Informatica Cloud Data Quality Content

Objectives

After successfully completing this course, students should be able to:

  • Describe Informatica Intelligent Data Management Cloud Architecture
  • Describe what Cloud Data Quality is and how it can be used
  • Use Cloud Administrator to define connections
  • Create Mappings using Cloud Mapping Designer
  • Profile data to identify anomalies
  • Create Dictionaries to hold reference data for verification and standardization routines
  • Use Rule Specifications to build rules
  • Identify and label data in fields using a Labeler asset
  • Configure the Cleanse asset to standardize and cleanse data
  • Configure the Parse asset to parse data
  • Use the Deduplicate functionality to identify and consolidate duplicate records
  • Verify and enhance Addresses using the Verify asset
  • Identify Exception Records and download them for manual correction

Module 1: Informatica Intelligent Data Management Cloud Overview

  • Introduction to Informatica Intelligent Data Management Cloud (IDMC)
  • Informatica Intelligent Data Management Cloud Terminolgy
  • Informatica Intelligent Data Management Cloud Architecture
  • Informatica Intelligent Data Management Cloud Services
  • IICS train Account Create and Activation
  • Install and Configure Secure Agent
  • Services enablement on Secure Agent
  • Runtime Environments
  • Connections
  • The Administrator Service
  • Lab: Defining Connections
Module 2: Cloud Data Quality Overview
  • What is Data Quality?
  • Discuss the Data Quality Management Process Cycle
  • List and explain the Dimensions of Data Quality
  • Describe Data Quality functions, inputs, and outputs
  • Cloud Data Quality Services and Assets

Module 3: Cloud Mapping Designer

  • Cloud Mapping Designer Overview
  • Mapping Designer Terminologies
  • Mappings and Mapplets
  • Common Transformations
  • Lab: Create your training folder
  • Lab: Create and run a mapping to load data into a SQL table

Module 4: Cloud Data Profiling

  • Profile Data
  • Review Profiling Results and identify anomalies
  • Profile Features
  • Lab: Profiling Data
  • Lab: Profiling Insights

Module 5: Dictionaries

  • What are Dictionaries and why are they used?
  • Creating Dictionaries
  • Lab: Create a Dictionary to standardize data
  • Lab: Copy and update an existing Dictionary to validate data
  • Lab: Create a Dictionary to enhance data

Module 6: Rule Specifications

  • Introduction to Rule Specifications
  • Building Rule Specifications
  • Lab: Create a Rule Specification to validate the Company field
  • Lab: Create a Rule Specification with multiple rules

Module 7: Scorecards

  • Scorecard Overview
  • Update a Profile and define Rule Occurrences
  • Review Scorecards
  • Lab: Apply Rules to a Profile and Review
  • Lab: Create a Scorecard

Module 8: The Labeler Asset

  • Standardization Overview
  • Introduction to the Labeler Asset
  • Configuring a Labeler Asset in Token Labeler mode
  • Configuring a Labeler Asset in Character Labeler mode
  • Lab: Create a Labeler to mask nonnumeric data

Module 9: The Cleanse Asset

  • Introduction to the Cleanse Asset
  • Cleanse, standardize and enhance data
  • Build a mapping to cleanse and transform data
  • Lab: Create a mapplet to cleanse and standardize the Company name
  • Lab: Configure a mapplet to derive a Master Contact name
  • Lab: Configure a mapplet to remove noise from a numeric field
  • Lab: Configure a mapping to cleanse, standardize and enrich data

Module 10: The Parse Asset

  • Introduction to the Parse Asset
  • Parsing data
  • Lab: Configure a Parse Asset using Prebuilt Mode
  • Lab: Configure a Parse Asset using a Regular Expression
  • Lab: Update the Load Mapping to include both datasets
  • Lab: Reprofile and standardize the data

Module 11: The Deduplicate Asset

  • Introduction to the Deduplicate Asset
  • Matching Theory
  • Identify matching or related records
  • Configure the Deduplicate Asset to consolidate matched data
  • Lab: Configure the Deduplicate Asset to identify duplicate or related records
  • Lab: Create a mapping to identify duplicate records
  • Lab: Update the deduplicate asset to consolidate matched records

Module 12: The Verifier Asset

  • Introduction to the Verifier Asset
  • Verify Address Data
  • Lab: Configure a Verifier Asset to verify and correct US master records
  • Lab: Create a mapping to verify data US master records

Module 13: Exception Management

  • The Exception Management Process
  • Configure an Exception Task
  • Lab: Identify Exception Records
  • Lab: Export Project Assets and Delete the Contents and Folder

 

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