Data Quality 9.x: Developer, Level 1 (Blended Learning)

Blended Learning | Data Quality | 2 Days (55% lecture, 45% hands on labs, 10 hours onDemand)

Data Quality 9.x: Developer, Level 1 (Blended Learning)

Course Overview

This course has been developed following a blended learning approach that allows the student to take advantage of the flexibility and convenience of an online course while retaining the benefits of the instructor led classroom experience. Learners benefit from multiple learning channels and media formats – so this approach is more likely to appeal to all learning styles.

We are following a 3 step approach:

We have developed eLearning Modules to introduce the student to the concepts of Data Quality and provide them with a strong foundation. Students can learn at a time and pace that suits them.
Following this, our 2 day instructor led course covers the Core elements of Data Quality. Students are more prepared and have a foundation that enables them to benefit more from the Instructor Led Modules. They will perform tasks such as profiling and identifying anomalies, developing mappings and mapplets for use in processes such as data standardization and identifying duplicate records.
There are elements to the software that not every student will want to cover at the same time. It makes more sense to allow students go through these modules and labs at a time when the information is relevant to them. Because of this we have developed a series of onDemand Modules that allow the user learn at their own pace and work on labs in a preconfigured environment.

Data Quality 9x: Developer, Level 1 - Blended Learning

Objectives

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

Navigate the Developer Tool and collaborate on projects with Analysts.
Perform Column, Rule, Multi object, Comparative and Mid-Stream Profiling.
Manage reference tables.
Create standardization, cleansing and parsing Mappings and Mapplets.
Identify duplicate records using Classic Data Matching.
Build mappings to associate and consolidate matched records.
Create and execute Workflows to populate user inboxes with Exception and Duplicate record tasks.
Run data quality mappings in DQ Standalone.

Target Audience

New users of Informatica Developer, including Business and Data Developers
Users who wish to re-familiarize themselves with the Developer tool

Prerequisites

Windows GUI and theoretical understanding of process development and design

Agenda
Prerequisite eLearning Modules: What to Expect Where to begin and how to proceed. Informatica Developer Tool: Introduction for New Users Work with Informatica Developer GUI, Mappings, Mapplets, Transformations, Content Sets, Data Objects Informatica Data Quality Developer Course Introduction An Introduction to the Data Quality Course and Data Quality Concepts and Processes Project Collaboration and Reference Table Management Review projects created by the Analyst Review objects, Profiles, Rules, Scorecards Comments and Tags Create/add Reference tables ILT Core Modules Developer Profiling and Logical Data Objects Create a Logical Data Object Perform: Column Profiling Multi Object Profiling Mid-stream profiling Comparative profiling Create Mappings and work with DQ and Core transformations Data Standardization Cleanse and transform data using Standardization Transformations Develop standardization mappings and mapplets Parsing Perform parsing using methods such as: Token Parser Pattern Parser NER/Probabilistic parsing	Matching Become familiar with the concepts involved in Matching Grouping data Match Performance Analysis DQ Matching Match Cluster Analysis Running DQ in a Standalone environment Schedule DQ mappings to run in DQ Standalone using Windows Task Manager. onDemand Modules Parsing Perform parsing using methods such as: Token Parser Pattern Parser NER/Probabilistic parsing Automatic Consolidation Use the Consolidation Transformation to automatically Consolidate matched records. Be able to choose the most affective consolidation strategy for your data; simple, row based or advanced. Manual Exception and Consolidation Management Build and execute Mappings, using the Exception Transformation, to identify exception and duplicate records. Task and Workflow Management Build and execute workflows to populate Informatica user inboxes with exception and duplicate records. Update exception and duplicate records in Informatica Data Director. Object Import/Export Import Projects using both Basic and Advanced methods. Export Projects


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