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Cloud Data Quality:
Cleansing and Enhancing Data

Instructor Led | IDMC Data Quality | 2 Days | November 2024 Release

Course Overview

Enhance your understanding of Informatica Cloud Data Quality through in-depth analysis of its cleansing and enhancement features. Learn how to configure Data Quality Assets and effectively implement them in mappings or mapplets within Cloud Data Integration. This course equips you with the necessary skills to design and construct a Data Quality Cloud process, tailored for use in Data Migration, Data Integration, or Data Quality Projects.
Access the latest tools and methodologies with this latest November 2024 Release.

Objectives

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

  • Describe what Cloud Data Quality is and how it can be used to optimize your data
  • Use Cloud Administrator to define connections
  • Create Mappings using Cloud Mapping Designer
  • Collaborate with team members
  • Identify and label data using a Labeler asset
  • Configure the Cleanse asset to standardize, cleanse, and enhance data
  • Configure the Parse asset to extract or separate data
  • Use Deduplicate functionality to identify and consolidate duplicate records
  • Verify and enhance addresses using the Verify asset
  • Review available Content Bundles

Target Audience

  • Developer
  • Business User

Prerequisites

Agenda
Module 0: Course Introduction
  • Course Introduction
Module 1: Informatica Intelligent Data Management Cloud
  • Introduction to Informatica Intelligent Data Management Cloud (IDMC)
  • Informatica Intelligent Data Management Cloud Terminology
  • Informatica Intelligent Data Management Cloud Architecture
  • Informatica Intelligent Data Management Cloud Services
  • Runtime Environments
  • Connections
  • The Administrator Service
  • Lab: Defining Connections
  • Lab: Creating a Training Folder
Module 2: Cloud Data Quality Overview
  • What is Data Quality?
  • Discussing the Data Quality Management Process Cycle
  • Listing and Explaining the Dimensions of Data Quality
  • Cloud Data Quality Services and Assets
Module 3: Team Collaboration
  • Profiling Data
  • What are Dictionaries and why are they used?
  • Using Rule Specifications to Cleanse and Enhance Data
  • Lab: Reviewing Team Assets
Module 4: Cloud Mapping Designer
  • Cloud Mapping Designer Overview
  • Mapping Designer Terminologies
  • Mappings and Mapplets
  • Common Transformations
  • Lab: Configuring a Mapping to Load Data into a SQL Table
Module 5: 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: Creating a Labeler to Mask Non-Numeric Data
Module 6: The Cleanse Asset
  • Introduction to the Cleanse Asset
  • Cleansing, Standardizing, and Enhancing Data
  • Building a Mapping to Cleanse and Transform Data
  • Lab: Configuring a Mapplet to Remove Noise from a Numeric Field
  • Lab: Configuring a Multi Instance Cleanse Asset to Cleanse and Standardize the Address Fields
  • Lab: Configuring a Mapplet to Derive a Master Contact Name
  • Lab: Configuring a Mapping to Cleanse, Standardize, and Enrich Data
Module 7: The Parse Asset
  • Introduction to the Parse Asset
  • Parsing Data
  • Lab: Configuring a Parse Asset using Pre-built Mode
  • Lab: Configuring a Parse Asset using a Regular Expression
  • Lab: Updating the Load Mapping to include both datasets
  • Lab: Standardizing the Data
Module 8: The Deduplicate Asset
  • Introduction to the Deduplicate Asset
  • Matching Theory
  • Identifying Matching or Related Records
  • Configuring the Deduplicate Asset to Consolidate Matched Data
  • Lab: Configuring a Deduplicate Asset to Identify Duplicate or Related Records
  • Lab: Creating a Mapping to Identify Duplicate Records
  • Lab: Updating the Deduplicate Asset to Consolidate Matched Records
Module 9: The Verifier Asset
  • Introduction to the Verifier Asset
  • Verifying Address Data
  • Lab: Configuring a Verifier Asset to Verify and Correct US Master Records
  • Lab: Creating a Mapping to Verify Master Records
Module 10: Data Quality Bundles
  • Introduction to Data Quality Bundles
  • Lab: Working with Data Quality Bundles
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