DATAWAREHOUSING CONCEPTS
Curriculum
Module1:
- Introduction about Data Stage
- History of Data Stage
- What’s new in Data Stage 8.0.1?
- What is way ahead in Data Stage?
- Difference between Data Stage 7.5.2 and 8.0.1
Module2:
- IBM Information Sever architecture
- Data Stage in IBM Information server architecture
- Difference between SMP/MPP(Cluster) Architecture
Module3:
- Data stage components (Server components /Client components)
- Different types of jobs in Data Stage
- Difference between Server Jobs and Parallel Jobs
Module4:
- Connecting to Designer
- Repository
- Palette
- Type of Links
Module5:
- File Stages
- Sequential file
- Dataset file
- File set
- Lookup file set
- Difference between Sequential file/Dataset/File set
- Create job that reads and writes from a sequential file.
- Create a job to read data from multiple files by using file pattern
- Saving and load table definitions
- Different types of table definitions
- Difference between Orchestrate, Sequential and Plug in table definition.
Module6:
- Overview of iway, Classic federation and netezza
- Database stages
- Dynamic RDBMS
- Oracle Enterprise
- ODBC Enterprise
- ODBC connector
- Stored Procedure
Module7:
- Difference between Pipeline Parallelism and Partition Parallelism
- Partition techniques (Round Robin, Random,
- Hash, Entire, Same, Modules, Range, DB2, Auto)
- Difference between partitioning and re partitioning
- Different types of combining and collecting techniques.
- Configuration file and its components
- Explain OSH and score
Module8:
- Combining data using Join Stage
- Combining data using Merge Stage
- Combining data using Lookup Stage
- Combining data using Funnel Stage
- Difference between Join/Lookup/Merge
- Difference between Join/Lookup
Module9:
- Sorting data using different types of sort techniques and sort stage.
- Combine data using Aggregate Stage
- Removing duplicates using remove duplicates stage
Module10:
- Transforming data using transformer
- Using functions, macros and routines in transformer.
- Difference between basic transformer and transformer
- Performance tunings while using transformer
- Filtering data using filter stage
- Different types of filters in Data Stage
- Difference between filter, External filter and switch stages.
- Renaming and changing data types using modify stage
Module11:
- Determining delta records using Change Capture stage
- Applying changes from change capture using change apply stage
- Applying SCD1 and SCD2 using SCD stage
- Using surrogate generator stage
Module12:
- Use of a generic stage in Data Stage
- Use of a pivot stage
- Encode and decode stages
- Compare Stage
- Difference Stage
- FTP stage
- Copy stage
Module13:
- Adding job parameters to a job
- What is Parameter set?
- Explain Run time column propagation
- Explain and create Schema files
Module14:
- Head
- Tail
- Peek
- Row Generator
- Column Generator
- Sample
- Creation of Range map
Module15:
- Local Container
- Shared Container
- Difference between Local Container and Shared Container
Module16:
- Arrange job activities in sequencer
- Triggers in Sequencer
- Notification activity
- Terminator Activity
- Wait for file activity
- Start loop activity
- Execute command activity
- Nested Condition activity
- Routine activity
- Exception handing activity
- User variable activity
- End loop activity
- Adding Checkpoints
Module17:
- How to connect to Data stage Director?
- Job Status View
- View logs
- Scheduling
- Batches Creation
- Cleaning resources using director
- Message handling
Module18:
- Importing the Job
- Exporting the Job
- Different types of exportable.
- Importing Table Definition
- Different types of table definitions and their differences.
- Importing Flat File Definition
Module19:
- Explain and create Routines
- Dataset management and ORCHADMIN
- Quick search and advanced search
Module20:
- Creating project, Editing project and Deleting project
- Permissions to user
- Different kinds of variables in Data Stage
- Cleaning resources using Administrator
Module21:
- What is Date Quality and why do we for data quality?
- Integration of Data Quality in Data Stage?
- Data stage Quality stages
- Investigate stage
- Standardize stage Match Frequency stage
- Unduplicate Match stage
- Reference Match stage
- Survive stage
- Standardized rule sets.
- Components of Standardized rule sets.
- Match designer
- WAVES
Note : The Duration of Course is 30 Sessions of one hour each