case and Analytics

Identify Data Sources

IT BIG Data Architecture

-------------------------

------------------


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


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


HP Approach supporting Big Data Initiatives


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


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


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


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


• 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


Thank you

tom norton, torsten herkel – bb1691 - infrastructure positioning to underpin a big data strategy

Technology

big data functionalities

big data classification

devicesenterprise data

big data initiative3

transformation variables

data velocity andsources

data sources exampledatawhy

big datawhat