sap business warehouse powered by sap hanafm.sap.com/data/upload/files/08_ny_hana_das.pdf · sap...

SAP Business Warehouse powered by SAP HANA

Joydeep Das, Vice President, SAP HANA Product Management, SAP

SAP HANA CIO Innovation Forum September 12, 2013 • New York

© 2013 SAP AG or an SAP affiliate company. All rights reserved. 2

14000+ Customers

VAST MAJORITY: CENTRAL EDW, HARMONIZING MANY SOURCE SYSTEMS

EMBEDDED INTO MISSION CRITICAL BUSINESS PROCESSES

200 New Installations/Month

3100+ BW 7.3 Customers

SAMPLE REFERENCE CUSTOMERS:

SAP NetWeaver Business Warehouse (BW)

Overview


SAP NetWeaver BW 7.3 Powered by SAP HANA

Business and IT Benefits

Speed and Accelerated performance

Excellent query performance => Improved decision making

Data load process speed up => Quick access to latest data

Accelerated In-Memory planning => Much faster planning scenarios

New Business Insights

Self-Service BI, Data modeling => Flexibility, agility to users

Combine EDW with HANA-native data => Better insights and decisions

Streamline landscape and simplify data management

Non-disruptive DB Migration => Quick time to value

No aggregates, indexes, rollups => Reduced complexity and administration

No user retraining, retain security setup => Leverage existing investment



300+ customers with 60+ in production


Project Scope

and Business

Scenario

One of the largest privately held oil and gas company in the world. They implemented a

BW on HANA pilot system running next to their production BW on Oracle system. They are

feeding delta loads from their production ECC to both BW on Oracle and BW on HANA.

Performance and

Scale Benefits

DSO: Loaded 1 million+ rows of delta data from ECC into biggest DSO (FI-GL line item)

with 1 billion rows of active data. On Oracle, the activation took 588 seconds. With BW on

HANA, the activation took 14 seconds. 42x performance improvement.

InfoCubes: 14 million rows of data into InfoCube for Lease Operations took 37 minutes in

BW on Oracle and only 12 minutes in in-memory optimized InfoCube in BW on HANA. 3x

performance improvement.

Compression: The Lease Operations InfoCube was 64.7 GB in BW on Oracle. The same

InfoCube in BW on HANA occupied 19.3 GB. 3x better compression

Customer

Quote

“I am able to access the lowest level of detail in our General Ledger DSO and the

performance is incredible. Using the intuitive, Excel-based Analysis Office Interface I can

navigate through 1 billion records in 10 seconds or less per navigation.”


Merit Energy company – business and IT benefits


• Optimize Power Procurement through demand/consumption analysis

• Improved Sales Planning through better understanding of customer behavior

• Accelerate Sales by targeting new offers for customers

• Improved Sales Planning by enabling POS analytics for sales, marketing & ops

• Reduce Stock-Outs through improved inventory visibility

• Reduce Operational Expenses by enabling real-time shipping fee calculations

• 50% Reduction in Inventory

• Improved Sales Planning – Track sales against targets on demand

• Improved Cash Flow by lowering Carrying Costs


More snapshots of business benefits


MIGRATION WITHOUT REIMPLEMENTATION – NO DISRUPTION OF EXISTING SCENARIOS

SAP HANA-optimized DataStore Objects and InfoCubes

SAP HANA In-Memory platform

In-Memory planning engine

Consumption of HANA artifacts created via HANA studio

BW staging from HANA

The reporting UI is not affected

SAP NetWeaver 7.3 BW on HANA

BW Data Modeling

Planning

Data Management

OLAP

Pro

ce

ss

Ma

nag

em

en

t

HANA

Push Down

Standard DataStore Objects

DB server and SAP NetWeaver BWA

Standard InfoCubes

BW Integrated Planning

HANA Data Marts running side-by-side BW

RDBMS

SAP NetWeaver BW on RDBMS

Data Modeling

Planning

Data Management

OLAP

Pro

ce

ss

Ma

nag

em

en

t


Why is it better?


Tables/partitions in SAP HANA can be marked as “non active”

Such tables/partitions are …

– loaded into RAM only when accessed

– loaded into RAM in case of read access (column-wise) and processed as

usual (same speed and functionality)

– loaded to RAM for merge process

(if new data was written and delta reaches limit)

– displaced from RAM with highest priority in case of RAM shortage

(but only then) or when actively a cleanup is triggered

BW automatically marks all PSA tables and all write-optimized DSO tables as

“not-active”, no extra maintenance or tuning is necessary

Data Stores (RAM)

Persistence

Layer

SAP NetWeaver BW 7.3, SP8 Highlights “Non Active” data concept - providing lower TCO by optimized RAM sizing


Optimized RAM Sizing

• “Non active” data concept has substantial

impact on SAP NetWeaver BW on SAP

HANA RAM sizing

• Assumption: only ~ 20% of “not active” tables

are required in memory, rest resides on disk

only.

• ABAP Sizing Report (note 1736976) for SAP

NW BW on HANA will take “not active” data

into account

Examples of

Customer Savings 32% 37% 28%

SAP NetWeaver BW 7.3, SP8 Highlights

“Non Active” data concept - reduces RAM sizing, thereby reducing TCO

0

500

1000

1500

2000

2500

3000

GB RAM Size without “non active” data consideration

GB RAM Size with “non active” data consideration


PERFORMANCE DATA VOLUME

• Data is read and/or written frequently

• In memory

• No restrictions, all features available

• Infrequent access

• On disk, no need to keep in memory all the time

• No restrictions, all features available

• Sporadic access

• Not stored in HANA DB; stored in Near-line Storage

• Restricted to NLS capabilities

Non-Active Data Concept

Hot

Warm

Cold

SAP NetWeaver BW 7.3, SP8 Highlights Multi temperature data - providing lower TCO by optimized RAM management


Next generation of an NLS solution

for BW powered via HANA

Data Aging strategy

Capabilities for reporting, ETL, and look-ups

Great query performance for all data without

administrative overhead

Reduced backup and disaster recovery efforts

Supported for HANA and RDBMS

SAP HANA BW

NL

S I

nte

rfac

e

Very frequent Frequent Rarely


Near Line Storage with SAP Sybase IQ


BW:

- SAP Extractors

- Data Services

- SLT

Native HANA:

- SAP Extractors (DXC)

- Data Services

- SLT

BW InfoProvider consumption in HANA

HANA model consumption in BW

HANA data staged into BW

BW data provisioning for HANA

Analytic Views

Consumption


Mixed scenarios


SAP NetWeaver BW 7.3 Powered by SAP HANA Accelerate move to SAP HANA environment with Rapid Deployment Service Packages

Planning Assessment for SAP HANA

• BW version

• # of objects

• Size of the database

• Unicode readiness

• Authorizations readiness

• Data flows readiness

• Legacy RDBMS

• Level of customization

• # of SAP and non-SAP data sources

• …..

RDS Service Package

BW Database Migration

• Unicode Conversion*

BW functional upgrade

• BW Authorization Migration*

BW Technical upgrade

Installation of SAP HANA

BW Data Volume Optimization

RDS Configuration

• Project plan

• Efforts

• Economical estimate

• Deliverables

• Delivery model

• Resources

• Architecture

• …

Based on the results of the Planning Assessment for SAP HANA the customer relevant services are determined and scoped, in

order to provide an end-to-end RDS Service Package. Depending on the specific services needed the RDS Service Package

will be sized.

*in this example Unicode Conversion and

BW Authorization Migration are not needed


Business benefits from BW in-memory are driven by

• Faster cycle times for planning for more responsive action

• Improved reporting performance and the impact on operations

• Deeper/broader data analysis for better decision making

BW on HANA extends analytics to enable a new culture of intelligence

• Drive more user analysis with less IT intervention

• Scale analytics across more individuals and user types

• Enable ad hoc analysis without compromising enterprise capacity

BW on HANA provides a kick-start for IT modernization

• Leverage existing BW investments without process redesign or app. reimplementation

• Speed transition to in-memory applications with your consolidated data foundation

• Leverage Enterprise data management disciplines to manage new data types & sources


Speeds operational responsiveness and enhances analysis


Hear directly from SAP

BW/HANA customers

BW on HANA cookbook –

learn how it works

Blogs from experts on BW

HANA key topics


LEARN MORE – EXPERIENCE SAPHANA.COM

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