This 40 hour course provides an introduction to SAP Business Objects Data Services (BODS), which is SAP's ETL platform. It allows users to extract, transform and load data from various sources into a single location. The course covers fundamental concepts like the BODS architecture and components. It teaches how to design ETL jobs using the BODS designer tool. Additional topics include defining source and target metadata, creating and troubleshooting batch jobs, using functions and scripts, platform and data quality transforms, addressing cleansing, data cleansing, matching and consolidating data, SAP interfaces, data profiling, and migration. The trainer has over 14 years of experience in data warehousing and business intelligence projects.

1. SAP Business Objects Data Services 4.0 – Topics
Duration: 40 hrs
Course Introduction: SAP Business Objects Data services are SAP’s ETL (Extraction
transformation and Loading) Platform. It combines industry-leading data quality and
integration into one platform. With Data Services, an organization can transform and
improve data anywhere. It provides a Single environment for development, runtime,
management, security and data connectivity.
• Fundamental capabilities of Data Services is extracting, transforming, and loading (ETL)
data from heterogeneous source systems, transform that data to meet the business
requirements of your organization, and load the data into a single location.
• You create applications (jobs) that specify data mappings and transformations using the
Data services designer. Use any type of data, including structured or unstructured data
from databases, flat files and ERP systems (such as SAP) to process and cleanse and
remove duplicate entries. You can create and deliver projects more quickly with a single
user interface.
1. Introduction to BODS
• BODS Architecture
• Components
2. Designer
• Project area
• Tool palette
• Workspace.
• Local object library
• Object editors and Working with objects
3. About Projects and Jobs
• Executing Jobs
• Overview of Data Services job execution
• Preparing for job execution
• Monitoring Jobs
4. Defining Source and Target Metadata
• Use data stores
• Working with Flat file sources

2. • Use data store and system configurations
5. Creating Batch Jobs
• Work with objects
• Create a data flow
• Use the Query transform
• Use target tables
• Execute the job
6. Troubleshooting Batch Jobs
• Use descriptions and annotations
• Validate and tracing jobs
• Use View Data and the Interactive Debugger
• Use auditing in data flows
7. Using Functions, Scripts, and Variables
• Overview of Functions
• Functions combining multi categories
• Introduction to scripting
• Overview of variables and parameters
8. Using Platform Transforms
• Describe platform transforms
• Use the Map Operation transform
• Use the Validation transform
• Use the Merge transform
• Use the Case transform
• Use the SQL transform
9. Setting up Error Handling
• Recovery Mechanisms
10. Capturing Changes in Data
• Update data over time
• Use source-based CDC
• Use target-based CDC

3. 11. Using Data Integrator Transforms
• Describe the Data Integrator transforms
• Use the Pivot transform
• Use the Hierarchy Flattening transform
• Describe performance optimization
• Use the Data Transfer transform
• Use the XML Pipeline transform
12. Using Data Quality Transforms
• Describe the data quality framework and processes
• Describe Data Quality transforms
13. Using Address Cleanse
• Understand the purpose of address cleansing
• Prepare your input data for the Address Cleanse transforms
• Define the Address Cleanse transforms
• Work with global address data
• Complete an Address Cleanse transform
14. Using Data Cleanse
• Understand the purpose of data cleansing
• Describe strategies for Data Cleanse transforms
• Complete a Data Cleanse transform
• Understand parsing dictionaries
• Refine data cleansing results
• Set up Universal Data Cleanse
15. Matching and Consolidating Data
• Understand the purpose of matching and consolidating records
• Use the Match Wizard to set up matching
• Configure the Match transform manually using the Match Editor
• Perform post-match processing
• Define advanced match strategies
16. SAP Interfaces using BODI
• Creating custom ABAP transforms
• IDoc sources in Batch jobs

4. • IDoc Targets in Batch jobs
• Adding an to a Batch job
• To Add an IDoc to a Batch job
17. Using the Data Profiler
• Column level profiling
• Detail profiling
18. Migration
• Job Export to ATL File
• Job Import from ATL File
• Job Migration across Environments
Trainer Profile Summary:
Trainer, Mr.Srikanth Addagiri, a veteran Data Warehouse and Business Intelligence expert with well
over 14 years of Software Development, Project Management experience, of which about a decade
of experience in the area of Data Warehouse and Business Intelligence projects. Mr. Srikanth has
rendered his technical expertise for large scale Data Warehouse and Business Intelligence projects
implementation for Fortune 500 companies, Government and public sector clients in various
business domains in Singapore and Asia Pacific region in the last decade.