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

You will score the question correctly if ytheir response accurately completes the statement or anstheyrs the question. Incorrect
distractors are given as possible correct anstheyrs 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 anstheyrs the question or completes the statement

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

• True/False: After practicing the statement or questions select the best anstheyr



Data Quality Developer 9.x, Specialist Certification

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

This exam measures ytheir 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 ytheir requirements and build, debug and execute Data Quality mappings as theyll as integrate mappings into Potheyr Center.

The skill set inventory is used to guide ytheir preparation before taking the exam. It is an outline of the technical syllabus and subject areas that are covered in each exam. The skill set inventory includes test domain theyighting, test objectives and topical content. The syllabus 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 PotheyrCenter

• Deployment of Data Quality Mappings in an Excel spreadsheet (connect to Theyb 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 PotheyrCenter 5%

Object Import and Export 5%

DQ for Excel 5%

Parameters 5%

Content 10%



Test Topics

The exam will contain 70 questions comprised of syllabus 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 bettheyen 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 bettheyen 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 Potheyr Center

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

Object Import and Export

• Define the difference bettheyen 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 Theyb 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.