TRAINING

Enroll Now

IBM InfoSphere Training  

In the Data Modeling with IBM InfoSphere Data Architect training course you will learn how to do data modeling using the IBM InfoSphere Data Architect. This is a fast paced course and its primary objective is to make you productive quickly in creating data models and using the tool. Unlike courses that focus only on mechanics of using the tool, you will also learn the best practices of data modeling together with the productive use of the tool. The course is suitable for modelers new to the InfoSphere Data Architect, those who are migrating from other tools, and the IT professionals who need to quickly master the task of data modeling.

The Data Modeling with IBM InfoSphere Data Architect training course begins with logical data modeling. We deal with various practical cases and show how to represent them with InfoSphere Data Architect models. Physical data models are covered next, including the modeling of databases and creation of DDL. Finally, we devote attention to InfoSphere Data Architect advanced automation capabilities for improving the productivity through transformations and team development. 

The Data Modeling with IBM InfoSphere Data Architect training course uses InfoSphere Data Architect Version 7.5.

The course can be customized for those transitioning from other tools, such as CA ERwin or Embarcadero ER/Studio.

Objectives

Upon completion of this course, attendees will be able to:

• Create logical and physical data models
• Apply best practices of data modeling
• Reverse engineer existing databases
• Productively use InfoSphere Data Architects
• Use transformation of models

Audience

The Data Modeling with IBM InfoSphere Data Architect training course is intended for roles involved in data modeling and development.

• Data Modelers
• Data Developers
• Data Specialists
• DBAs

Pre Requisites

Attendees must be familiar with basic concepts of relational databases.

IBM InfoSphere Course Content

Introduction to Data Modeling

• The Value of Modeling
• Logical Data Modeling
• Physical Data Modeling
• InfoSphere Data Architect

Logical Data Modeling

• Entities
• Attributes
• Relationships and Cardinality
• Optional and Mandatory Relationships
• Aggregation and its Challenges
• Applying Normalization
• Supertypes, Subtypes and Their Proper Use
• Recursive Relationships
• Using Domain Data Types and Domain Models
• Data and Metadata
• Business Rules
• Naming
• Glossary Models
• Integrating Data Models and Use Cases
• Precision
• Quality Criteria for Models

Physical Data Modeling

• Creating physical models based on logical models
• Physical Data Modeling and Databases
• Reverse Engineering Databases
• Creating DDL
• Working with Indexes, Views and Storage Information

Transformations

• Transforming Logical Models into Physical Models
• Transforming Physical Models into Logical Models
• Transforming XML Schemas
• Transforming UML Models

Advanced InfoSphere Data Architect Functionality

• Web Publishing
• Reporting
• Team Support
• Partitioning Models
• Comparison and Synchronization of Models
• Impact Analysis
• Mapping Models
• Agile Development Workflow with Optim Development Studio