Datastage Training in California, USA
Azon Technologies offers best Datastage Training in California, USA with most experienced professionals. Our Instructors are working in Datastage and related technologies for more years in MNC’s. We aware of industry needs and we are offering Datastage Training in California, USA in more practical way. Our team of Datastage trainers offers Datastage in Classroom training, Datastage Online Training and Datastage Corporate Training services. We framed our syllabus to match with the real world requirements for both beginner level to advanced level. Our training will be handled in either weekday or weekends programme depends on participants requirement.
We do offer Fast-Track DataStage Training in California, USA and One-to-One Datastage Training in California, USA. Here are the major topics we cover under this Datastage course Syllabus Datastage Introduction, Types of Datastage Job, Setting up Datastage Environment, Creating Parallel Jobs, Accessing Sequential Data , Platform Architecture, Combining Data, Sorting and Aggregating Data, Transforming Data, Repository Functions, Working with Relational Data, Metadata in Parallel Framework:, Job Control.Every topic will be covered in mostly practical way with examples.
Azon Technologies located in various places in California, USA. We are the best Training Institute offers certification oriented Datastage Training in California, USA. Our participants will be eligible to clear all type of interviews at end of our sessions. We are building a team of Datastage trainers and participants for their future help and assistance in subject. Our training will be focused on assisting in placements as well. We have separate HR team professionals who will take care of all your interview needs. Our Datastage Training Course Fees is very moderate compared to others. We are the only Datastage training institute who can share video reviews of all our students. We mentioned the course timings and start date as well in below.
Datastage Training Syllabus in California, USA
- Datastage Architecture
- Datastage Clients
- Datastage Workflow
Types of Datastage Job
- Parallel Jobs
- Server Jobs
- Job Sequences
Setting up Datastage Environment
- Datastage Administrator Properties
- Defining Environment Variables
- Importing Table Definitions
Creating Parallel Jobs
- Design a simple Parallel job in Designer
- Compile your job
- Run your job in Director
- View the job log
- Command Line Interface (dsjob)
Accessing Sequential Data
- Sequential File stage
- Data Set stage
- Complex Flat File stage
- Create jobs that read from and write to sequential files
- Read from multiple files using file patterns
- Use multiple readers
- Null handling in Sequential File Stage
- Describe parallel processing architecture Describe pipeline & partition parallelism
- List and describe partitioning and collecting algorithms
- Describe configuration files
- Explain OSH & Score
- Combine data using the Lookup stage
- Combine data using merge stage
- Combine data using the Join stage
- Combine data using the Funnel stage
Sorting and Aggregating Data
- Sort data using in-stage sorts and Sort stage
- Combine data using Aggregator stage
- Remove Duplicates stage
- Understand ways Datastage allows you to transform data
- Create column derivations using userdefined code and system functions
- Filter records based on business criteria
- Control data flow based on data conditions
- Perform a simple Find
- Perform an Advanced Find Perform an impact analysis
- Compare the differences between two Table Definitions and Jobs
Working with Relational Data
- Import Table Definitions for relational tables.
- Create Data Connections.
- Use Connector stages in a job.
- Use SQL Builder to define SQL Select statements.
- Use SQL Builder to define SQL Insert and Update statements.
- Use the DB2 Enterprise stage.
- Use the Datastage Job Sequencer to build a job that controls a sequence of jobs.
- Use Sequencer links and stages to control the sequence a set of jobs run in.
- Use Sequencer triggers and stages to control the conditions under which jobs run.
- Pass information in job parameters from the master controlling job to the controlled jobs.
- Define user variables.
- Enable restart.
- Handle errors and exceptions.