Informatica Idq Data Quality

Informatica idq data quality online training

Course Syllabus

Introduction to Informatica Developer

  1. Overview of Informatica Architecture
  2. GUI

3.Developer Basics

4.Creating Flat Files

5.Importing Flat Files

6.Creating Relational Connections

7.Importing Relational Data Objects

8. Mappings, Mapplets/Rules, Transformations, Content Sets

Developer Profiling

  1. Join Analysis Profiling
  2. Column Profiling
  3. Multi Object Profiling
  4. Mappings and Transformations
  5. Mid-Stream Profiling
  6. Comparative Profiling

Informatica Analyst Collaboration

  1. Reviewing information from the Analyst
  2. Comments/Tags
  3. Creating/Modifying Reference tables

Working with PowerCenter Transformations

  1. Expression, Filter, Router Lookup, Joiner, Sorter, Aggregator, Union, Sequence Generator etc.

Data Standardization

1. Cleanse and Transform data using Case Converter, Labeler and Standardization Transformations

2. Label data using Tokens

3. Data Standardization using Tokens

4. Data Standardization using Reference Table

5. Develop Data Standardization Mapplets and Mappings

Data Parsing

  1. Perform Parsing using different methods:
  2. Token based Parsing
  3. Pattern based Parsing

Address Validation

1. Perform Address Validation using in built address doctor information

Matching

a. Grouping Data

b. Analyze Detail Report

c. DQ Matching

d. Cluster Analysis Report

e. Matching Mapplets

Identity Matching

a. Build Matching mappings using Identity matching

b. Identity Populations and Strategies

Data Consolidation

a. Associate and Consolidate data using Association and Consolidation Transformations

b. Choose Consolidation Strategy for your data

Exception Management

a. Perform Bad Record Management using Decision and Exception Transformations

PowerCenter Integration

  1. Run IDQ Mappings in PowerCenter

Object Import/Export

  1. Import/Export Objects using both Basic and Advanced methods
  2. Export Mapplets into PowerCenter

Parameters

  1. How to use Parameters in Data Quality mappings, transformations and reference tables

Workflows

a. How to create different objects in DQ workflows modules. Examples: mapping task, Notification Task, Human Task etc.

Introduction to Data Virtualization

1. Import Physical Data Objects

2. Create Logical Data Object Model

3. Create Logical Data Objects (Inside the Model)

4. Create an SQL Data Service

5. Deploy an SQL Data Service to a Data Integration Service as an application

6. Use the Application info. to create ODBC Connections

7. Connect via 3rd party Tools/Reporting Tools

8. Use the Virtual Tables like any other Tables...!!!