Training

IBM InfoSphere DataStage Essentials V8.7

Overview
This course works with Information Server V8.7
In this course, you will learn about the features of IBM InfoSphere DataStage V8 and learn how to build and run DataStage Extract, Transform and Load (ETL) jobs. Also covered will be information on DataStage V8.1 in its IBM Information Server environment. You will learn how to build DataStage parallel jobs that read and write data to and from a variety of data stores including sequential files, data sets, and relational tables. Additionally, you will learn how to build parallel jobs that process data in a variety of ways: business transformations, data filtering, data combining, data generation, sorting, and aggregating.
This course replaces course IBM InfoSphere DataStage Essentials V8

Audience
This is a basic course for project administrators and ETL developers responsible for data extraction and transformation using DataStage.

Prerequisites
You should have:
 Knowledge of the Windows OS
 Familiarity with Open Database Connectivity (ODBC) and relational database access technique

Objective
 Combine data using lookup, join, and merge stages
 Create jobs that read from and write to sequential files
 Make jobs that read from and write to a relational database using the connector stages
 Build jobs that process data using transformations, combinations, filterings, sortings and aggregations
 Conduct searches and impact analyses
 Produce job reports
 Construct DataStage users
 Administer the DataStage environment

For Registration click here

IBM InfoSphere DataStage Essentials 9.1

Overview
This course is designed to introduce ETL developers to DataStage 9.1.

Audience
This is a basic course for project administrators and ETL developers responsible for data extractions and transformations using DataStage.

Prerequisites
You should have:
 Basic knowledge of the Windows operating system and
 Some familiarity with database access techniques

Objective
 Describe the uses of DataStage and the DataStage workflow
 Describe the Information Server architecture and how DataStage fits within it
 Describe the Information Server and DataStage deployment options
 Use the Information Server Web Console and the DataStage Administrator client to create DataStage users and to configure the DataStage environment
 Import and export DataStage objects to a file
 Import table definitions for sequential files and relational tables
 Design, compile, run, and monitor DataStage parallel jobs
 Design jobs that read and write to sequential files
 Describe the DataStage parallel processing architecture
 Design jobs that combine data using joins and lookups
 Design jobs that sort and aggregate data
 Implement complex business logic using the DataStage Transformer stage
 Debug DataStage jobs using the DataStage PX Debugger
 Read and write to database tables using DataStage ODBC and DB2 Connector stages
 Work with the Repository functions such as search and impact analysis
 Build job sequences that controls batches of jobs
 Understand how FastTrack and Metadata Workbench can be profitably used with DataStage

For Registration click here

IBM InfoSphere QualityStage Essentials V8.7

Overview
This course teaches how to build QualityStage parallel jobs that investigate, standardize, match, and consolidate data records. You will gain experience by building an application that combines customer data from three source systems into a single master customer record.
This course replaces IBM InfoSphere QualityStage Essentials V8

Audience
This basic course is for:
 Data Analysts responsible for data quality using QualityStage
 Data Quality Architects
 Data Cleansing Developers

Prerequisites
You should be familiar with:
 Windows
 A text editor

Objective
 Describe data quality definition and issues
 Build QualityStage jobs to investigate data quality issues
 Build QualityStage jobs to cleanse data
 Consolidate duplicate records using QualityStage
 Create a consolidated view of customer records
 Create a reference match that will relate customers to event data

For Registration click here

IBM InfoSphere QualityStage Essentials 9.1

Overview
This course teaches how to build QualityStage parallel jobs that investigate, standardize, match, and consolidate data records. You will gain experience by building an application that combines customer data from three source systems into a single master customer record.

Audience
This course is for Data Analysts, Quality Architects and, Data Cleansing Developers responsible for cleaning up duplicates, redundant information, conflicting data will benefit from this course while helping them to use InfoSphere QualityStage in the most effective way.

Prerequisites
You should have familiarity with:  Windows
 A text editor

Objective
 Describe data quality definition and issues
 Build QualityStage jobs to investigate data quality issues
 Build QualityStage jobs to cleanse data
 Consolidate duplicate records using QualityStage
 Create a consolidated view of customer records
 Create a reference match that will relate customers to event data

For Registration click here

IBM InfoSphere QualityStage V8.5 Postal Modules

Overview
Learn how to build QualityStage jobs that standardize and verify address data. Gain hands-on experience building jobs that use MNS, CASS, WAVES, and AVI stages. Use the AVI stage to standardize multibyte-encoded address data.

Audience
This intermediate QualityStage training is for the following Information Server client groups:
 Data Analysts responsible for data quality using QualityStage
 Data Quality Architects
 Data Cleansing Developers
 Data Quality Developers needing to standardize and validate address data

Prerequisites
You should:
 have familiarity with Windows
 complete QualityStage Essentials course or have equivalent experience

Objective
 Standardize multinational address data including multibyte character data
 Validate standardized addresses

For Registration click here

IBM InfoSphere Advanced DataStage V8

Overview
This course works with Information Server V8.5.
This course is designed to introduce advanced job development techniques in DataStage V8.5.This course replaces course number view

Audience
This advanced course is for Experienced DataStage developers seeking training in more advanced DataStage techniques and who seek an understanding of the parallel framework architecture.

Prerequisites
You should complete:
 DataStage Essentials course or equivalent
 and have at least one year of experience developing parallel jobs using DataStage

Objective
 Describe the parallel processing architecture and development and runtime environments
 Describe the compile process and the runtime job execution process
 Describe how partitioning and collection works in the parallel framework
 Describe sorting and buffering in the parallel framework and optimization techniques
 Describe and work with parallel framework data types
 Create reusable job components
 Use loop processing in a Transformer stage
 Process groups in a Transformer stage
 Extend the functionality of DataStage by building custom stages and creating new Transformer functions
 Use Connector stages to read and write from relational tables and handle errors in Connector stages
 Process XML data in DataStage jobs using the XML stage
 Design a job that processes a star schema database with Type 1 and Type 2 slowly changing dimensions
 List job and stage best practices

For Registration click here

IBM InfoSphere Advanced DataStage - Parallel Framework V9.1

Overview
This course is designed to introduce advanced parallel job development techniques in DataStage V9.1. In this course you will develop a deeper understanding of the DataStage architecture, including a deeper understanding of the DataStage development and runtime environments. This will enable you to design parallel jobs that are robust, less subject to errors, reusable, and optimized for better performance.

Audience
This advanced course is for experienced DataStage developers seeking training in more advanced DataStage job techniques and who seek an understanding of the parallel framework architecture.

Prerequisites
You should have:
 Taken DataStage Essentials course or equivalent and
 At least one year of experience developing parallel jobs using DataStage

Objective
 Describe the parallel processing architecture
 Describe pipeline and partition parallelism
 Describe the role and elements of the DataStage configuration file
 Describe the compile process and how it is represented in the OSH
 Describe the runtime job execution process and how it is depicted in the Score
 Describe how data partitioning and collecting works in the parallel framework
 List and select partitioning and collecting algorithms
 Describe sorting in the parallel framework
 Describe optimization techniques for sorting
 Describe sort key and partitioner key logic in the parallel framework
 Describe buffering in the parallel framework
 Describe optimization techniques for buffering
 Describe and work with parallel framework data types and elements, including virtual data sets and schemas
 Describe the function and use of Runtime Column Propagation (RCP) in DataStage parallel jobs
 Create reusable job components using shared containers
 Describe the function and use of Balanced Optimization
 Optimize DataStage parallel jobs using Balanced Optimization

For Registration click here

InfoSphere QualityStage 8.7 Advanced

Overview
This course works with Information Server V8.5
Learn how to build QualityStage rule sets to standardize product data. Learn how to use reference matching to find related records. Gain hands-on experience by building jobs that standardize and match product data.

Audience
This course is for QualityStage training is for the following Information Server client groups:
 Data Analysts responsible for data quality using QualityStage
 Data Quality Architects
 Data Cleansing Developers
 Data Quality Developers needing to customize QualityStage rule sets

Prerequisites
You should be familiar with:
 Windows
 A text editor
 Completion of QualityStage Essentials course

Objective
 Modify rule sets
 Build a custom rule set
 Build QualityStage jobs to investigate data quality issues with newly standardized file
 Match related product and data warehouse records using QualityStage reference matching

For Registration click here

IBM InfoSphere Advanced QualityStage V9.1

Overview
Learn how to build QualityStage rule sets to standardize product data. Learn how to use reference matching to find related records. Gain hands-on experience by building jobs that standardize and match product data.

Audience
This advanced QualityStage training is applicable to the following Information Server client groups:
 Data Analysts responsible for data quality using QualityStage
 Data Quality Architects
 Data Cleansing Developers
 Data Quality Developers needing to customize QualityStage rule sets

Prerequisites
You should:
 Complete QualityStage Essentials course or have equivalent experience
 Have familiarity with:

 Windows
 A text editor

Objective
 Modify rule sets
 Build a custom rule set
 Build QualityStage jobs to investigate data quality issues with newly standardized file
 Match related product and data warehouse records using QualityStage reference matching

For Registration click here

IBM InfoSphere Advanced DataStage - Advanced Data Processing V9.1

Overview
This course is designed to introduce you to advanced parallel job data processing techniques in DataStage V9.1. In this course you will develop data techniques for processing different types of complex data resources including relational data, unstructured data (Excel spreadsheets), Hadoop HDFS (''big data'') files, and XML data. In addition, you will learn advanced techniques for processing data, including techniques for masking data and techniques for validating data using data rules. Finally, you will learn techniques for updating data in a star schema data warehouse using the DataStage SCD (Slowly Changing Dimensions) stage. Even if you are not working with all of these specific types of data, you will benefit from this course by learning advanced DataStage job design techniques, techniques that go beyond those utilized in the DataStage Essentials course.

Audience
This advanced course is for Experienced DataStage developers seeking training in more advanced DataStage job techniques and who seek techniques for working with complex types of data resources.

Prerequisites
You should:
 complete DataStage Essentials course or equivalent
 and have at least one year of experience developing parallel jobs using DataStage

Objective
 Use Connector stages to read from and write to database tables
 Handle SQL errors in Connector stages
 Use the Unstructured Data stage to extract data from Excel spreadsheets
 Use the Big Data stage to read from and write to Hadoop HDFS files
 Use the Data Masking stage to mask sensitive data processed within a DataStage job
 Use the XML stage to parse, compose, and transform XML data
 Use the Schema Library Manager to import and manage XML schemas
 Use the Data Rules stage to validate fields of data within a DataStage job
 Create custom data rules for validating data
 Design a job that processes a star schema data warehouse with Type 1 and Type 2 slowly changing dimensions
 Use the Surrogate Key Generator stage to generate surrogate keys

For Registration click here