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© 2012 SAP AG. All rights reserved. 1

SAP Business Warehouse

powered by

SAP HANA

© 2012 SAP AG. All rights reserved. 2

Agenda – SAP NetWeaver BW Powered by SAP HANA

Overview

Deep Dive

Implementation

Next Steps

© 2012 SAP AG. All rights reserved. 3

?

In a Perfect World ...

Cost-effective

Management of Large

Data Volumes

Current and Complete

Information

Immediate Answer

to Any Question

? ?

© 2012 SAP AG. All rights reserved. 4

SAP in-memory innovations make

real-time business a reality

In-Memory

Row +

Column Database

Massively Parallel

Processing

Calculation Engine

Columnar storage increases the

amount of data that can be

stored in limited memory

(compared to disk)

Column databases enable

easier parallelization of

queries

Row database fast

transactional processing

In-memory processing

gives more time for

relatively slow updates

to column data

In-memory allows

sophisticated calculations

in real-time

MPP optimized software enables

linear performance scaling

making sophisticated calculations

like allocations possible

© 2012 SAP AG. All rights reserved. 5

Preconfigured Analytical Appliance

■ In-Memory software + hardware

(HP, IBM, Fujitsu, Cisco. Dell, Hitachi)

In-Memory Computing Engine Software

■ Data Modeling and Data Management

■ Real-time Data Replication Services

■ Data Services for ETL capabilities

Capabilities Enabled

■ Analyze information in real-time at unprecedented

speeds on large volumes of non-aggregated data

■ Create flexible analytic models based on real-time

and historic business data

■ Foundation for new category of applications

(e.g., planning, simulation)

to significantly outperform current

applications in category

■ Minimizes data duplication

SAP In-Memory Appliance (SAP HANA) Architecture

MDX SQL BICS SQL

Modeling

Studio

Real–Time

Replication

Services

Data

Services

SAP HANA

Other Applications SAP BusinessObjects

SAP NetWeaver

BW

SAP Business

Suite 3rd Party

In-Memory Computing Engine

Calculation and

Planning Engine

Row & Column

Storage

© 2012 SAP AG. All rights reserved. 6

Why you invested in SAP BW

Better

visibility

into your

business

One version

of the truth

Central view

across the

enterprise

Solid data

foundation

© 2012 SAP AG. All rights reserved. 7

But challenges are on the rise

Traditional RDBMS under SAP BW not keeping up

with todays business climate

© 2012 SAP AG. All rights reserved. 8

SAP BW powered by HANA is the

next step for your business

IT Value

Today

New Apps in

2012

Business

Value Today

Next Gen

Platform

© 2012 SAP AG. All rights reserved. 9

INSIGHT Unlock new

insights with the

most powerful

analytics available

FORESIGHT Deliver precise

business planning &

prediction on any data

at ANY level

RESPONSIVE 10x faster decisions

makes you more agile

than the competition

SAP BW powered by HANA:

BUSINESS VALUE TODAY Do more with your data. Be more responsive.

© 2012 SAP AG. All rights reserved. 10

“Enabling HANA to run under our SAP BW

system is a very important milestone. We can

now create key reports on shipping more

timely and accurately across all of our

plants. This is the kind of capability we need to

drive operational excellence and become

number one!”

XiaoYu Liu

Vice President

GM Global Applications Development

Lenovo

© 2012 SAP AG. All rights reserved. 11

AGILE Eliminate constant

remodeling, enable

self-service BI

FAST Dramatic 10x

improvement in data

loading and visibility

into real time info

SIMPLE Lower cost of ownership

& reduce administrative

tasks with no disruption

SAP BW powered by HANA:

IT VALUE TODAY End to End performance. Simplify your landscape.

© 2012 SAP AG. All rights reserved. 12

SAP BW powered by HANA Benchmark:

1000X better!

SAP HANA 100B uncompressed rows per second 100 TB Benchmark 100B Sales and Distribution Records 16 Node IBM X5 $640K Data Loading: 16M per minute with 20x compression BW Workload: 300ms - 500ms Ad-Hoc Analytics: 800ms to 2s No Database Tuning, No Indexes, No Caching

VS.

Oracle “With lightening fast scan speed of

up to 100 million rows/second and

enhancements like support for

analytical functions and up to 10x

columnar compression, TimesTen

for in-memory analytics delivers

faster reports & dashboards for

departmental as well as enterprise

wide consumption.”

© 2012 SAP AG. All rights reserved. 13

“With SAP HANA, we see a tremendous

opportunity to dramatically improve our enterprise

data warehouse solutions, drastically reducing

data latency and improving speed when we can

return query results in 45 seconds from BW

on HANA vs. waiting up to 20 minutes for

empty results from BW on Oracle.”

Weijun Zhang

IT Manager

Shanghai Volkswagen

© 2012 SAP AG. All rights reserved. 14

APPS Leverage all new

business apps &

solutions built

exclusively for

HANA

BW & ERP Starting with BW on

HANA today

prepares your for

the suite on HANA

NEXT GEN Literally hundreds of

new business

applications exclusive to

the HANA platform are

coming

SAP BW Powered by HANA:

APPS TODAY & NEXT GEN PLATFORM Amazing performance. Streamline your landscape.

© 2012 SAP AG. All rights reserved. 15

SAP BPC 10 NW

SAP Finance and Controlling

Accelerator

SAP Smart Meter Analytics

SAP Sales Pipeline Analysis

SAP Predictive Analytics

SAP Customer Segmentation

Accelerator

SAP HANA Platform

SAP Business Warehouse

SAP BusinessObjects BI &

SAP CO-PA Accelerator

SAP B1 Analytics

Third Party Apps

SAP ERP (Q4 2012)

Today

New Cloud Apps

New Mobile Apps

SAP Planning for Retail

SAP Customer Value Intelligence

SAP Predictive Segmentation

SAP Sales & Operations Planning

SAP Account Intelligence

SAP Demand Signal Management

SAP Account Intelligence

SAP Liquidity Risk Management

SAP Customer Energy Mgmt.

SAP Trade Promotion Mgmt

Future

Exclusive content. Killer apps.

© 2012 SAP AG. All rights reserved. 16

Agenda – SAP NetWeaver BW Powered by SAP HANA

Overview

Deep Dive

Implementation

Next Steps

© 2012 SAP AG. All rights reserved. 17

Eliminate

Relational DB

under BW

OS-DB

Migration

In-memory

calculation &

planning

SAP NetWeaver BW

Data Modeling

HANA

Data Management

Data Storage

Analytical / Planning

Engine

DBMS

SAP NetWeaver BW

Data Modeling

Analytical / Planning

Engine

Relational Database

Data Management

Data Storage

SAP NetWeaver BW – Fully In-Memory Enabled EDW

© 2012 SAP AG. All rights reserved. 18

Database migration is done using

standard SAP OS and DB migration tool

SAP BW 7.x

RDBMS

SAP BW 7.3 SP5

HANA BWA

BI clients BEx Query BI clients BEx Query

Pre-requisite: SAP HANA 1.0 SPS 03

© 2012 SAP AG. All rights reserved. 19

Factors Impacting BW Report Speed

Database Access

Time OLAP Computation

Report

Rendering

© 2012 SAP AG. All rights reserved. 20

BWA Acceleration

Database Access

Time OLAP Computation

Report

Rendering

DB OLAP Computation Report

Rendering

© 2012 SAP AG. All rights reserved. 21

HANA – In-Memory Acceleration for ALL Content

Database Access

Time OLAP Computation

Report

Rendering

DB

OL

AP

Report

Rendering

© 2012 SAP AG. All rights reserved. 22

Evolving In-Memory Footprint in SAP BW Overview

Planning Engine

Data Manager

InfoCubes

DataStore Objects

Analytic Engine

Data Persistency

and Runtime

Data

Modeling

Ente

rprise D

ata

Ware

house a

nd D

ata

Ma

rt M

odelin

g w

ith S

AP

NetW

eaver

BW

BWA instead of

aggregates

filter +

aggregation

BWA-only

InfoCubes

BWA reporting

for DSOs

reporting +

activation for

DSOs in-memory

in-memory

planning engine

first calculation

scenarios in BWA

additional

calculations

in-memory

MultiProvider

handling and

flexible joins

BW 7.0

DB + BWA 7.0

BW 7.3

DB + BWA 7.2 BW 7.3 on HANA

Data Provisioning

In-Memory

optimized

InfoCubes

Consumption of

HANA models in

BW

HANA data for

BW Staging

© 2012 SAP AG. All rights reserved. 23

SAP NW BW Query on

InfoCube,

Masterdata

AnalyticIndex,

CompositeProvider

Query on

DSO, BW InfoSet

SAP HANA

SQL Engine Calc Engine

Aggregation Engine on In-Memory data

Superior Reporting Performance

In-memory column store

Parallel query execution (MPP)

On-the-fly aggregation &

calculation

NEW HANA optimized DSO

and InfoCube objects

Fully leverage HANA In-memory architecture

Faster reporting for all BW objects - InfoCube, DSO

No indexes, pre-aggregation, query tuning

Fewer materialized layers, less lookup and faster queries

© 2012 SAP AG. All rights reserved. 24

Real-time Data Access

BW Schema Non-BW data

InfoCube Transient

Info Provider

Composite Provider

Query Query SAP BW

SAP HANA

Reporting & Analytics Tools

Replicate data in real-time into

SAP HANA operational marts

Build views in HANA against

operational data mart AND BW

schemas

Run HANA operational mart and

BW on same HANA landscape

Consume HANA Agile/Operational marts in BW

Real-time reporting in BW leveraging HANA operational data feeds

Simplified IT landscape for HANA operational mart and BW on HANA

© 2012 SAP AG. All rights reserved. 25

Simulate Faster and Plan More Frequently

Reduces network I/O

between App Server & DB

Reduces load on App Server

Performance boost for

planning capabilities like:

Aggregation, Disaggregation,

for Plan/Actual analysis, …

Execute calculations & planning in-memory

Plan with larger volumes of data improving planning accuracy

Plan more frequently (e.g. daily basis) improving planning speed

Plan with granular information (SKU or BOM level) improving insight

© 2012 SAP AG. All rights reserved. 26

Accelerated Planning

Traditional Approach

1. Determine the delta +50

2. Disaggregate (in appl. server)

per week (52)

per branch (500)

26000 combinations / values

3. Send 26000 values to DB to save

HANA-Based Approach

1. Determine the delta +50

2. Send 1 value to DB

+ instruction to disaggregate and

how

3. Disaggregate (in DB engine)

per week (52)

per branch (500)

create + save 26000 values

user changes

a plan value

© 2012 SAP AG. All rights reserved. 27

SAP runs SAP End to end financial planning on SAP HANA with SAP Planning and Consolidation

and the planning applications kit

Challenge

Planners using their own local, offline, non-

integrated tools with high TCO and high effort for

data reconciliation

Goal

Achieve a planning environment which is meeting

both corporate and lines of business demands -

an environment that is flexible, stable, reliable,

scalable and efficient

Solution

Implemented an integrated corporate and de-

centralized planning process with SAP Planning

and Consolidation 10.0, version for SAP

NetWeaver and the planning applications kit

running on SAP HANA

Benefits

Real-time reporting of plan and reference data

More time spent on business analysis - less time spent on data reconciliation

© 2012 SAP AG. All rights reserved. 28

Planned innovations Future vision Today

Vision for SAP Planning and Consolidation, version for SAP NetWeaver

– powered by SAP HANA

Support SAP HANA as the

underlying database

Enablement of customers

interested in SAP HANA to

move to the new platform

Performance gains with SAP

HANA

– Over time and with each

support package, the plan is

to leverage additional

functions of SAP HANA

Further enhancements

with SAP HANA

Accelerated reporting with the

SAP Planning and

Consolidation application

Automated variance analysis

(AVA)

Accelerated performance

Via support packages*

Customer-driven

innovations

Delivery of innovative

functionality to address

business needs

Further innovation of

SAP Planning and

Consolidation on

SAP HANA

Continued leveraging of SAP

HANA to improve performance

for other calculation-intensive

functionality

– Consolidations

– Logic scripts and allocations

– Business rules

– Driver-based planning

Near term (plan) Short term (plan) Midterm (plan)

*Planned future release, subject to change and

including support and enhancement packs

Key themes, capabilities, and planned innovations

© 2012 SAP AG. All rights reserved. 29

Reduced Load Windows

Delta calculation completely

integrated in HANA

No round trip between BW and

database which eliminates I/O

overhead

DSO activations & transformations In-memory

Speeds up data staging; DSO 5x-10x, InfoCube loading by 80%

Faster to build and maintain flattened in-memory BW data objects

Avoid storage of redundant data layers

© 2012 SAP AG. All rights reserved. 30

Greater modeling flexibility

Facts

D

D

MD MD

MD MD

Migration / New

Facts

M

D

M

D

M

D

M

D

F F E

In-memory optimized flattened InfoCube object

Fast data loads (no DIMIDs) up to 80% time reduction

No physical dimensions simplifies modeling and faster changes

All processes, all Queries and MultiProviders can remain unchanged

© 2012 SAP AG. All rights reserved. 31

Agenda – SAP NetWeaver BW Powered by SAP HANA

Overview

Deep Dive

Implementation

Next Steps

© 2012 SAP AG. All rights reserved. 32

Netweaver BW on HANA Solution Planning 3 Clear Steps with SAP Consulting

Your path to a successful deployment of SAP NetWeaver BW powered by SAP HANA follows a 3-step process…

© 2012 SAP AG. All rights reserved. 33

Migration Strategy

Deployment Options

–Full Migration

–Phased Migration

–Mixed Environment

Migration Steps

© 2012 SAP AG. All rights reserved. 34

HANA

Full Migration

Source Applications

BW 7.01

BWA RDBMS

Upgrade to 7.3 SP5+

BW 7.3 SP5+

Migrate RDBMS to HANA

© 2012 SAP AG. All rights reserved. 35

Full Migration

Considerations

Performs a migration of a BW system

– Any in memory optimization of objects will occur after migration

– By definition there is no partial migration

– Standard practice

© 2012 SAP AG. All rights reserved. 36

Phased Migration

Source Applications

HANA

BW 7.3 SP5+

BWA RDBMS

BW 7.x/3.5

Introduce New BW on HANA

Migrate

Content

BW 7.3 SP5+ .

Retire Old BW

© 2012 SAP AG. All rights reserved. 37

Phased Migration

Goal: Operate two instances of BW and migrate content over time

Potential Benefits

– Source BW may not need to be upgraded to 7.3 SP5

– In Memory Optimization can be done during migration

– Can optimize BW processes during migration (learning curve)

– Can manage BW upgrade costs

– Consider HANA Custom Data Mart Scenarios (e.g. Operational RDS)

Possible Drawbacks

– Need to operate multiple BW systems

– Providing combined reporting across BW systems requires design

– Potentially longer project duration/Becomes a mixed environment

© 2012 SAP AG. All rights reserved. 38

Mixed Environment

BWA

Source Applications

RDBMS

BW 7.x/3.5

HANA

BW 7.3 SP5+

Introduce New BW on HANA

Partial Migrate

Content

BW 7.3 SP5+ .

Retire BWA

© 2012 SAP AG. All rights reserved. 39

Mixed Environment

Goal: Operate two instances of BW Permanently

Potential Benefits

– In Memory based BW at a smaller scale.

– Manage BW upgrade costs

Possible Drawbacks

– Need to operate multiple BW systems (though typical for many customers)

– Providing combined reporting across BW systems requires some design

© 2012 SAP AG. All rights reserved. 40

Migration Strategy

SAP HANA Landscape Evolution – for review

Deployment Options

–Full Migration

–Phased Migration

–Mixed Environment

Migration Steps

© 2012 SAP AG. All rights reserved. 41

BW on HANA Solution Planning

Initial advisory design service drives more

effective projects and is tailored to individual organizational needs

• How can I most efficiently upgrade to BW 7.3? • Are there opportunities to optimize my BW

system? • Do I need to migrate my security

authorizations?

• What are some of the DB migration considerations I will need to consider?

• How do I properly size my implementation of HANA?

• Will Unicode be a factor for me?

Design your path to BW powered by HANA

Time to execute. Once to the required BW

support pack, you’re ready for BW on

HANA! BW 3.x / 7.x

System (Legacy DB/HW)

BW 7.3 (Legacy DB/HW)

BW Upgrade

Migrate to NW BW for HANA Prepare SAP NW BW for HANA

Current State BW on HANA

BW 7.3 (HANA)

Netweaver BW on HANA Solution Planning 3 Clear Steps with SAP Consulting

BW 7.3 Prepare

BW on HANA Migrate

BW on HANA Core Assessment

© 2012 SAP AG. All rights reserved. 42

BW 3.x / 7.x (Legacy DB/HW)

Current State

BW 7.3 SP7 (Legacy DB/HW)

BW 7.3 BW7.3 on HANA

Netweaver BW on HANA Solution Planning

BW 7.3 SP7 (HANA)

BW on HANA Core Assessment

Use Case Identification

Unicode Planning

BW Technical Upgrade

BW Authorizations

BW Data Volumes

Data Flow Analysis

Technical Upgrade

Unicode Upgrade

Functional Upgrade

Authorizations

BW Data Volumes

Data Flow Conversion

BW on HANA Upgrade

HANA Readiness

BW RDBMS RDS

BW on HANA Migration

Services Portfolio

1. BW Powered by HANA Pre-defined Planning Assessment

Services Portfolio

1. BW Technical Upgrade Build

2. Unicode Conversion

3. BW Authorizations Build

4. BW Data Volume Optimization

5. BW Functional Upgrade Build including In-Memory Conversion

Services Portfolio

1. SAP HANA Install and Configuration

2. SAP Rapid Deployment Solution for BW RDBMS to HANA Migration

© 2012 SAP AG. All rights reserved. 43

5 - 25 days 10 to 139 Days 40 Days

Rea

din

ess

Time Estimate

Minimum Consideration: 45 Days

Maximum Consideration: 204 Days

Design your Path to BW on HANA

Prepare Netweaver BW for HANA

Run BW on HANA

Netweaver BW on HANA Solution Planning End to End Time Line

© 2012 SAP AG. All rights reserved. 44

Main Landing Page – One Stop and “E2E Guide”

http://www.sdn.sap.com/irj/sdn/edw-ops

http://help.sap.com/nw73bwhana#section2

© 2012 SAP AG. All rights reserved. 45

Agenda – SAP NetWeaver BW Powered by SAP HANA

Overview

Deep Dive

Implementation

Next Steps

© 2012 SAP AG. All rights reserved. 46

SAP NetWeaver BW Powered by SAP HANA Value Proposition

Supercharge BW with Dramatically Improved Performance

Simplified Administration and Streamlined Landscape

Unlock The Power of Your Data Across The Enterprise

Preserve Your BW Investment without Disruption

1

2

3

4

© 2012 SAP AG. All rights reserved. 47

BW on HANA Incentives

No better time!

BWA to HANA

credit

Implementation

services credit

Exchange

flexibility

© 2012 SAP AG. All rights reserved. 48

Deploy Now! Rapid Deployment Solutions for HANA

BW HANA CRM

Analytics RDS

BPC for BW on

HANA RDS

BW to HANA

Migration RDS

© 2012 SAP AG. All rights reserved. 49

Sapphire

Attend Sapphire and Meet Successful Customers

Call Your SAP AE to learn more about BWA Conversion Credit

HANA powered by BW implementation Credit

© 2012 SAP AG. All rights reserved. 50

SAP HANA