SAP NetWeaver BW 7.3 powered by HANAa248.g.akamai.net/.../2016/10/8401a216-547c-0010-82c… · · 2016-07-07DataStore Objects in SAP NetWeaver BW 7.3 Overview and Challenge DataStore

SAP NetWeaver BW Powered by

SAP HANA and Future Roadmap

Lothar Henkes

April, 201

© 2012 SAP AG. All rights reserved. 2

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.

Agenda Introduction

SAP NetWeaver BW‟s use of In Memory technology

SAP NetWeaver BW powered by SAP HANA

Customer results

What‟s new with NetWeaver BW 7.3, SP8

Outlook- SAP NetWeaver BW 7.3 SP 9 and further Roadmap

Agenda Introduction



Customer results




Unlock The Power of Your Data Across The Enterprise Enterprise Data Warehousing – the single point of truth

Enterprise Data Warehousing - why

– Consolidate the data across the enterprise to get a consistent

and agreed view on your data

"Having data is a waste of time when you can't agree on an interpretation."

– Combine SAP and other sources together

– Standardized data models on corporate information

– Supporting decision making on all organizational levels

EDWs require a Database plus an EDW application

EDW with SAP NetWeaver BW -

a flexible and scalable EDW application

– Highly integrated tools for modeling, monitoring and managing the EDW

– Open for SAP and non-SAP systems

– Agile data modeling using BW workspaces

– Runs on top of HANA and other RDBMS

– Easy consumption of HANA Data Mart scenarios via virtualized data access

EDW with custom built application

– High development and maintenance efforts

– Variety of tools with lacking integration


SAP NetWeaver BW Adoption Productive SAP NetWeaver BW Systems – Constant Growth

Stable Product, Large installed Base,

Constant Growth

Adoption of SAP NetWeaver BW constantly

growing

Unaffected by economic downturn in 2009

~ 14.000 customers referring

to >17.000 productive systems

Usage

Vast majority: Central DWH, harmonizing many

source systems

Minority: One-to-One to an ERP

Embedded into mission critical business processes

12.000

13.000

14.000

15.000

16.000

17.000

18.000

Q1 0

9

Q2 0

9

Q3 0

9

Q4 0

9

Q1 1

0

Q2 1

0

Q3 1

0

Q4

10

Q1 1

1

Q2 1

1

Q3 1

1

Q4 1

1

Q1

12

Q2 1

2

Q3 1

2

Q4 1

2

Q1

13

Agenda Introduction



Customer results




Customer Value of BW Powered by SAP HANA

Speed and Accelerated performance

Excellent query performance for improved decision making

Performance boost for Data Load processes for decreased data latency

Accelerated In-Memory planning capabilities for faster planning scenarios

New Business Insights

Self-Service BI – Data modeling with BW Workspaces

Flexible combine EDW with HANA-native data for better insights and

decision making

Streamline Landscape and simplify data management

Non-disruptive DB Migration with SAP standard tools and services

Data persistency layers are cut out and admin efforts reduced: No

aggregates, indexes, rollups, statistics

Simplified data modeling and remodeling


SAP NetWeaver BW7.3 Powered by SAP HANA How Does BW 7.3 Running on HANA Differ from BW Running on xDB?

SAP NetWeaver BW 7.x on xDB

Standard DataStore Objects

Data Base server and SAP NetWeaver BWA

Standard InfoCubes

BW Integrated Planning

HANA Data Marts running side-by-side BW

SAP NetWeaver BW 7.3 on HANA

SAP HANA-optimized DataStore Objects

SAP HANA In-Memory platform

SAP HANA-optimized InfoCubes

In-Memory planning engine

Consumption of HANA artifacts created via HANA studio

BW staging from HANA

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.

Migration without reimplementation - no disruption of existing scenarios

BW 7.0x

BW 7.3

BW Upgrade

Migration


DataStore Objects in SAP NetWeaver BW 7.3 Overview and Challenge

DataStore Objects are fundamental building blocks

for a Data Warehouse architecture

They are used to create consistent delta information

from various sources

Reporting can be done on a detailed level

In today‟s RDBMS-based implementation, the

activation and querying operations are extremely

performance-critical

Active Data Table Change Log

Activation Queue

Query Delta upload

Parallel Upload

Activation


DataStore Objects in SAP NetWeaver BW 7.3 Creation of Consistent Delta Information

Current architecture

Activation algorithm calculates the changes of

each record and creates heavy load on the DBMS

Delta calculation performed on the application

server, too complex to push it down to the DBMS

as SQL/Stored Procedure

Roundtrips to application server needed for delta

calculation

Activation Queue

Sorted Full Table Scan

Data

Packages

Lookup Calculate

Delta Update

Active Data Table Change Log


SAP HANA-Optimized DataStore Objects Accelerated Data Loads

SAP HANA-optimized DSOs

Delta calculation completely integrated in HANA

Using in-memory optimized data structures for

faster access

No roundtrips to application server needed

Process of SID generation highly optimized for

HANA Optimized DSOs low impact on staging

performance

Speeding up data staging to DSOs by factor 5-10

Avoids storage of redundant data

After the upgrade to BW on HANA all DSOs

remain unchanged

Tool support for converting standard DSOs into SAP

HANA-optimized DSOs

Database

Layer

Database

Layer

User interface

Layer User interface

Layer

Application

Layer Application

Layer

Presentation

DSO Objects

Activation

Data

Presentation

DSO Objects

Activation

Data

SAP NW BW

SAP NW BW SAP NW BW

SAP NW BW

SAP HANA xDB



No changes of Data Flows required


SAP HANA-Optimized InfoCubes Faster Data Loads and Easier Modeling

Facts

MD MD

MD MD

F

Facts

D

D

MD MD

MD MD

F E

Conversion/New

Traditional InfoCubes tailored to a relational DB consist

of 2 Fact Tables and the according Dimension tables

SAP HANA-optimized InfoCubes represent “flat” structures

without Dimension tables and E tables*:

Up to 5 times faster data loads

Creation of DIM Ids no longer required

Simplified Data modeling

Faster remodeling of structural changes

After the upgrade to BW7.3, SP5 all InfoCubes remain unchanged

Tool support for converting standard InfoCubes

Preliminary lab result: 250 Million records in 4 minutes

No changes of processes, MultiProvider, Queries required



*Tables for compressed data


Query Performance Query Performance at Least as Good as with BWA

Query acceleration on BW InfoCubes

Leverage column store and In-Memory Calculation

Engine for query acceleration

No replication – fast query access directly on primary

data persistence

Indexes on InfoCubes and InfoObjects no longer required

No Rollups, Change runs

Query acceleration on BW DataStore Objects

Leverage column store and In-Memory Calculation

Engine for query acceleration

SID generation during DSO activation to be enabled

Result: Same kind of excellent query performance on DSOs

Process of SID generation highly optimized for HANA

Optimized DSOs low impact on staging performance

SAP NW BW Query on

InfoCube, DSO(with SIDs),

MultiProvider, Masterdata

AnalyticIndex, CompositeProvider

Query on

DSO(w/o SIDs), BW InfoSet

SAP HANA SQL Engine Calc Engine

Aggregation Engine on In-Memory data



No changes of processes, MultiProvider, Queries required


Query Performance Are InfoCubes Still Required ?

Query

DataStore Object

InfoCube

BW 7.x on

RDBMS

Aggregates

or BWA

index

InfoCube

BW on SAP

HANA

BW on SAP

HANA

InfoCube can be removed when used for query performance only

Info Cubes required for

Non-disruptive approach

when migrating to BW on HANA

Non-cumulative Key Figures

Complex business logic(report specific)

BW Integrated Planning

External write-interface(RSDRI)

Conclusion

There are scenarios where the InfoCube

layer becomes obsolete

Less materialized data and simplification

Decision to be made scenario by scenario:

Business and Performance needs

Conversion Conversion

DTP

DataStore Object DataStore Object (w SID generation)

DTP

Rollup


TransientProvider based on HANA Model

For ad hoc scenarios

Generated not modeled, no InfoObjects required

Full BEx Query support

Can be included in a CompositeProvider to combine with

other BW InfoProviders

VirtualProvider based on HANA Model

For a flexible integration of HANA data with BW managed

metadata (e.g. lifecycle)

Security handled by BW


Can be included to Composite- and MultiProvider to

combine with other BW InfoProviders

SAP BW

on HANA

SAP BW Schema

SAP HANA Schema(s)

HANA Analytical View

InfoCube TransientProvider Virtual Provider

Query Query Query

Composite

Provider

SAP HANA

Consumption of SAP HANA data models in BW

SAP NetWeaver BW – SAP HANA Interoperability


BW In-Memory Planning Accelerated Planning Functions

Database

Layer

Database

Layer

User interface

Layer User interface

Layer

Application

Layer Application

Layer

Presentation

Orchestration

Calculation

Data

Presentation

Orchestration

Calculation

Data

SAP NW BW

SAP NW BW SAP NW BW

SAP NW

BW

SAP HANA xDB

Traditional Planning runs planning

functions in the App. Server

In-memory Planning runs all planning

functions in the SAP HANA platform

Performance boost for planning

capabilities like:

Aggregation, Disaggregation

Conversions, Revaluation

Copy, Delete, Set value, Repost, FOX

Performance boost for plan/actual analysis



No changes of planning models, planning

processes, MultiProvider, Queries required


SAP NetWeaver BW – Post-Copy Automation (BW PCA)

Automated migration of SAP NetWeaver BW on RDBMS to

SAP NetWeaver BW on SAP HANA using BW PCA

Optimized downtime for SAP NetWeaver BW source system

Automated delta-queue cloning/synchronization

– Enables easy operation of original + new system in parallel

Automated clean up of target system

Automated post-copy configuration

Easier and faster migration to SAP NetWeaver BW on SAP HANA

Agenda Introduction



Customer results




SAP NetWeaver BW on SAP HANA Asian Paints

Project scope and

business scenario

Asian Paints, the biggest paint manufacturing company in India with very strong brand equity is

seen as the early adopter of cutting edge IT solutions, and is widely regarded in the SAP customer

community as very prolific user of SAP BI. In late 2011, Asian Paints decided to implement HANA

for their growing analytical needs for the large volume ERP and BW implementations, and with the

help of SAP Consulting implemented SAP HANA running under SAP BW in only 3 weeks.

Performance and

benefits

Data volume compression savings of 6:1 moving from BW/Oracle to BW/HANA

Significant improvement in the query performance: average query performance improvement

was15 x with maximum improvement 266x times.

Certain queries, for analyzing orders and billing that could not run in the past on BW-Oracle, are

returning the results with an impressive query response time of 15-20 secs with BW-HANA.

Data load time reduced by an average of 95% with some of the delta data load completing in 2

minutes in BW-HANA, paving the way for near real-time data extraction and analysis, compared

to more than 35-40 minutes it used to take in BW-Oracle.


SAP NetWeaver BW on SAP HANA Merit Energy

Project scope and

business scenario

Merit Energy is one of the largest privately held oil and gas companies in the world. They

purchased BW on HANA in Q4 2011 and implemented a BW on HANA pilot system that is running

next to their production BW on Oracle system. They are feeding delta loads from their production

ECC environment to both BW on Oracle and BW on HANA.

Performance and

benefits

DSO Activation

Biggest DSO is for FI-GL line items with nearly 1 billion rows of active data. From ECC, loaded 1

million+ rows of delta data into the FI-GL DSO. On Oracle, the activation took 588 seconds. With

BW on HANA, the activation took 14 seconds! 42x Improvement.

Data Loading

Loading 14 million rows of data into an InfoCube for Lease Operating System data took 37

minutes in the Oracle based BW system. With BW on HANA, the In Memory Optimized InfoCube

with no Dimension ID lookups took only 12 minutes for a 3x improvement.

Infocube Compression

The Lease Operating System InfoCube was 64.66 GB. With BW on HANA the same cube was

only 19.32 GB for 3x compression.

“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.” Customer

Quote


Yazaki Europe, an automotive supplier and the world‟s largest producer of wiring harnesses for cars and

trucks, had been using the 3.5 version of SAP NetWeaver BW 3.5. The company was having challenges

with the performance of the existing reporting system.

“We chose SAP NetWeaver BW powered by SAP HANA to improve and accelerate several processes in

the areas of finance and controlling, production and logistics and we have already seen major

improvements. We were able to accelerate processes within finance and controlling, such as end-of-

month closing, year-end closing and other common analysis in the area of controlling.”

“Our next big step will be the acceleration of processes within the productive ERP system, among others

in the area of production and logistics.”

With SAP NetWeaver BW powered by SAP HANA, Yazaki Europe has been able to accelerate reporting

and is now accessing reports faster out of info cubes and using creativity within reporting. In addition, they

are leveraging in-memory processing for fast acceleration of raw tables, calculations and BW metadata.

Salim Siddiqi,

CIO Yazaki Europe


More time for everyone

Agenda Introduction



Customer results




Overview

SAP HANA-specific highlights*

SAP BW and SAP HANA Mixed Scenarios

“Non active” data concept

Conversion of Semantic Partitioned Objects (SPO)

Enhanced Partitioning for write-optimized DSOs

Platform independent highlights

Enhanced Support of 3.x 7.x Dataflow Migration

File Download of BW meta data

DSO Planning

*please ensure to install the latest HANA revision


SAP NetWeaver BW – SAP HANA Mixed Scenarios: Combining the strengths of both worlds

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


TransientProvider based on HANA Model

For ad hoc scenarios

Generated not modeled, no InfoObjects required


Can be included in a CompositeProvider to combine with

other BW InfoProviders

VirtualProvider based on HANA Model

For a flexible integration of HANA data with BW managed

metadata (e.g. lifecycle)

Security handled by BW


Can be included to Composite- and MultiProvider to

combine with other BW InfoProviders

SAP BW

on HANA

SAP BW Schema

SAP HANA Schema(s)

HANA Analytical View

InfoCube TransientProvider Virtual Provider

Query Query Query

Composite

Provider

SAP HANA

Recap - Consumption of SAP HANA data models in BW before SP8




Optimized SAP HANA Data Load into

SAP NetWeaver BW

Complementary to DB Connect

Based on new source system type: Operational Data

Provider (ODP) with the context „HANA‟

Enable direct loading from HANA Views via DTP into BW

managed schema

Data persistency in PSA optional

Mass data loading

SAP BW

on HANA

SAP BW Schema

SAP HANA Schema(s)

SAP HANA Analytic /

Calculation / Attribute View

InfoCube

Data Transfer

Process

DSO MasterData

SAP HANA

Direct loading of HANA data into BW

ODP source system,

context ‚Hana„


SAP NetWeaver BW Virtual Master Data

HANA attribute view exposed as master data in BW

No data staging of SAP HANA master data required

Prior to SP 8 information in master data tables stored in

SAP HANA schema could only be consumed in BW query

via staging into BW

SAP BW

on HANA

SAP BW Schema

SAP HANA Schema(s)

SAP HANA Attribute

View

Virtual

Info

Object

Master Data Read

Class

Query

InfoProvider

Virtual

Info

Object

Virtual

Info

Object

SAP HANA


Easy consumption of HANA master data in BW queries


Open Hub Destination with new target

SAP HANA DB:

Support data transfer from BW InfoProviders,

DataSources and Queries into tables residing in SAP

HANA for further usage by HANA applications.

Default is 1:1 mapping, individual transformation can

be modeled

Delta extraction supported for InfoProviders and

DataSource

Query snapshots via QueryProvider are possible

Supported also for BW on classic RDBMS BW Schema HANA Schema

SAP BW

on HANA

SAP HANA

SAP BW Schema

SAP HANA Schema(s)

SAP HANA table

InfoCube Open Hub Service

DSO

MasterData

SAP HANA


Flexible BW Data Provisioning for SAP HANA applications

Query

DataSource


Generate Analytic View for BW

InfoProvider via HANA Modeler

Generated Analytic View contains basic BW

Metadata

Generated Analytic View can be consumed via

SAP HANA interfaces and used in further SAP

HANA models

This enables SAP BO Explorer on BW data

SAP BW

on HANA

SAP HANA

Explorer

consumes

BW Schema

SAP BW Schema

SAP HANA Schema(s)

SAP HANA

HANA Analytic View

Info

Cube DSO

Master

Data


Easy BW InfoProvider Consumption

generates

SAP HANA Studio


“Non Active” Data Concept *

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)

Providing lower TCO by optimized RAM sizing

Persistence

Layer

* Requires HANA SPS 5


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

Multi Temperature Data

Non-Active Data Concept

Providing lower TCO by optimized RAM management

hot

warm

cold


“Non Active” Data Concept – SAP NetWeaver BW

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

0

500

1000

1500

2000

2500

3000

Customer A

Software Industry

Customer B

Beverage Industry

Customer C

Automotive Industrie

GB RAM Size without “non active” data consideration

GB RAM Size with “non active” data consideration

32%

Reduces RAM sizing, thereby reducing TCO

37% 28%


Conversion of Semantic Partitioned Objects to HANA optimized

Source1 Source2 Source3

Sem

an

tic P

art

itio

ned

Ob

ject

(SP

O)

Source1 Source2 Source3

Sem

an

tic P

art

itio

ned

Ob

ject

(SP

O)

RSMIGRHANADB

SAP HANA

optimized SPO

Tool Support for Converting existing SPOs to HANA-optimized DSOs and InfoCubes

Integrated into standard conversion tool RSMIGRHANADB to ensure consistency during conversion

Conversion can be re-started at any time in case of failure

Providing Investment Protection for investment made in SPOs


Partitioning of Write-Optimized DSOs

Main Index

Delta Index

Merge

Request 1

Request 2 Request n

Better performance of write-optimized

DataStore Objects

Write-optimized DSO are now partitioned by request-ID

Partitioning improves merging performance

significantly, especially in case the delta Index is

merged for a large Write-Optimized DSO.

With partitioning only the relevant (last) partition (with

changed/new records) is merged.

In addition performance for read and delete is

improved, because with partition pruning only a subset

of the data is accessed.

Reduces data latency for Write-Optimized DSOs

Main Indexes

Agenda Introduction



Customer results




Planned Innovations Future Direction Today

SAP NetWeaver BW Product Roadmap Overview – Key Themes and Capabilities

Upcoming planned release

HANA-and platform independent

SAP NetWeaver BW Near Line Storage

solution (NLS) based on Sybase IQ

– Helps to reduce TCO by reducing data

volume in BW

– Shortens backup time frames

– High speed analysis for NLS residing

historical information

– SAP owned solution out of one hand

SAP NetWeaver BW Post-Copy Automation

Refresh

– Helps to reduce operations costs and risks

by automating post-copy configuration

tasks

– Availability planned with 2013/Q2 for all

releases from BW 7.0 onwards

Future innovations

Prepare for Big Data

Data LifeCycle Management /

Multi-temperature data

Bulk load capabilities

Dimensions with more than 2 billion members

Hadoop connection

Additional flexibility / agility

Harmonize SAP NetWeaver BW and

SAP HANA modeling

Eclipse based modeling environment in BW

e.g. BW Query Designer, CompositeProvider

PSA layer becomes optional

Leverage HANA libraries in BW

transformations

Support extra long texts

(Release SAP NW BW 7.3 SP8; SAP NW BW 7.31 SP5)

* SAP will continue to support RDBMS platforms

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.

SAP NW BW 7.3 on SAP HANA

SAP HANA specific features

Performance boost for data loading, query response

time and In-memory planning

SAP HANA-optimized InfoCubes and Data Store Objects

Simplified and faster data modeling/remodeling

“Not active” data concept

SAP NetWeaver BW and SAP HANA Mixed Scenarios

(BO Explorer, BW Virtual Master Data, etc.)

Support of Semantic Partitioned Objects and enhanced

partitioning for write optimized DSOs

Simplified system landscape

Platform independent highlights*

Graphical data flow modeling and enhanced support of

3.x-> 7.x data flow migration

Semantic Partitioned Objects (SPO)

Rapid prototyping of Ad Hoc scenarios via BW

Workspaces

File download of BW meta data

DSO planning

Tighter integration with SAP Data Services

(Release SAP NW BW 7.3 SP9; SAP NW BW 7.31 SP7)

© 2013 SAP AG. All rights reserved.

© 2013 SAP AG. All rights reserved.

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Documents

SAP NetWeaver BW 7.3 powered by HANAa248.g.akamai.net/.../2016/10/8401a216-547c-0010-82c… · · 2016-07-07DataStore Objects in SAP NetWeaver BW 7.3 Overview and Challenge DataStore