2011_04_14_BID

© 2010 SAP AG. All rights reserved. /

The Future of BI Decision-Making … Now with SAP HANA & HP

Snehanshu Shah Sr. Director, BA&T SAPLane Goode Manager, SAP Alliances & Solutions HPRuss Stanziale Director, SAP BI Consulting HP


Disclaimer

This presentation outlines our general product direction and should not be relied on in making a purchase decision. This presentation is not subject to your license agreement or any other agreement with SAP.

SAP has no obligation to pursue any course of business outlined in this presentation or to develop or release any functionality mentioned in this presentation. This presentation and SAP's strategy and possible future developments are subject to change and may be changed by SAP at any time for any reason without notice.

This document is provided without a warranty of any kind, either express or implied, including but not limited to, the implied warranties of merchantability, fitness for a particular purpose, or non-infringement. SAP assumes no responsibility for errors or omissions in this document, except if such damages were caused by SAP intentionally or grossly negligent.


Years It Took to Reach a Market Audience of 50 Million

Radio38 years

TV13 years

Internet4 years

iPod3 years

Facebook2 years

In 2005, mankind created 150 exabytes (1 exabyte = 1B gigabytes = 10B copies of The Economist). In 2011, 1,200 exabytes will be created.

Wal-Mart handles 1M customer transactions every hour, feeding 2.5 petabytes of data, the equivalent of 167 times the books in the Library of Congress.

Facebook houses 40B photographs.

Google processes 1 petabyte of search data every hour.

Decoding the human genome took 10 years when it was done initially in 2003. Now, it can be done in one week.

Source: Data, Data, Everywhere - The Economist, 2/25/11

The Data Explosion


Challenges of Real-Time Enterprise

Explosive growth of data

Speed of business requiresrapid consumption of information for immediate action

Different systems, different data types, diverse locations

© 2010 SAP AG. All rights reserved. / © 2010 SAP AG. All rights reserved. / Executive Board Meeting Page 5 CONFIDENTIAL

Time Value of Information

Impact

Tim

e


In A Perfect World ....

Cost Effective Management of Large

Data Volumes

Current & Complete Information

Immediate Answer to Any Questions



Data Volumes



Reality... Cannot Meet All 3 Requirements


Extraordinary and expensive measures are taken ….

Increased TCOand a

Dissatisfied Business Community

Increased TCOand a

Dissatisfied Business Community

While optimizing systems we’ve sub-optimized business results, by:

Deleting Details (aggregation)

Restricting Information Access

Deploying Multiple Databases

Duplicating Information

Building Complex Extract/Transform/Load logic

Incurring Lengthy Validation/Approval Processes


Potential Losses.....

Missed Deadlines

Blind Spots

Slow Reaction

Non-Compliance

Lack of Competitive Differentiations

Missed Opportunities

Inaccurate Forecasts/Plans


“By 2012, 70% of Global 1000 organizations will load detailed data into memory as the primary method to optimize BI application performance.”

- Gartner


In-Memory Computing – The Time is NOWOrchestrating Technology Innovations

HW Technology Innovations

64bit address space – 2TB in current servers

100GB/s data throughput

Dramatic decline in price/performance

Multi-Core Architecture (8 x 8core CPU per blade)

Massive parallel scaling with many blades/servers

Inexpensive memory modules

Current IBM Server config ~1 core / 16GB memory

Row and Column Store

Compression

Partitioning

No Aggregate Tables

Insert Only on DeltaReal-Time Update

The elements of In-Memory computing are not new. However, dramatically improved hardware economics and technology innovations in software has now made it possible for SAP to deliver on its vision of the Real-Time Enterprise with In-Memory

business applications

SAP SW Technology Innovations


Your Reality With SAP In-Memory Solutions


Data Volumes



Speed

Scale

Flexible


Your Reality With SAP In-Memory Solutions

Speed

Scale

Flexible

Groundbreaking In-Memory HW

Innovations100x Faster Analytics

Real-Time Access to Transactional Data


SAP HANA Proof-Points

© 2010 SAP AG. CONFIDENTIAL - FOR INTERNAL USE ONLY – SUBJECT TO TERMS/CONDITIONS/ASSUMPTIONS CONTAINED IN DOCUMENT / CONFIDENTIAL

In-Memory Computing Engine

Admin and Data Modeling

Real–Time Replication Services

Data Integration Services

In-MemoryComputing

Calculation and Planning

Engine

SAP NetWeaverBW

3rd Party

SAP Business Suite

Other Applications

SAP BusinessObjects

MDX SQL BICS

Data Management Service

SAP HANASAP High-Performance Analytic Appliance

Preconfigured Analytical ApplianceIn-Memory software + hardware(HP, IBM, Fujitsu, Cisco)

In-Memory Computing Engine SoftwareData Modeling and Data ManagementReal-time Data replication for SAP ECCData Integration for 3rd Party Systems

Capabilities EnabledAnalyze information in real-time at unprecedented speeds on large volumes of non-aggregated dataCreate flexible analytic models based on real-time and historic business dataFoundation for new category of applications (e.g., planning, simulation) to significantly outperform current applications in categoryMinimizes data duplication


Simplifying CO-PA Analysis - Large CPG Company

Approximately 70,000 dunning items generated in total1.8 million rows read

Not scalable & long run-time on reports 10 minutes to hours is typical. Report time-out is common

In-flexibleCan only analysis by limited number of attributesHierarchies are fixed. Can’t easily change heirarchies

Approximately 70,000 dunning items generated in total1.8 million rows read

Challenge – Standard CO-PA in SAP ECC

SAP HANA scenario for CO-PA implemented in 30 days on-siteReal-time replication of SAP ECC information

Implementation

Results

2.9 seconds

61 minutes (3660 seconds)

Standard CO-PA Report

600 million records

Drill-down to detail

Analyze any SKU, product family, region, time period …

HANA CO-PA Analysis


Query AccelerationLarge Euro Bank – Customer Contact Data Management

6.6

41.9

0 5 10 15 20 25 30 35 40 45

HANA

Traditional DB

Data Volume (GB)

Data Compression with HANA

0 500 1000 1500 2000 2500 3000

Query 1

Query 2

Query 3

3.2

5.1

5.1

1050

1320

2660

Query Run-Time (seconds)

Query Run-Time Comparison

Traditional DB HANA

6.3x Data Compression

369x Average Query Speed-Up

No Schema Changes

Same Data

Same SQL

Immediate Benefits

All inbound / outbound customer contact

Analyzed by a large # of groups w/in the Bank

Challenge:

Only 30 days of info stored due to size of dataset

Reporting ran 8 min to 8 hours


HANA Applications/Content

Strategic Workforce Planning Smart Grid Analytics

COPA case (includes financial line item reporting)

CRM & ECC Content (Q2 2011)

Inventory Movement

Billing Management

Smart Grid Analytics

SAP BW Powered by HANA

SAP BPC Powered by HANA

Order to Cash analysis

Trade Motions Management

Sales Pipeline Analyzer

Banking: Bank Analyzer

Demand Signal Repository

Available in Ramp-up Ramp-up H2 2011

20+ SAP Projects - H2 2011 for Ramp-up & GA Early 2012


In-Memory AnalyticsSAP HANA real-time operational analyticsComplete BI Suite with BI 4 runs on SAP HANA

One Store for Data and AnalyticsSAP HANA only persistence layer for SAP Business SuiteSAP Business Suite optimized for in-memory computing

Flexible real time analysis of operations at non-aggregated level

Real-Time operational planning and simulation capabilities: link to executionPrimary persistence and optimized for SAP BW

Reduced landscape complexityValue chain transformation

Capabilities

Benefits

Next-gen ApplicationsSAP BW fully running on SAP HANASAP HANA platform for in-memory appsSAP Business Suite runs on SAP HANAFurther optimization of BI 4 Suite for SAP HANAIndustry and LOB Analytic Apps

“Innovation“Mid-Term (Plan)

“Transformation”Longer-Term (Plan)

SAP In-Memory StrategyProduct Strategy and Plan

“Renovation”SAP HANA 1.0

Ramp-Up since Dec 2010


Polling Question #1:

What is your organization’s barrier to effective business analytics?

a) Effective self-service BI tools – Dependent on IT for reports

b) Access to timely data – takes too long to get the right information

c) Access to complete information – can’t drill-down to right level of details

d) Quality of information

©2010 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice

•Lane Goode, Alliance Manager, SAP Alliance and Solutions•Russ Stanziale, Americas Sales Director, Enterprise Information Solutions

MODERNIZING YOUR SAP ENVIRONMENTWITH SAP HANA

HP for SAP In-Memory SolutionsA full lifecycle methodology

• BI Strategy and DW Architecture

• Use Case, ROI

BWAHANA

• Sizing, configuration• Educate on best

practices• Factory Integration

• Implementation• Knowledge Transfer to your team

• Proactive Services (o/s patch, firmware)

• Reactive Services (break-fix)

• Integrated support w/ SAP

• Healthchecks• Upgrades• Collaboration with

SAP

HP’s SAP HANA 1.0

BW/EDWSAP Business Suite(ERP, SCM, etc.)

In-Memory Compute Engine

Replication server

BO BI 3.x“Other” BI tools BO BI 4.0

HP P

roLi

ant D

L 980

Server Management Tools

SLES11 SP1

HANA appliance

Business Objects

DataServices

In-Memory Database

1. Technology: HP Proliant-scalable, HA, automated, energy TCO; full stack HP owned and supported

2. HP Services: Expertise for Design, Build, Run

25

HP PREMA Architecture to scale up with confidenceIntroducing the HP ProLiant DL980 G7

Self-healing Resiliency– 200% boost in server availability– Redundant system fabric to maximize uptime

Balanced Scaling– World record performance enabled by HP Smart CPU caching

– Up to 8 Intel® Xeon® 7500 series processors

– Up to 8 cores and 24MB L3 cache per processor

– Up to 128 DDR3 DIMM slots; 2.0TB max memory!

– Up to 16 slots, PCI-E 2.0 or PCI-X

– Quad-Port 1GbE embedded NIC upgradable to Dual Port 10GbE

Breakthrough Efficiency – Consolidate up to 197 legacy servers on to a single system

– HP-only innovations like Thermal Logic, Sea of Sensors, and Dynamic Power Capping for ROI that competitors can’t touch

– iLO3 & Insight Control for tomorrow’s datacenter capabilities today

PREM

A Ar

chite

ctur

e

HP hardware configurations for SAP HANA 1.0

Appliance Size

Small (1)<1.2TB

Medium1.0TB– 2.5TB

Medium (2)1.0TB–2.5TB

Large2.5TB–5.0TB

X-Large (scale-out) >5.0TB (5)

Server HP ProLiant DL580 G7

HP ProLiant DL580 G7



HP ProLiant DL980 G7 x N

Processor 2 Nehalem-EX 4 Nehalem-EX 4 Nehalem-EX 8 Nehalem-EX

Memory 256G 512G 512G 1TB

Storage 2x300GB SASExt 25x146G SAS

2x300GB SASExt 25x146G SAS



SSD Storage 1x320GB FIO 2x320GB FIO 2x320GB FIO 4x320GB FIO

OS SLES11 SP1 SLES11 SP1 SLES11 SP1 SLES11 SP1

SAP SW Preloaded Preloaded Preloaded Preloaded

HP Svcs Incl. Incl. Incl. Incl.

HP services for SAP HANA 1.0

Factory based server

manufacturing

Factory Express services, incl.

on-site installation

Fast Start On-site

Integration services

HP Mission Critical Support for the HANA

Lifecycle

•Configure to Order from server factory•0D1

•Hardware components integration into a rack•HW configuration•OS & SW Load•Customer site physical install

•Network connection•Connection to source data•BO config•End-end validation•Access/use to ICE•Troubleshoot install•Etc

•Additional HANA services available upon request

–Dedicated account management–Risk reduction strategy– Proactive services– HP/SAP aligned Global support teams– Broad technical and process experience

BW/EDWSAP Business Suite(ERP, SCM, etc.)

In-Memory Compute

Engine

Storage or s torage controller

Replication server

BO BI 3.x“Other” BI tools

BO BI 4.0

HP

ProL

iant

DL

980

Server Management Tools

SLES11 SP1

HANA appliance

Bus iness Objects

DataServices

28 ©2010 Hewlett-Packard Development Company

3 SAP TRENDS IMPACTING YOU

Speed of ChangeSpeed of Change

2Technology

AdvancementsIn-memory/HANA

Technology Advancements

In-memory/HANA

1

Analytics Focus

Analytics Focus

3


CONSIDERATIONS FOR SAP HANA – HOLISTIC VIEW

Impacts To Your Infrastructure•How does SAP HANA Roadmap impact your plan & budget?

•How will SAP HANA impact your service level requirements?

•Will your IT POR require significant change?

Impacts To Your People•What skills will your IT and SAP support teams need?

•What training will your business users need?

Impacts To Your Strategy •SAP HANA will allow you to do things previously impossible

•How will you leverage this new power for strategic advantage?


SA

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Polling Question #2:

Where should your organization apply in-memory technology?

a) Financial Analysis (e.g., profitability analysis, treasury management)

b) Business Operations (e.g., warehousing, supply chain, manufacturing)

c) Sales and Marketing

d) Business Planning (e.g., workforce planning, budgeting, resource optimization)

e) Other


WHERE DO YOU START?

SERVICES FOR SAP HANA

Financial Assessment for SAP HANA

Impact Analysis forSAP HANA

Solution Assessment for SAP HANA

Landscape Preparation For SAP HANA

Implementation Service for SAP HANA

HP Critial Advantage Proactive Services -Support for the SAP HANA solution

lifecycle

Mandatory SAP HANA Fast Start


NEXT STEPS

• Engage your HP Account General Manager for an SAP HANA planning session

• Schedule a workshop

• Schedule a phone call

• HP BI Consulting Services:

Russ Stanziale [email protected]


WHAT HP BRINGS

ExperienceHP has the most experience with SAP In-Memory products to date

KnowledgeWorking with SAP side by side during development & planning.

Very broad skill-base of highly-credentialed BI professionals.

PowerInfrastructure to push the limits of performance

Ability To ExecuteFrom start of the project to value achievement

PassionTo ensure great customer experience with SAP products


SAP HANA: Value PropositionAddressing Key Business Drivers

1. Real-Time Decision MakingFast and easy creation of ad-hoc views on businessAccess to real time analysis

2. Accelerate Business Performance Increase speed of transactional information flow in areas such as planning, forecasting, pricing, offers…

3. Unlock New Insights Remove constraints for analyzing large data volumes - trends, data mining, predictive analytics etc.Structured and unstructured data

4. Improve Business ProductivityBusiness designed and owned analytical modelsBusiness self-service reduce reliance on ITUse data from anywhere

5. Improve IT efficiencyManage growing data volume and complexity efficientlyLower landscape costs

Speed

Scale

Flexible


Questions?


THANK YOUTHANK YOU

2011_04_14_BID

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