IBM InfoSphere DataStage v11.5 – Advanced Data Processing

Description

At SIXE we have been providing official IBM training around the world for over 12 years. Get the best training from our specialists in Europe. We have important discounts and offers for two or more students.

Course details

Target audience

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

Desired Prerequisites:

DataStage Essentials course or equivalent.

Instructors

The great majority of the IBM courses we offer are taught directly by our engineers. This is the only way we can guarantee the highest quality. We complement all the training with our own materials and laboratories, based on our experience during the deployments, migrations and courses that we have carried out during all these years.

Added value

Our courses are deeply role oriented. To give an example, the needs for technology mastery are different for developer teams and for the people in charge of deploying and managing the underlying infrastructure. The level of previous experience is also important and we take it very seriously. That is why beyond (boring) commands and tasks, we focus on solving the problems that arise in the day to day of each team. Providing them with the knowledge, competencies and skills required for each project. In addition, our documentation is based on the latest version of each product.

Agenda and course syllabus

Unit 1 –Accessing databases

Topic 1:  Connector stage overview

• Use Connector stages to read from and write to relational tables

• Working with the Connector stage properties

Topic 2:  Connector stage functionality

• Before / After SQL

• Sparse lookups

• Optimize insert/update performance

Topic 3:  Error handling in Connector stages

• Reject links

• Reject conditions

Topic 4:  Multiple input links

• Designing jobs using Connector stages with multiple input links

• Ordering records across multiple input links

Topic 5:  File Connector stage

• Read and write data to Hadoop file systems

Demonstration 1: Handling database errors

Demonstration 2:  Parallel jobs with multiple Connector input links

Demonstration 3:  Using the File Connector stage to read and write HDFS files

Unit 2 – Processing unstructured data

Topic 1:  Using the Unstructured Data stage in DataStage jobs

• Extract data from an Excel spreadsheet

• Specify a data range for data extraction in an Unstructured Data stage

• Specify document properties for data extraction.

Demonstration 1:  Processing unstructured data

Unit 3 – Data masking

Topic 1:  Using the Data Masking stage in DataStage jobs

• Data masking techniques

• Data masking policies

• Applying policies for masquerading context-aware data types

• Applying policies for masquerading generic data types

• Repeatable replacement

• Using reference tables

• Creating custom reference tables

Demonstration 1: Data masking

Unit 4 – Using data rules

Topic 1:  Introduction to data rules

• Using the Data Rules Editor

• Selecting data rules

• Binding data rule variables

• Output link constraints

• Adding statistics and attributes to the output information

Topic 2:  Use the Data Rules stage to valid foreign key references in source data

Topic 3:  Create custom data rules

Demonstration 1:  Using data rules

Unit 5 – Processing XML data

Topic 1:  Introduction to the Hierarchical stage

• Hierarchical stage Assembly editor

• Use the Schema Library Manager to import and manage XML schemas

Topic 2:  Composing XML data

• Using the HJoin step to create parent-child relationships between input lists

• Using the Composer step

Topic 3:  Writing Hierarchical data to a relational table

Topic 4:  Using the Regroup step

Topic 5:  Consuming XML data

• Using the XML Parser step

• Propagating columns

Topic 6:  Transforming XML data

• Using the Aggregate step

• Using the Sort step

• Using the Switch step

• Using the H-Pivot step

Demonstration 1:  Importing XML schemas

Demonstration 2: Compose hierarchical data

Demonstration 3: Consume hierarchical data

Demonstration 4:  Transform hierarchical data

Unit 6:  Updating a star schema database

Topic 1:  Surrogate keys

• Design a job that creates and updates a surrogate key source key file from a dimension table

Topic 2:  Slowly Changing Dimensions (SCD) stage

• Star schema databases

• SCD stage Fast Path pages

• Specifying purpose codes

• Dimension update specification

• Design a job that processes a star schema database with Type 1 and Type 2 slowly changing dimensions

Demonstration 1: Build a parallel job that updates a star schema database with two dimensions

Do you need to adapt this syllabus to your needs? Are you interested in other courses?  Ask us without obligation.

Locations for on-site delivery

• Austria: Vienna
• Belgium: Brussels, Ghent
• Denmark: Cophenhagen
• Estonia: Tallinn
• Finland: Helsinki
• France: Paris, Marseille, Lyon
• Germany: Berlin, Munich, Cologne, Hamburg
• Greece: Athens, Thessaloniki
• Italy: Rome
• Louxemburg: Louxembourg (city)
• Netherlands: Amsterdam
• Norway: Oslo
• Portugal: Lisbon, Braga, Porto, Coimbra
• Slovakia: Bratislava
• Slovenia: Bratislava
• Spain: Madrid, Sevilla, Valencia, Barcelona, Bilbao, Málaga
• Sweden: Stockholm
• Turkey: Ankara
• United Kingdom: London