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i want to learn sap-bw can anyone suggest me any material for bw.plz help me

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Part

I

Guided Tours

In Part I, we will tour basic SAP BW (Business

Information Warehouse) functionalities using a

simplified business scenario—sales analysis.

After introducing the basic concept of data warehousing and giving an

overview of BW, we create a data warehouse using BW and load data into it.

We then check data quality before creating queries and reports (or workbooks,

as they are called in BW). Next, we demonstrate how to use an SAP tool called

Profile Generator to manage user authorization.

After finishing the guided tours, we will appreciate BW’s ease of use and

get ready to explore other BW functionalities.

1

Contents

CHAPTER 1 Business Scenario and SAP BW

CHAPTER 2 Creating an InfoCube

CHAPTER 3 Loading Data into the InfoCube

CHAPTER 4 Checking Data Quality

CHAPTER 5 Creating Queries and Workbooks

CHAPTER 6 Managing User Authorization

28925 FU 01 001-016 r3rg.ps 6/27/02 4:04 PM Page 1

28925 FU 01 001-016 r3rg.ps 6/27/02 4:04 PM Page 2

Chapter

1

Business Scenario

and SAP BW

The objective of data warehousing is to analyze

data from diverse sources to support decision

making. To achieve this goal, we face two challenges:

• Poor system performance. Adata warehouse usually contains a large volume

of data. It is not an easy job to retrieve data quickly from the data

warehouse for analysis purposes. For this reason, the data warehouse

design uses a special technique called a star schema.

• Difficulties in extracting, transferring, transforming, and loading (ETTL)

data from diverse sources into a data warehouse. Data must be cleansed

before being used. ETTL has been frequently cited as being responsible for

the failures of many data warehousing projects. You would feel the pain if

you had ever tried to analyze SAP R/3 data without using SAP BW.

3

28925 FU 01 001-016 r3rg.ps 6/27/02 4:04 PM Page 3

SAP R/3 is an ERP (Enterprise Resources Planning) system that most large

companies in the world use to manage their business transactions. Before the

introduction of SAP BW in 1997, ETTL of SAP R/3 data into a data warehouse

seemed an unthinkable task. This macro-environment explained the urgency

with which SAP R/3 customers sought a data warehousing solution. The result

is SAP BW from SAP, the developer of SAP R/3.

In this chapter we will introduce the basic concept of data warehousing. We

will also discuss what SAP BW (Business Information Warehouse) is, explain

why we need it, examine its architecture, and define Business Content.

First, we use sales analysis as an example to introduce the basic concept of

data warehousing.

1.1 Sales Analysis—A Business Scenario

Suppose that you are a sales manager, who is responsible for planning and

implementing sales strategy. Your tasks include the following:

• Monitoring and forecasting sales demands and pricing trends

• Managing sales objectives and coordinating the sales force and distributors

• Reviewing the sales activities of each representative, office, and region

Suppose also that you have the data in Tables 1.1 through 1.3 available

about your firm’s materials, customers, and sales organization.

4 • PART I: GUIDED TOURS

TABLE 1.1

MATERIALS

Material Number Material Name Material Description

MAT001 TEA Ice tea

MAT002 COFFEE Hot coffee

MAT003 COOKIE Fortune cookie

MAT004 DESK Computer desk

MAT005 TABLE Dining table

MAT006 CHAIR Leather chair

MAT007 BENCH Wood bench

MAT008 PEN Black pen

MAT009 PAPER White paper

MAT010 CORN America corn

MAT011 RICE Asia rice

MAT012 APPLE New York apple

MAT013 GRAPEFRUIT Florida grapefruit

MAT014 PEACH Washington peach

MAT015 ORANGE California orange

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You also have three years of sales data, as shown in Table 1.4.

CHAPTER 1: BUSINESS SCENARIO AND SAP BW • 5

TABLE 1.2

CUSTOMERS

Customer ID Customer Name Customer Address

CUST001 Reliable Transportation Company 1 Transport Drive, Atlanta, GA

23002

CUST002 Finance One Corp 2 Finance Avenue, New York, NY,

10001

CUST003 Cool Book Publishers 3 Book Street, Boston, MA 02110

CUST004 However Forever Energy, Inc. 4 Energy Park, Houston, TX 35004

CUST005 Easy Computing Company 5 Computer Way, Dallas, TX 36543

CUST006 United Suppliers, Inc. 6 Suppliers Street, Chicago, IL

61114

CUST007 Mobile Communications, Inc. 7 Electronics District, Chicago, IL

62643

CUST008 Sports Motor Company 8 Motor Drive, Detroit, MI 55953

CUST009 Swan Stores 9 Riverside Road, Denver, CO

45692

CUST010 Hollywood Studio 10 Media Drive, Los Angeles, CA

78543

CUST011 One Source Technologies, Inc. 11 Technology Way, San Francisco,

CA 73285

CUST012 Airspace Industries, Inc. 12 Air Lane, Seattle, WA 83476

TABLE 1.3

SALES

ORGANIZATION

Sales Region Sales Office Sales Sales

Representative Representative ID

EAST ATLANTA John SREP01

NEW YORK Steve SREP02

Mary SREP03

MIDWEST DALLAS Michael SREP04

Lisa SREP05

CHICAGO Kevin SREP06

Chris SREP07

WEST DENVER* Sam SREP08

LOS ANGELES Eugene SREP09

SEATTLE Mark SREP10

*Prior to January 1, 2000, the Denver office was in the Midwest region.

28925 FU 01 001-016 r3rg.ps 6/27/02 4:04 PM Page 5

The data in these tables represent a simplified business scenario. In the real

world, you might have years of data and millions of records.

To succeed in the face of fierce market competition, you need to have a

complete and up-to-date picture of your business and your business environment.

The challenge lies in making the best use of data in decision support. In

decision support, you need to perform many kinds of analysis.

This type of online analytical processing (OLAP) consumes a lot of computer

resources because of the size of data. It cannot be carried out on an

online transaction processing (OLTP) system, such as a sales management

system. Instead, we need a dedicated system, which is the data warehouse.

6 • PART I: GUIDED TOURS

Customer Sales Material Per Unit Unit of Quantity Transaction

ID Representative ID Number Sales Price Measure Sold Date

CUST001 SREP01 MAT001 2 Case 1 19980304

CUST002 SREP02 MAT002 2 Case 2 19990526

CUST002 SREP02 MAT003 5 Case 3 19990730

CUST003 SREP03 MAT003 5 Case 4 20000101

CUST004 SREP04 MAT004 50 Each 5 19991023

CUST004 SREP04 MAT005 100 Each 6 19980904

CUST004 SREP04 MAT005 100 Each 7 19980529

CUST005 SREP05 MAT006 200 Each 8 19991108

CUST006 SREP06 MAT007 20 Each 9 20000408

CUST007 SREP07 MAT008 3 Dozen 10 20000901

CUST007 SREP07 MAT008 3 Dozen 1 19990424

CUST008 SREP08 MAT008 3 Dozen 2 19980328

CUST008 SREP08 MAT009 2 Case 3 19980203

CUST008 SREP08 MAT010 1 U.S. pound 4 19991104

CUST009 SREP09 MAT011 1.5 U.S. pound 5 20000407

CUST010 SREP10 MAT011 1.5 U.S. pound 6 20000701

CUST010 SREP10 MAT011 1.5 U.S. pound 7 19990924

CUST010 SREP10 MAT012 2 U.S. pound 8 19991224

CUST010 SREP10 MAT013 3 Case 9 20000308

CUST011 SREP10 MAT014 1 U.S. pound 10 19980627

CUST012 SREP11 MAT014 2 U.S. pound 1 19991209

CUST012 SREP11 MAT015 3 Case 2 19980221

CUST012 SREP11 MAT015 2 Case 3 20000705

CUST012 SREP11 MAT015 3.5 Case 4 20001225

TABLE 1.4 SALES DATA

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1.2 Basic Concept of Data Warehousing

A data warehouse is a system with its own database. It draws data from

diverse sources and is designed to support query and analysis. To facilitate

data retrieval for analytical processing, we use a special database design technique

called a star schema.

1.2.1 Star Schema

The concept of a star schema is not new; indeed, it has been used in industry

for years. For the data in the previous section, we can create a star schema like

that shown in Figure 1.1.

The star schema derives its name from its graphical representation—that is,

it looks like a star. Afact table appears in the middle of the graphic, along with

several surrounding dimension tables. The central fact table is usually very

large, measured in gigabytes. It is the table from which we retrieve the interesting

data. The size of the dimension tables amounts to only 1 to 5 percent of the

size of the fact table. Common dimensions are unit and time, which are not

shown in Figure 1.1. Foreign keys tie the fact table to the dimension tables.

Keep in mind that dimension tables are not required to be normalized and that

they can contain redundant data.

As indicated in Table 1.3, the sales organization changes over time. The

dimension to which it belongs—sales rep dimension—is called the slowly

changing dimension.

CHAPTER 1: BUSINESS SCENARIO AND SAP BW • 7

Customer ID

Customer Name

Customer Address

Customer ID

Sales Rep ID

Material Number

Per Unit Sales Price

Unit of Measure

Quantity Sold

Sales Revenue†

Transaction Date

Material Number

Material Name

Material Description

Customer Dimension

Sales Rep ID*

Sales Rep Name

Sales Office*

Sales Region*

Sales Rep Dimension

Material Dimension

Fact Table

FIGURE 1.1

STAR SCHEMA

*Sales Region, Sales Office, and Sales Rep ID are in a hierarchy as shown in Table 1.3.

†Sales Revenue = Per Unit Sales Price Quantity Sold.

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The following steps explain how a star schema works to calculate the total

quantity sold in the Midwest region:

1. From the sales rep dimension, select all sales rep IDs in the Midwest

region.

2. From the fact table, select and summarize all quantity sold by the sales

rep IDs of Step 1.

1.2.2 ETTL—Extracting, Transferring, Transforming,

and Loading Data

Besides the difference in designing the database, building a data warehouse

involves a critical task that does not arise in building an OLTP system: to

extract, transfer, transform, and load (ETTL) data from diverse data sources

into the data warehouse (Figure 1.2).

In data extraction, we move data out of source systems, such as an SAP R/3

system. The challenge during this step is to identify the right data. A good

knowledge of the source systems is absolutely necessary to accomplish this

task.

In data transfer, we move a large amount of data regularly from different

source systems to the data warehouse. Here the challenges are to plan a realistic

schedule and to have reliable and fast networks.

In data transformation, we format data so that it can be represented consistently

in the data warehouse. For example, we might need to convert an entity

with multiple names (such as AT&T, ATT, or Bell) into an entity with a single

8 • PART I: GUIDED TOURS

Data Warehouse

Load

Source System

Transform

Transfer

Extract

FIGURE 1.2

ETTL PROCESS

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name (such as AT&T). The original data might reside in different databases

using different data types, or in different file formats in different file systems.

Some are case sensitive; others may be case insensitive.

In data loading, we load data into the fact tables correctly and quickly. The

challenge at this step is to develop a robust error-handling procedure.

ETTL is a complex and time-consuming task. Any error can jeopardize data

quality, which directly affects business decision making. Because of this fact

and for other reasons, most data warehousing projects experience difficulties

finishing on time or on budget.

To get a feeling for the challenges involved in ETTL, let’s study SAP R/3 as

an example. SAP R/3 is a leading ERP (Enterprise Resources Planning) system.

According to SAP, the SAP R/3 developer, as of October 2000, some 30,000 SAP

R/3 systems were installed worldwide that had 10 million users. SAP R/3

includes several modules, such as SD (sales and distribution), MM (materials

management), PP (production planning), FI (financial accounting), and HR

(human resources). Basically, you can use SAP R/3 to run your entire business.

SAP R/3’s rich business functionality leads to a complex database design.

In fact, this system has approximately 10,000 database tables. In addition to the

complexity of the relations among these tables, the tables and their columns

sometimes don’t even have explicit English descriptions. For many years,

using the SAP R/3 data for business decision support had been a constant

problem.

Recognizing this problem, SAP decided to develop a data warehousing

solution to help its customers. The result is SAP Business Information Warehouse,

or BW. Since the announcement of its launch in June 1997, BW has

drawn intense interest. According to SAP, as of October 2000, more than 1000

SAP BW systems were installed worldwide.

In this book, we will demonstrate how SAP BW implements the star

schema and tackles the ETTL challenges.

1.3 BW—An SAP Data Warehousing Solution

BW is an end-to-end data warehousing solution that uses preexisting SAP technologies.

BW is built on the Basis 3-tier architecture and coded in the ABAP

(Advanced Business Application Programming) language. It uses ALE (Application

Link Enabling) and BAPI (Business Application Programming Interface)

to link BW with SAP systems and non-SAP systems.

CHAPTER 1: BUSINESS SCENARIO AND SAP BW • 9

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1.3.1 BW Architecture

Figure 1.3 shows the BW architecture at the highest level. This architecture has

three layers:

1. The top layer is the reporting environment. It can be BW Business

Explorer (BEx) or a third-party reporting tool. BEx consists of two components:

• BEx Analyzer

• BEx Browser

BEx Analyzer is Microsoft Excel with a BW add-in. Thanks to its easy-touse

graphical interface, it allows users to create queries without coding

SQL statements. BEx Browser works much like an information center,

allowing users to organize and access all kinds of information. Thirdparty

reporting tools connect with BW OLAP Processor through ODBO

(OLE DB for OLAP).

10 • PART I: GUIDED TOURS

FIGURE 1.3

BW

ARCHITECTURE

Source: Adapted from SAP BW online documentation.

Browser Analyzer

Non-SAP OLAP Clients

ODBO

Staging Engine

ALE/BAPI

PSA

BDS/ OLAP Processor

User Roles

InfoCubes/

ODS Objects

Data

Manager

BW Server

Metadata

Manager

Metadata

Repository

Scheduler

Administrator

Workbench

Monitor

Business Explorer

Extractor

Non-SAP System

Extractor

SAP System

OLE DB for OLAP Provider

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2. The middle layer, BW Server, carries out three tasks:

• Administering the BW system

• Storing data

• Retrieving data according to users’ requests

We will detail BW Server’s components next.

3. The bottom layer consists of source systems, which can be R/3 systems,

BW systems, flat files, and other systems. If the source systems are SAP

systems, an SAP component called Plug-In must be installed in the

source systems. The Plug-In contains extractors. An extractor is a set of

ABAP programs, database tables, and other objects that BW uses to

extract data from the SAP systems. BW connects with SAP systems (R/3

or BW) and flat files via ALE; it connects with non-SAP systems via BAPI.

The middle-layer BW Server consists of the following components:

• Administrator Workbench, including BW Scheduler and BW Monitor

• Metadata Repository and Metadata Manager

• Staging Engine

• PSA (Persistent Staging Area)

• ODS (Operational Data Store) Objects

• InfoCubes

• Data Manager

• OLAP Processor

• BDS (Business Document Services)

• User Roles

Administrator Workbench maintains meta-data and all BW objects. It has

two components:

• BW Scheduler for scheduling jobs to load data

• BW Monitor for monitoring the status of data loads

This book mainly focuses on Administrator Workbench.

Metadata Repository contains information about the data warehouse.

Meta-data comprise data about data. Metadata Repository contains two types

of meta-data: business-related (for example, definitions and descriptions used

for reporting) and technical (for example, structure and mapping rules used for

data extraction and transformation). We use Metadata Manager to maintain

Metadata Repository.

Staging Engine implements data mapping and transformation. Triggered

by BW Scheduler, it sends requests to a source system for data loading. The

source system then selects and transfers data into BW.

CHAPTER 1: BUSINESS SCENARIO AND SAP BW • 11

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PSA (Persistent Staging Area) stores data in the original format while

being imported from the source system. PSA allows for quality check before

the data are loaded into their destinations, such as ODS Objects or InfoCubes.

ODS (Operational Data Store) Objects allow us to build a multilayer structure

for operational data reporting. They are not based on the star schema and

are used primarily for detail reporting, rather than for dimensional analysis.

InfoCubes are the fact tables and their associated dimension tables in a star

schema.

Data Manager maintains data in ODS Objects and InfoCubes and tells the

OLAP Processor what data are available for reporting.

OLAP Processor is the analytical processing engine. It retrieves data from the

database, and it analyzes and presents those data according to users’ requests.

BDS (Business Document Services) stores documents. The documents can

appear in various formats, such as Microsoft Word, Excel, PowerPoint, PDF,

and HTML. BEx Analyzer saves query results, or MS Excel files, as workbooks

in the BDS.

User Roles are a concept used in SAP authorization management. BW

organizes BDS documents according to User Roles. Only users assigned to a

particular User Role can access the documents associated with that User Role.

Table 1.5 indicates where each of these components is discussed in this

book. As noted in the Preface, this book does not discuss third-party reporting

tools and BAPI.

12 • PART I: GUIDED TOURS

TABLE 1.5

CHAPTERS

DETAILING BW

COMPONENTS

Components Chapters

Business Explorer: Chapter 5, Creating Queries and Workbooks

• Analyzer and Browser

Non-SAP OLAP Clients Not covered

ODBO

OLE DB for OLAP Provider

Extractor: Chapter 3, Loading Data into the InfoCube, on how

• ALE to load data from flat files

Chapter 10, Business Content, on how to load data

from R/3 systems

Chapter 11, Generic R/3 Data Extraction

BAPI Not covered

Administrator Workbench The entire book, although not explicitly mentioned

BW Scheduler Chapter 3, Loading Data into the InfoCube, on BW

Scheduler

BW Monitor Chapter 4, Checking Data Quality, on BW Monitor

28925 FU 01 001-016 r3rg.ps 6/27/02 4:04 PM Page 12

1.3.2 BW Business Content

One of the BW’s strongest selling points is its Business Content. Business Content

contains standard reports and other associated objects. For example, BW

provides you, the sales manager, with the following standard reports:

Quotation Processing

• Quotation success rates per sales area

• Quotation tracking per sales area

• General quotation information per sales area

Order Processing

• Monthly incoming orders and revenue

• Sales values

• Billing documents

• Order, delivery, and sales quantities

• Fulfillment rates

• Credit memos

• Proportion of returns to incoming orders

• Returns per customer

• Quantity and values of returns

• Product analysis

• Product profitability analysis

CHAPTER 1: BUSINESS SCENARIO AND SAP BW • 13

Components Chapters

Metadata Repository The entire book, although not explicitly mentioned

Metadata Manager

Staging Engine Chapter 3, Loading Data into the InfoCube

PSA

Chapter 4, Checking Data Quality

ODS Objects Chapter 9, Operational Data Store (ODS)

InfoCubes Chapter 2, Creating an InfoCube

Chapter 7, InfoCube Design

Chapter 8, Aggregates and Multi-Cubes

Data Manager Chapter 12, Data Maintenance

OLAP Processor Chapter 13, Performance Tuning

BDS Chapter 5, Creating Queries and Workbooks

User Roles Chapter 6, Managing User Authorization

28925 FU 01 001-016 r3rg.ps 6/27/02 4:04 PM Page 13

Delivery

• Delivery delays per sales area

• Average delivery processing times

Analyses and Comparisons

• Sales/cost analysis

• Top customers

• Distribution channel analysis

• Product profitability analysis

• Weekly deliveries

• Monthly deliveries

• Incoming orders analysis

• Sales figures comparison

• Returns per customer

• Product analysis

• Monthly incoming orders and revenue

Administrative and Management Functions

• Cost center: plan/actual/variance

• Cost center: responsible for orders, projects, and networks

• Order reports

• WBS Element: plan/actual/variance

• Cost center: plan/actual/variance

• Cost center: hit list of actual variances

• Cost center: actual costs per quarter

• Cost center: capacity-related headcount

Former Member
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Try the SDN wiki? It has a lot of material on BI, including learning and certification paths.

https://www.sdn.sap.com/irj/sdn/wiki

Click on 'Business Intelligence (BI)'.

Hope this helps.

Sudha

Former Member
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Hi,

SAP Business Information Warehouse (BW) is SAP´s Data Warehouse solution. It has been specially developed to allow you to gather and analyze all kinds of statistical information in the best possible way.

The SAP Business Information Warehouse (SAP BW) is a core element of mySAP.com. SAP BW is an enterprise-wide information hub that enables data analysis from R/3 and other business application, including external data sources such as databases and the Internet. SAP BW also offers easy integration with other mySAP solutions, such as mySAP Supply Chain

Management (mySAP SCM), mySAP Strategic Enterprise Management (mySAP SEM), and mySAP Customer Relationship Management (mySAP CRM).

SAP BW is a comprehensive end-to-end data warehouse solution with optimized structures for reporting and analysis. To help knowledge workers quickly mine an enterprise’s business data, SAP BW is equipped with preconfigured information models and reports, as well as automatic data extraction and loading methods.

With an easy-to-use Microsoft Excel-based user interface, you can create, format, and analyze reports, and publish those reports to the web. Built for high performance, SAP BW resides on its own dedicated server. Online Transaction Processing (OLTP) and reporting activities are therefore separated, and system performance is not compromised.

If you have any SAP Business Information Warehouse queries, please feel free to raise it in the SAP BW Forum.

Check these links.

www.sap-img.com/sap-bw.htm

www.sap-img.com/business/difference-between-bw-technical-and-functional.htm

www.sap-img.com/business/what-is-spro-in-bw-project.htm

www.sap-img.com/business/questions-answers-on-sap-bw.htm

Hope this resolves your query.

Reward all the helpful answers.

Regards

p291102
Active Contributor
0 Kudos

Hi,

Check this below links.

/people/gilad.weinbach2/blog/2007/02/23/a-beginners-guide-to-your-first-bi-model-in-nw2004s

http://www.squidoo.com/BW

http://searchsap.techtarget.com/generic/0,295582,sid21_gci1182794,00.html

Thanks,

Sankar M

Former Member
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Hi,

This is the Best site for BW material .

" http://esnips.com/_t_/SAP+BW";

Regards,

Priyanka.

Former Member
0 Kudos

Hi,

The link below is a PDF for SAP-BW.

Check out this. it shud help u.

https://www.sdn.sap.com/irj/sdn/go/portal/prtroot/docs/library/uuid/505351fe-ec8c-2910-c5b5-a43bbf53...

****Reward points if useful.

All the best