BO DI

Business Objects Data Integration Online Training Course

SAP DATA SERVICES 12.2.1/BODI

Overview of Data Services
Introduction of Data Services Architecture

●Data Services Designer
● Data Services repository
● Data Services Job Server
● Data Services engine
● Data Services Access Server
● Data Services Address Server
● Data Services Administrator
● Data Services Metadata Reports applications
● Data Services Service
● Data Services SNMP Agent
● Data Services Adapter SDK
● Data Services SAP RAPID MARTS

Preparing to Install Data Services Client /Server Components

● Pre-installation overview
● Installation scenarios

Repository Creation

● Repository database requirements and preparation
● Creating a Data Services repository and Selecting a repository
● Central versus local repository creation with live examples
● Using the Repository Manager.
● Multi-user Environment Setup
● Activating a central repository
● Implementing Central Repository Security
● Data Services and multiple users
● Security and the central repository
● Version Checking.
● Adding objects to the central repository Checking out

Logging into the Designer

● Project area
● Tool palette
● Workspace.
● Local object library
● Object editors and Working with objects

About Projects and Jobs

● Executing Jobs
● Overview of Data Services job execution
● Preparing for job execution
● Monitoring Jobs

Datastore creation and Overview

● Datastores and Data Flows — What is a data flow.
● Datastore and system configurations
● Multi-user Development
● Creating and managing multiple datastore configurations
● File Formats and what are file formats?
● File format editor, Creating file formats and Editing file formats

Configure a Job Server

● Changing Job Server options
● Configure an Access Server
● To configure Metadata Integrator
● To select a web application server

Using the Server Manager

● Performing a scripted installation
● Logging in to the Management Console
● Connecting the Data Profiler
● Troubleshooting installation problems
● Running Data Services components in multi-user mode

Publishing Data Services

Transformations and usage in data services

● Descriptions of transforms.
● Query transforms overview
● Data Quality transforms overview
● Lookup tables and the lookup_ext function

Data flow execution

● Creating and defining data flows
● Calling data flows to perform data movement operations
● Defining the conditions appropriate to run data flows
● Pass parameters to and from data flows

Work Flows and what is a work flow

●How to Creating a work flows
● Steps in a work flow and Order of execution in work flows

Creating real-time jobs

●Real-time source and target objects
● Testing real-time jobs

Overview of variables and parameters

● How to create Variables and Parameters.
● Using local variables and parameters and about global variables.
● Local and global variable rules.

Overview of data quality

● Address Cleanse transformation overview
● Data Cleanse.
● Match
● Design and Debug
● Using View Data to determine data quality
● Using the Validation transform.

Understanding changed-data capture

● Using CDC with Oracle sources
● Using CDC for targets/Sources

Data Services Management Console: Administrator

● Scheduling, monitoring, and executing batch jobs
● Connecting repositories to the Administrator
● Configuring, starting, and stopping real-time services
● Configuring Job Server, Access Server, and repository usage
● Configuring and managing adapters
● Managing users
● Publishing batch jobs and real-time services via Web services

Functions and ProceduresAbout functions

● Descriptions of built-in functions

Raising Exceptions by usingTry/catch blocks

● Catch error functions and other function calls
● Nested try/catch blocks
● If statements to perform different actions for different exceptions

Job Scheduling using scripting and How to use Scripts in BODS

● Data Services Scripting Language
● Python
● Python in Data Services

Batch Jobs

● Executing batch jobs, Scheduling jobs and Monitoring batch jobs

Using the Data Profiler

● Defining the profiler repository
● Column level profiling
● Detail profiling

Recovery Mechanisms

● Recovering from unsuccessful job execution
● Automatically recovering jobs
● Manually recovering jobs using status tables