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PR000005 Exam Format | PR000005 Course Contents | PR000005 Course Outline | PR000005 Exam Syllabus | PR000005 Exam Objectives

PR000005 Exam Information and Guideline

Data Quality 9.x Developer Specialist



Below are complete topics detail with latest syllabus and course outline, that will help you good knowledge about exam objectives and topics that you have to prepare. These contents are covered in questions and answers pool of exam.





You may select from one or more response offerings to answer a question.

You will score the question correctly if your response accurately completes the statement or answers the question. Incorrect
distractors are given as possible correct answers so that those without the required skills and experience may wrongly select that choice.

A passing grade of 70% is needed to achieve recognition as an Informatica Certified Specialist (ICS) Data Quality Developer v9.x.

You are given 90 minutes to complete the exam. Test formats used in this exam are:

• Multiple Choice: Select one option that best answers the question or completes the statement

• Multiple Response: Select all that apply to best answer the question or complete the statement

• True/False: After reading the statement or questions select the best answer



Data Quality Developer 9.x, Specialist Certification

About the ICS Data Quality Developer Exam and the Skill Set Inventory

This exam measures your competency as a member of a project implementation team. This involves having an in-depth knowledge of
each of the Data Quality processes from Profiling to Standardization, Matching and Consolidation. You need to be able to select and configure the appropriate Data Quality transformation for your requirements and build, debug and execute Data Quality mappings as well as integrate mappings into Power Center.

The skill set inventory is used to guide your preparation before taking the exam. It is an outline of the technical topics and subject areas that are covered in each exam. The skill set inventory includes test domain weighting, test objectives and topical content. The topics and concepts are included to clarify the test objectives.

Test takers will be tested on:

• Their ability to navigate through the Developer Tool

• Use of Project Collaboration techniques; shared Tags, Comments, Profiles, reference tables to share information with Analysts

• Using a variety of profiling methods to profile data

• The use of Analyst built profiles to develop mappings

• Build mappings and mapplets to cleanse and standardize data

• Perform Address Validation

• Identifying duplicate records in a dataset

• Automatically and manually consolidating duplicate records to create a master record

• Execution of mappings/mapplets in PowerCenter

• Deployment of Data Quality Mappings in an Excel spreadsheet (connect to Web Services)



Title % of Test

Informatica Overview 10%

Analyst Collaboration 10%

Profiling 15%

Standardization/Mapplets 10%

Address Validation 5%

Matching 10%

Consolidation and the DQA 10%

Integration with PowerCenter 5%

Object Import and Export 5%

DQ for Excel 5%

Parameters 5%

Content 10%



Test Topics

The exam will contain 70 questions comprised of topics that span across the sections listed below. In order to ensure that you are prepared for the test, review the subtopics with each section.

Informatica Overview

• Describe the Informatica 9 architecture and set up
including the repositories required for installation

• Provide information on the Data Quality process and
dimensions of data quality

Analyst Collaboration

• Use and describe the functionality of the Analyst Tool including Scorecarding, Reference Table Management, Tags, Filters, Profiles and Comments

• Describe how Analysts and Developers can
collaborate on projects

• Describe the benefits of project collaboration to a
team

Profiling

• Perform and interpret column, rule, comparative and
mid-stream profiling

Standardization/Mapplets

• Be aware of where data standardization fits in the
DQ process

• Apply, configure and troubleshoot data
standardization transformations

• Differentiate between the various parsing techniques
available

• Recognize how reference tables are used in the
standardization process

Address Validation

• Verify the importance of Address Validation

• Configure the Address Validation transformation
including explaining each mode that is available and
what custom templates can be used for

• Interpret the AV outputs generated
Matching

• Develop and build match plans to identify duplicate
or related data

• Differentiate between the matching algorithms
available and explain how matching scores are

• Configure Identity Matching option for the match
transformation

• Explain populations, the identity match strategies that
are available and how they are used in Identity
Matching

Consolidation and the DQA

• Explain Automatic and Manual consolidation
techniques and configure the Transformations used
for automatic consolidation

• Use the Exception Transformation to generate and
populate the Bad Records and Duplicate Records
tables

• Troubleshoot any problems that may occur

• Generate a survivor record in the DQA

• Remove duplicates using DQA
Integration with Power Center

• Explain how to integrate IDQ mappings and
mapplets into PowerCenter Workflows including how
content is handled

Object Import and Export

• Define the difference between the Basic and
Advanced Import options available

• Explain Dependency conflict resolution and how it is
handled

• Describe how to Export a Project
DQ for Excel

• Describe the requirements for integration for Excel

• Define the techniques for creating mappings for DQ
for Excel

• Explain the Web service capabilities required for DQ
for Excel

• Provide an explanation on how to use the Informatica
ribbon in Excel

Parameters

• Explain what parameters are and why they are used
including what parameter functions are supported

• Identify which Transformations can use parameters

• Describe the process of exporting mappings with
parameters built in Content

• Explain what Content is, what is contained in the
Core Accelerator and why it is used.

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