The Job of the Information/Data Quality Professional · The Job of the Information/Data Quality Professional January 2011/May 2017 Page 4 of 74 Job Analysis Panel Members • Walid

The Job of the Information/Data Quality Professional Job Analysis Report January 2011—updated May 2017

The Job of the Information/Data Quality Professional: Job Analysis Report January 2011 Updated 2017 Edited By C. Lwanga Yonke, Christian Walenta, John R. Talburt Published by IQ International Adapted from the Job Analysis Study report developed by Scott T. Bublitz of Castle Worldwide, Inc., for the Information Quality Certified Professional (IQCPSM) Credential © 2011-2017 IQ International.

This work is licensed under a Creative Commons Attribution-

NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) License. See creativecommons.org/licenses/by-nc-nd/4.0/ for the terms and conditions of this license.

https://creativecommons.org/licenses/by-nc-nd/4.0/

The Job of the Information/Data Quality Professional January 2011/May 2017

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Table of Contents

Executive Summary 6 Introduction 8

Overview and Objectives 8 Definitions 8

Background and Summary of Development Process 9 Profile of the Information Quality Certified Professional (IQCPSM) 10 Phase I - Initial Development and Evaluation 11

Domain Development 11 Tasks, Knowledge and Skills 11 Panel Evaluation of Domains and Tasks 11

Phases II and III - Validation Study and Development of Test Specifications 12 Survey Design and Distribution 12 Statistical Analysis of Domains and Tasks Ratings 12

IQCP Domains and Tasks 14 Business Need for Certification (Based on Survey Responses) 21

Organizational Need 21 Professional Need 23

Conclusion 29 Appendix A: IQCP(SM) Exam Blueprint 30

DOMAIN 1 - Information Quality Strategy & Governance 31 DOMAIN 2 - Information Quality Environment & Culture 37 DOMAIN 3 - Information Quality Value and Business Impact 42 DOMAIN 4 - Information Architecture Quality 46 DOMAIN 5 - Information Quality Measurement and Improvement 50 DOMAIN 6 - Sustaining Information Quality 56

Appendix B: Who Responded to the Survey? Respondents’ Demographics 60 Personal Profile 60 Professional Profile 66 Organizational Profile 70 How large is your organization? 71


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Job Analysis Panel Members

• Walid el Abed, Global Data Excellence, Switzerland • Elizabeth Davis, International Finance Corporation (World Bank) USA • Brenda Maas, Target, USA • Danette McGilvray, Granite Falls Consulting, USA • Jeff Monica, Sun Microsystems, USA • Elizabeth Pierce, University of Arkansas at Little Rock, USA • Jeff Pettit, One Truth Enterprise LLC, USA • John Talburt, University of Arkansas at Little Rock, USA • Keith Underdown, UK • Christian Walenta, IBM, USA • C. Lwanga Yonke, IQ International

Facilitator: Scott T. Bublitz, Ph.D, CASTLE Worldwide, Inc., Morrisville, NC


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About IQ International

Chartered in January 2004 as the International Association for Information and Data Quality, IQ International is a not-for profit, vendor-neutral professional society of people passionate about improving information and data quality. IQ International is advancing the quality of information and data around the world by building a community that supports learning and sharing knowledge for the benefit of all information consumers. IQ International offers a wide range of IDQ products and services to meet the needs of information/data quality professionals at all experience levels. To learn more about IQ International, please visit the website: iqint.org.

Acknowledgements

The editors are grateful for the many people who contributed to the work summarized in this report, starting with the members of the Job Analysis Panel who conducted the initial role delineation work. We greatly appreciate and thank the many individuals who completed the survey. We also specifically express our sincere gratitude to the many people who provided valuable guidance and insight during the various phases of this project, including Daragh O Brien and Grant Robinson. We thank Gwen Thomas, Dylan Jones and Guy Tozer, for their contributions to the knowledge and skills sections of several tasks.

http://www.iaidq.org/


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Executive Summary For the first time, a broad group of information/data quality practitioners across the globe has reached consensus on the definition of the job of information/data quality professional. This achievement represents a major milestone in the establishment of information/data quality as a distinct profession.

This breakthrough is the outcome of a job analysis study jointly conducted between October 2008 and March 2009 by IQ International, the International Association for Information and Data Quality (IQint), guided by CASTLE Worldwide, Inc. (CASTLE). The purpose of the study was to build the association's Information Quality Certified Professional (IQCPSM) credential on a solid foundation validated by practitioners and consistent with best practices and accepted standards. The process followed by IQ International and CASTLE complies with widely accepted standards and regulations as the ISO/IEC 17024 for Personnel Certification Bodies, Standards for Educational and Psychological Testing, American Educational Research Association (1999); and the Uniform Guidelines on Employee Selection Procedures (1977 and updated); and Standards for the Accreditation of Certification Programs, published by the National Commission for Certifying Agencies (NCCA, 2002, USA).This distinguishes the IQCPSM credential from other information / data quality certifications or certificates currently offered in the marketplace.

The consensus definition of the job of IQCP consists of a framework containing six (6) performance domains, twenty-nine (29) tasks, and several hundred distinct knowledge and skills. After it was validated by a large international group of information/data quality practitioners, the framework was used to develop the specifications for the upcoming IQCP exam. Beyond this primary purpose, the IQCP Framework is also expected to:

• Drive an increase in the quality and consistency of the information/data quality training available in the market place,

• Provide a benchmark against which organizations can assess their information/data quality practices.

Findings of a survey conducted as part of the job analysis study include the following:

• Compliance/Risk is the primary focus of information quality efforts (39.7%) followed by Cost Reduction (29%), Revenue Growth (15%).

• Achieving data quality remains a challenge as only 10% of respondents rated their organization’s information quality efforts as very successful. Fortunately, 46% rated theirs as successful.

• A broad consensus exists that establishing information / data quality as a distinct profession is very important (49%), or important (43%).


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• A similarly strong number of respondents rate the availability an IQ certification as very helpful (44%) or helpful (48%) to the goal of establishing IQ as a distinct profession.

• Confirming the strong market demand for an IQ certification, • Survey participants indicate that they intend to take the IQCP exam when it is

available (23%), or are likely to do so (43%). • And 75% indicate that they expect to receive various forms of employer’s

support for their certification effort. • Professional development and effectiveness appear to be the strongest

motivators for becoming certified, as 43% of respondents indicate that the most important benefit they expect of the IQ certification is increased knowledge and mastery of the information/data quality discipline.

• Greater credibility and recognition in the market place ranked second, with 30%. • Finally, respondents anticipate that their employers will expect (13%) or are likely

to expect (30%) employees who work in information / data quality to become IQ certified. Similar expectations are reported for consultants engaged by clients.

As awareness about the impact of information quality on business results continues to grow in public and private organizations worldwide, the forthcoming availability of a robust, independent and practitioner-validated professional certification is a clear sign that the information/data quality discipline is indeed emerging as a distinct profession, for the benefit to society as a whole.


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Introduction

Overview and Objectives

For the first time, a broad group of information/data quality practitioners across the globe has reached consensus on the definition of the job of information/data quality professional. This achievement represents a major milestone in the establishment of information/data quality as a distinct profession.

This breakthrough is the outcome of a job analysis study jointly conducted between October 2008 and March 2009 by IQ International, the International Association for Information and Data Quality (IQint), guided by CASTLE Worldwide, Inc. (CASTLE).

This report documents the findings of the job analysis study, focusing on the performance domains, tasks, knowledge and skills of the Information Quality Certified Professional.

The Association initiated the study in order to identify the duties and requirements of candidates for Information Quality Certified Professional (IQCPSM) credential it is developing. The major objective of the certification program is to identify individuals who are qualified to provide information / data quality services, across various roles of an organization. The credential will provide assurance that a IQCP has met eligibility criteria addressing training, experience, and the knowledge and skills needed for competence.

The association worked with CASTLE, a full-service certification and licensure testing service, to conduct the job analysis study. CASTLE’s process ensured that the IQCP job analysis meets established guidelines and standards for such an activity. CASTLE follows such widely accepted standards and regulations as the ISO/IEC 17024 for Personnel Certification Bodies, Standards for Educational and Psychological Testing, American Educational Research Association (1999); and the Uniform Guidelines on Employee Selection Procedures (1977 and updated); and Standards for the Accreditation of Certification Programs, published by the National Commission for Certifying Agencies (NCCA, 2002).

Definitions

This report uses the following pairs of terms interchangeably: data and information; as well as data quality and information quality. In addition, depending on the context, the label “business” is sometimes used as a synonym for “non-IT/IS”.


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Background and Summary of Development Process Job analysis is the primary process for identifying the competency areas necessary for proficient performance in a trade, and it provides a blueprint for examination development. A job analysis supplies the means by which one can establish the content validity of a certification examination. Content validity is the most commonly applied and accepted validation strategy for establishing certification examination programs today. In psychometric terms, validation is the documentation method that a test provider employs to illustrate how levels of competence can be inferred from a score on the examination. A content-valid examination for IQCPs will appropriately evaluate the knowledge and skills required to function as a competent Information Quality Professional.

Thus, job analysis is an integral part of ensuring the content validity of an examination—that the professional knowledge and skill assessed by the examination reflect the essential knowledge and skill that IQCPs use in their work. Job analysis documents that the domains and tasks of information quality are important, critical, and frequently performed. Importance, criticality, and frequency ratings collected from a broad spectrum of IQCPs play an important role in specifying the content of the examination.

The job analysis for the IQCP program consisted of the following three phases:

Phase I: Initial Development and Validation. An eleven-member job analysis panel identified the performance domains and tasks essential to the competence of a IQCP. The panel also defined the essential knowledge and skills.

Phase II: Validation Study. A sample of Information/data quality practitioners reviewed and validated the domains and tasks as defined by the job analysis panel.

Phase III: Development of Test Specifications. Using the ratings collected from Phase II, the test specifications for the certification examination were developed.


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Profile of the Information Quality Certified Professional (IQCPSM) For whom is the IQCPSM credential designed? The Information Quality Certified Professional (IQCPSM) is an individual who demonstrates broad expertise in and practical knowledge of information/data quality concepts, methods, skills and principles.

The IQCP designation will confirm that the holder has mastered the core information quality competencies and subscribes to the Information Quality Code of Ethics and Professional Conduct. By maintaining their credential through re-certification, IQCPs will affirm their commitment to ongoing professional development in order to keep their skills current.

IQCPs hold any of a wide range of positions in their organizations, as individual contributors or as managers. They conduct, lead, champion or participate in information quality projects. They work in any of the functions or disciplines within their organization or are part of a specialized information quality team; yet all perform information quality activities as part of their job responsibilities. This information quality work is either part-time within a broader organizational role, or on a full-time basis.

To be eligible to sit for the certification exam, IQCP candidates must meet specific educational and professional experience requirements. Using terminology of the United States educational system:

• A bachelor's (or equivalent) or higher degree and at least three (3) years of information/data quality related work experience, including 4,500 hours performing, leading or directing information/data quality activities within the performance domains of the IQCP Framework.

OR

• A high school diploma (or equivalent) and at least five (5) years of information/data quality related work experience, including 7,500 hours performing, leading or directing information/data quality activities within the performance domains of the IQCP Framework

The three and five years of experience do not have to be continuous, but must have been accrued within the last ten consecutive years prior to the application submission date. Equivalent degrees and diplomas from institutions outside the United States can be used as substitutes.

Compliance to the experience and education requirements will be assessed through the application review and audit processes.


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Phase I - Initial Development and Evaluation The first steps in analyzing the job of the Information Quality Certified Professional (IQCP) included the identification of the major categories of responsibility (performance domains) and the tasks performed within each domain.

On October 3 – 5, 2008, in Raleigh, North Carolina, USA, a job analysis panel of eleven experts assembled by the Association met to delineate the essential responsibilities of the IQCP. The members of this international panel represented a variety of professional backgrounds, geographic regions, and backgrounds. This meeting was facilitated by a CASTLE psychometrician. A complete listing of the panel members is contained in this report on page 4.

Phase I consisted of three major steps: domain development; task, knowledge and skill development; and panel evaluation of the domains and tasks.

Domain Development The panel determined that the job of the IQCP could be characterized by six performance domains, or major areas of responsibility. Performance domains form the bedrock of the job analysis study. These areas of concentration establish the structure of the overall framework of the work that a IQCP performs.

Tasks, Knowledge and Skills The panel delineated the tasks required for the IQCP to achieve minimum competence in the field of information quality. These tasks were assigned to one of the in each of the six appropriate performance domains. A task is an activity performed within the performance domain that answers questions such as “What activity do you perform?” (not “What activity should you perform”). The panel developed an initial list of 29 tasks – six for Domain I, five in Domain II, four in Domain III, four in Domain IV, six in Domain V, and four in Domain VI (see the tasks on pp. 15 through 20). The panel then identified the knowledge and skill required by the newly certified IQCP to perform the tasks in a competent manner. These were documented and assigned within task statements.

Panel Evaluation of Domains and Tasks A few panel members evaluated each performance domain and task, rating each on importance and criticality as applied to the work of the newly certified IQCP and the frequency with which the activities associated with each domain and task are performed. The work and assessments of that subset of the panel were subsequently submitted to further validation by a large sample of information quality professionals across the globe.


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Phases II and III - Validation Study and Development of Test Specifications

Survey Design and Distribution

Using the domains and tasks identified by the job analysis panel, CASTLE developed a survey to be completed by a sample of stakeholders involved in information quality activities within their organizations. The association provided contact information for a sample consisting of 1,087 qualified information / data quality practitioners. CASTLE distributed the survey to the sample and asked them to evaluate, validate, and provide feedback on the job analysis panel's domain and task lists. The survey also solicited demographic information from the respondents in order to ensure that a representative response and completion was provided by appropriately qualified individuals.

These stakeholders were invited to complete an on-line survey via an email sent from CASTLE. This invitation explained the importance of the job analysis validation study and provided each individual’s unique username and password. The survey tool allowed respondents to complete a portion of the tool and return at a later date to pick up where they left off.

The survey was launched on 24 November 2008 and closed on 22 December 2008. CASTLE sent several email reminder notices to the sample during the four-week data collection period. When the survey deadline was reached, a total of 144 respondents had returned usable surveys, a number that allows for meaningful interpretation of the results. The survey response rate of 13% is somewhat low but well within the range of acceptability for this type of survey.

Because not every participant answered every question, the number of respondents who answered a question is given by “n” in the tables and charts featured in this report. In addition for some questions multiple responses by each participant were allowed. This is designated where applicable in the tables and charts. Finally some survey questions included an “Other” option. The presence of an “Other” option allowed survey participants to add their own responses in addition to selecting answers from a pre-determined set. Whenever possible, this report lists alternative answers suggested by respondents when discussing the results for these open-ended questions.

Statistical Analysis of Domains and Tasks Ratings

The primary duty of survey participants was to evaluate each performance domain and task, rating each on importance and criticality as applied to the work of the newly certified IQCP and also rating the frequency with which they performed the activities associated with each domain and task.


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These ratings were subject to a rigorous statistical analysis to establish validity and reliability. The ratings were then used to determine the specifications of the IQCP exam.

This report presents the IQCP domains and tasks as validated by the 144 survey respondents.


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IQCP Domains and Tasks

The performance domains describe the major responsibilities or duties that define the role of the IQCP. Six performance domains emerged from the role delineation. These performance domains are:

1. Information Quality Strategy and Governance 2. Information Quality Environment and Culture 3. Information Quality Value and Business Impact 4. Information Architecture Quality 5. Information Quality Measurement and Improvement 6. Sustaining Information Quality

Appendix A contains the certification exam blueprint.

This practitioner-validated Framework can serve multiple purposes beyond its primary use as the basis for the IQCP exam test specifications:

• Practitioners and consultants can draw from it to develop internal data quality process audit instruments;

• Managers can use it as a resource to define training plans for themselves and for their staff

• Professors can use it to define information/data quality curriculum • Consultants can develop training courses to teach various component of the

Framework. • Subsets of the knowledge and skills listed can be used for others in the

organization who are not fully engaged in information/data quality management.


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PERFORMANCE DOMAIN 1

Information Quality Strategy and Governance

D1 Task 1

Develop an information quality strategy and implementation roadmap in alignment with business

objectives, by working with business and technology leaders and other key stakeholders in order

to manage information as an asset and form the basis for the guiding information principles and

policies.

D1 Task 2

Define information quality principles, policies, and standards by referring to the information

quality strategy and business objectives and by consulting with knowledgeable people, in order

to guide decision-making, prioritization, and organizational behaviors affecting information

quality.

D1 Task 3

Define and implement a data governance model by naming key roles and responsibilities,

formalizing accountability, establishing decision rights, and identifying channels for

communication, interaction and escalation within the model, in order to establish a management

system for governing information assets.

D1 Task 4

Enforce conformance to established information quality principles, policies, standards and

methods through the data governance process, so that behaviors and results optimize the value

of information assets.

D1 Task 5

Define a communication strategy by identifying key audiences, messages, desired actions and

results, in order to gain support for the information quality strategy and governance

D1 Task 5

Build essential relationships with senior leaders by communicating regularly, demonstrating value and highlighting business results, so they will champion, sponsor, and enforce the information quality mandate


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Information Quality Environment and Culture

D2 Task 1

Develop people at all levels in information quality strategy, principles and practices, by

establishing education and training programs, career paths and professional certifications, in

order to create organizational knowledge, skills and capabilities around the information quality

discipline

D2 Task 2

Establish recognition practices for people at all levels who improve information quality and

display desired behaviors, by providing incentives and controls in order to establish and sustain

the information quality environment and culture

D2 Task 3

Embed information quality values, standards, methods and practices into the business operations,

by integrating and aligning them with business and technology processes, projects and

governance structures in order to achieve desirable behaviors in managing information assets.

D2 Task 4

Establish information quality accountabilities, stewardship roles and responsibilities, working

relationships and structures for collaboration across all functions, through organizational and

stakeholder analysis in order to enable effective decision-making and process execution in

support of the overall governance model.

D2 Task 5

Educate all stakeholders in information quality principles, policies, standards and practices, by

using a variety of communication tactics in order to raise awareness, obtain broad organizational

adoption, management sponsorship and demonstrate integration of information quality into the

corporate culture.


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Information Quality Value and Business Impact

D3 Task 1

Evaluate information quality and business issues, objectives, and opportunities by establishing

and confirming business relevance and impact, in order to improve and increase the value of

information assets.

D3 Task 2

Prioritize information quality initiatives, projects, and tasks by developing business justification

and trade-offs in order to provide the basis for decisions and investments.

D3 Task 3

Obtain decisions on information quality initiatives, projects or tasks, by providing

recommendations and priorities to decision makers so they designate sponsorship and initiate

execution.

D3 Task 4

Provide stakeholders with the results of information quality initiatives, projects and tasks, by

determining expected versus realized outcomes, in order to demonstrate the value to the

business and the effectiveness of the information quality function.


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Information Architecture Quality

D4 Task 1

Participate in the establishment of standard definitions, business terms and rules when changes to

the information architecture are proposed, by preventing, identifying and removing defects in

order to achieve consistent understanding and usage of information throughout the enterprise

and across its boundaries.

D4 Task 2

Assess the quality of the information architecture components through rigorous testing against

standards and needs, in order to identify defects.

D4 Task 3

Drive the quality of information architecture components by leading improvement processes in

order to achieve information architecture stability, flexibility and reuse.

D4 Task 4

Coordinate the ongoing gathering and maintenance of business metadata by working with IT and

business partners, in order to assure that data usage and meaning is consistent across the

enterprise.


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Information Quality Measurement and Improvement

D5 Task 1

Gather additional business and data quality rules through appropriate techniques (such as

facilitated sessions, rule discovery, etc.), in order to complete the understanding of business

requirements for the specific data set to be assessed.

D5 Task 2

Determine the data quality targets by reviewing business objectives with business customers in

order to prioritize improvement efforts to close gaps.

D5 Task 3

Measure the actual data quality level of specific data sets using various techniques and the

conformance to a set of pre-established business and data quality rules, in order to identify data

and process improvement opportunities.

D5 Task 4

Determine the root causes of data quality issues using a structured problem-solving methodology

in order to identify the most effective way to fix and prevent the problem.

D5 Task 5

Coordinate the implementation of prioritized data improvement efforts using data quality

methods, practices and data standards, in order to eliminate data errors and resolve data issues

identified.

D5 Task 6

Improve processes and establish controls by working with appropriate teams, in order to permanently eliminate the root causes of the problem and reduce the probability of similar problems occurring in the future.


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Sustaining Information Quality

D6 Task 1

Answer questions about data content by acting as an internal consultant in order to increase

business customers’ knowledge and understanding of the data.

D6 Task 2

Continuously monitor and report data quality levels through ongoing DQ monitoring in order to

assure data quality levels are maintained.

D6 Task 3

Participate in the system development lifecycle by working with project teams, providing input

and reviewing project plans and deliverables, in order to ensure that information quality best

practices are incorporated in all IT development and support processes

D6 Task 4

Participate in data conversion and migration by engaging in the establishment of the project plan

and the methodology, including checkpoints, certification and migration sign-off, in order to

ensure information quality principles and best practices are implemented throughout the data

conversion and migration program.


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Business Need for Certification (Based on Survey Responses)

Organizational Need

What is the primary direct or indirect business focus of your organization’s current information/data quality efforts?

The most common primary direct or indirect business focus was Compliance, Risk (38.7%) followed by Cost Reduction (28.6%). Health, Safety, Environment was chosen the least amount by respondents (3.4%) among options shown. However, many other focus areas were submitted in the open-ended “Other” category.

Primary Business Focus of IQ/DQ Efforts (n=119)

Compliance, Risk

38.7%

Cost reduction28.6%

Other*14.3%

Health, Safety, Environment

3.4%

Revenue growth15.1%

*Other responses included: all of the above, Accurate reporting for decision making; cost reduction, Business Process Execution, Client-specific, Cost reduction through improved compliance, Customer satisfaction (2), data quality improvement products, Education, Efforts are not well focused in any direction, Improve data migration success, improve effectiveness and reduce costs in delivering on our mandate, Increased contractual opportunities, Migration to new ERP, Performance Measurement, and Process efficiency.


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How successful are your organization’s current information quality efforts (formal or informal)?

Respondents were asked to indicate how successful they felt their organization’s IQ efforts are on a five point (Very unsuccessful to Very successful) scale. Results were relatively positive indicating that respondents thought that their organization’s IQ efforts are Very Successful (10.1%) or Successful (46.2%). However, a large percentage of respondents reported that these efforts are neither Successful nor Unsuccessful (36.1%). Perhaps success is too difficult to measure quantitatively. Further, less than ten percent of respondents chose the negative response options on the scale (Unsuccessful and Very Unsuccessful).

Success of IQ/DQ Efforts (n=119)

Very successful

10.1%

Successful46.2%Neither

successful nor unsuccessful

36.1%

Very unsuccessful

1.7%

Unsuccessful5.9%


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Professional Need

How important is it to you that information/data quality becomes established and recognized as a distinct profession?

Respondents were asked to indicate the level of importance they felt regarding the field of IDQ becoming recognized as a distinct profession on a five point scale (Not at all important to Very important). Results were overwhelmingly positive that respondents thought either that IDQ becoming a distinct profession as Very Important (48.7%) or Important (42.9%). Fewer than ten percent of respondents chose other options on the scale.

Importance of IQ/DQ as a Distinct Profession (n=119)

Not at all important

0.8%

Don’t know0.0%

Unimportant0.0%

Neither important nor unimportant

7.6%

Important42.9%

Very important48.7%


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How helpful is the existence of an IQ certification to the goal of establishing information/data quality as a distinct profession?

Respondents were asked to indicate how helpful they felt the existence of an IQ certification is to the field of IDQ becoming recognized as a distinct profession on a five point scale (Not at all helpful to Very helpful). Similar to the data shown on the previous page, results were overwhelmingly positive that an IQ certification would be Very Helpful (43.7%) or Helpful (47.9%) to the goal of establishing information/data quality as a distinct profession. Fewer than ten percent of respondents chose other options on the scale. Only one respondent (0.8%) indicated that the establishing the certification program is not at all helpful to the field of IQ.

Helpfulness of IQ/DQ Certification in Establishing the Profession (n=119)

Very helpful43.7%

Helpful47.9%

Neither helpful nor unhelpful

5.9%

Unhelpful0.0%

Don’t know1.7%

Not at all helpful0.8%


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Will you take the IQCP exam when it becomes available?

The next question asked respondents directly if they intend to take the IQCP examination once it is released. More than half of survey respondents answered Yes or Likely Yes to this question (22.7% and 42.9%, respectively). Nearly a quarter of candidates were uncertain of whether or not they intend to take the examination (27.7%). Negative responses (Unlikely and No) totaled less than 10% of respondents (5.0% and 1.7%, respectively).

Intention to Take the CIQP Exam (n=119)

Yes22.7%

Likely yes42.9%

Not sure27.7%

Unlikely5.0%

No1.7%


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Please indicate the level of support you expect to receive from your employer for certification and re-certification.

These answers to this question indicate that a multitude of different levels of support from employers are expected, the most common being reimbursement for examination fees (59) and application fees (59). A large number of respondents also indicated that their employers reimburse the costs of exam preparation courses (39) and review materials (39). It should be noted that 16 respondents reported that they do not receive any level of support from their employer for the purposes of certification.

*The responses written by the respondents to the “Other” category included “unemployed trying to be self-employed”, “Optional tax relief on recognized training from registered provider,” “bonus likely for passing cert,” “The level of support depends on other competing demands at the time,” “Answers are for former employer,” “Dependent upon the market pressure,” “Don't know,” “Not sure yet,” and “Would need to be reviewed,”

Expected Employer’s Support for Certification (n=118) Frequency Percent

My employer will reimburse me for the application fee 59 50.0%

My employer will reimburse me for examination fee(s). 59 50.0%

My employer will reimburse me for examination preparation course(s).

39 33.1%

My employer will reimburse me for books and other review materials.

39 33.1%

My employer will allow time away from work to sit for the examination(s).

25 21.2%

My employer will reimburse me for continuing professional development (e.g. conferences, seminars) so I can maintain my certification.

17 14.4%

My employer will allow time away from work to attend preparation courses.

11 9.3%

My employer will reimburse me for renewal/re-certification fees. 11 9.3%

Other* 9 7.6%

None; my employer does not provide support for certification or re-certification.

16 13.6%

Not applicable, I am self-employed. 14 11.9%


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What would be the most important benefit you expect to gain by obtaining the IQ certification?

The benefit of IQ certification chosen more than any other option was “Increased knowledge and mastery of the Information/data quality discipline” (42.9%) followed by “Greater credibility and recognition in the marketplace” (30.3%). Other notable responses were “Self-satisfaction and validation of my expertise” (7.6%) and “Greater job security” (0.8%).

* The only response written by the respondents to the “Other” category was “Overtime”

Most Important Benefit Expected of IQ Certification (n=118)

0.0%

0.0%

0.8%

0.8%

2.5%

4.2%

7.6%

10.9%

30.3%

42.9%

0% 5% 10% 15% 20% 25% 30% 35% 40% 45%

Higher pay/greater pay opportunities

Faster career advancement/promotion

Other*

Greater job security

Nothing will change

Better career options

Self-satisfaction and validation of my expertise

Greater credibility and recognition within myorganization

Greater credibility and recognition in the marketplace

Increased knowledge and mastery of theInformation/data quality discipline


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Do you believe your organization will eventually expect employees who work in information/data quality to become IQ certified?

Respondents were asked if they expect the IQ certification to become a work expectation in their organizations. A large percentage of survey respondents answered positively (Yes or Likely Yes) to this question (12.6% and 29.4%, respectively).

Yes12.6%

Likely yes29.4%

Not sure37.0%

Unlikely17.6%

No3.4%

IQ Certification Expectation for Employees (n=119)

Yes10.1%

Likely yes29.4%

Not sure40.3%

Unlikely13.4%

No6.7%

IQ Certification Expectation for Consultants (n=119)

Do you believe your organization will eventually expect consultants it hires to be IQ certified?

Respondents were asked if they expect the IQ certification to become an expectation for the consultants hired by their organizations. With the exception of “Unsure” respondents, responses to this question were very similar to responses to the previous question. A large percentage of survey respondents answered positively (Yes or Likely Yes) to this question (10.1% and 29.4%, respectively).


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Conclusion For the first time, a broad group of information/data quality practitioners across the globe has reached consensus on the definition of the job of information/data quality professional. This achievement represents a major milestone in the establishment of information/data quality as a distinct profession.

IQ International contracted with CASTLE Worldwide, Inc in 2008 to delineate the role of the IQCP in compliance with the Uniform Guidelines on Employee Selection Procedures (EEOC, 1978) and National Commission for Certifying Agencies (NCCA) Standards for the Accreditation of Certification Programs.

The consensus definition of the job of an Information Quality Certified Professional (IQCP) consists of a framework containing six (6) performance domains, twenty-nine (29) tasks, and more than three hundred (300) distinct knowledge and skills.

The practitioner survey conducted as part of this work validates the consensus of the job analysis panel assembled by the Association, on the important duties and requirements of someone working in the information / data quality profession. As such, the domains and tasks developed by the job analysis panel and validated by the survey respondents constitute an accurate definition of the work of IQCP. The resulting examination blueprint provides a solid foundation for generating content for a high-stakes examination.

As awareness about the impact of information quality on business results continues to grow in public and private organizations worldwide, the forthcoming availability of a robust, independent and practitioner-validated professional certification is a clear sign that the information/data quality discipline is indeed emerging as a distinct profession, for the benefit to society as a whole.


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Appendix A: IQCP(SM) Exam Blueprint

EXAM SPECIFICATIONS

Domain Name Number of Tasks

Percent of Questions in Certification

Exam

Information Quality Strategy and Governance 6 17%

Information Quality Environment and Culture 5 13%

Information Quality Value and Business Impact 4 18%

Information Architecture Quality 4 11%

Information Quality Measurement and Improvement

6 20%

Sustaining Information Quality 4 21%

The certification exam is 3-hours long, closed-book, and consists of 150 multiple choice questions with four possible answers each. Following Bloom’s Taxonomy, the questions assess three cognitive domains: Recall/Understanding, Application and Analysis.


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DOMAIN 1 - Information Quality Strategy & Governance

D1 Task 1

Task 1

Develop an information quality strategy and implementation roadmap in alignment with business objectives, by working with business and technology leaders and other key stakeholders in order to manage information as an asset and form the basis for the guiding information principles and policies.

Knowledge of:

1. Strategy and strategic planning fundamentals 2. Organizational characteristics that facilitate or hinder data quality management and

improvement 3. Philosophies and methodologies of quality pioneers 4. Philosophies and methodologies of information/data quality pioneers 5. Information quality best practices 6. Data quality standards, laws and regulations 7. Approaches to managing data as an asset 8. Information lifecycle concepts 9. Typical data categories 10. Ways data quality affects business results and objectives 11. Critical success factors of information quality management 12. Employee involvement techniques

Skill in:

1. Assessing an organization's information quality management maturity 2. Identifying an organization's most important data 3. Identifying how data can be used strategically to derive competitive advantage 4. Translating strategic business requirements into supporting IQ projects and initiatives 5. Articulating the cost of poor quality information and the business value of high quality

information 6. Negotiation, consensus building 7. Stakeholder identification and analysis 8. Systems thinking 9. Strategic thinking


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D1 Task 2

Task 2

Define information quality principles, policies, and standards by referring to the information quality strategy and business objectives and by consulting with knowledgeable people, in order to guide decision-making, prioritization, and organizational behaviors affecting information quality

Knowledge of:

1. Organizational characteristics that facilitate or hinder data quality management and improvement

2. Information quality best practices 3. Fundamental quality principles and their application to information quality 4. Philosophies and methodologies of quality pioneers 5. Philosophies and methodologies of information/data quality pioneers 6. Ways data quality affects business results and objectives 7. Critical success factors of information quality management 8. Enterprise Architecture concepts and typical information principles

Skill in:

1. Defining principles that are meaningful and applicable to all parts of the organization 2. Integrating information quality principles, policies and standards with the organization's

governing and guidance practices 3. Translating strategic business requirements into supporting IQ projects and initiatives 4. Negotiation, consensus building 5. Stakeholder identification and analysis 6. Systems thinking 7. Verbal and written communications, with a technical or business audience


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D1 Task 3

Task 3

Define and implement a data governance model by naming key roles and responsibilities, formalizing accountability, establishing decision rights, and identifying channels for communication, interaction and escalation within the model, in order to establish a management system for governing information assets.

Knowledge of:

1. Approaches to managing data as an asset 2. Best practice data governance models 3. Corporate governance structure and organizational hierarchy 4. Typical data governance activities 5. Processes to link and align strategy, governance, performance and rewards 6. Properties of data that differentiate it from other assets 7. Team structure and team processes

Skill in:

1. Assessing organizational readiness for data governance 2. Defining a fit-for-purpose data governance model 3. Identifying and assessing existing formal and informal information-related decision-makers and

power-holders 4. Defining business processes, process owners, and audit control points for issue identification

and resolution through the governance structure 5. Setting governance goals and performance measurements 6. Defining and articulating the value of data governance 7. Building partnerships, especially between IT and non-IT teams 8. Negotiation, consensus building 9. Stakeholder identification and analysis 10. Systems thinking 11. Leading change 12. Verbal and written communications, with a technical or business audience


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D1 Task 4

Task 4

Enforce conformance to established information quality principles, policies, standards and methods through the data governance process, so that behaviors and results optimize the value of information assets.

Knowledge of:

1. Auditing fundamentals 2. Motivation theories 3. Typical data governance measurement best practices 4. Data governance maturity models 5. Ways to assess the effectiveness of the information quality function 6. IQ International Codeof Ethics and Professional Conduct

Skill in:

1. Setting governance goals and performance measurements 2. Defining incentives and penalties for conformance and non-conformance to the governance

model 3. Building information quality requirements into job descriptions 4. Defining and articulating the value of data governance 5. Negotiation, consensus building 6. Collaboration, coalition-building 7. Conflict resolution 8. Leading change


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D1 Task 5

Task 5

Define a communication strategy by identifying key audiences, messages, desired actions and results, in order to gain support for the information quality strategy and governance.

Knowledge of:

1. Communications methods and best practices 2. Diffusion of innovations concepts

Skill in:

1. Developing a communication plan 2. Communicating effectively with all levels of the organization 3. Verbal and written communications, with a technical or business audience 4. Leading change 5. Stakeholder identification and analysis 6. Collaboration, coalition-building


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D1 Task 6

Task 6

Build essential relationships with senior leaders by communicating regularly, demonstrating value and highlighting business results, so they will champion, sponsor, and enforce the information quality mandate.

Knowledge of:

1. Communications methods and best practices 2. Management functions and roles (planning, organizing, leading, controlling) 3. Management roles in information quality 4. Financial management fundamentals 5. Diffusion of innovations concepts

Skill in:

1. Communicating effectively with all levels of the organization 2. Verbal and written communications, with a technical or business audience 3. Translating strategic business requirements into supporting IQ projects and initiatives 4. Articulating the cost of poor quality information and the business value of high quality

information 5. Strategic thinking 6. Leading change 7. Stakeholder identification and analysis 8. Collaboration, relationship-building 9. Negotiation, consensus building


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DOMAIN 2 - Information Quality Environment & Culture

D2 Task 1

Task 1

Develop people at all levels in information quality strategy, principles and practices, by establishing education and training programs, career paths and professional certifications, in order to create organizational knowledge, skills and capabilities around the information quality discipline

Knowledge of:

1. Adult learning characteristics 2. Training and professional development best practices 3. Best practices for segmenting training audience 4. Typical information quality training topics

Skill in:

1. Assessing the effectiveness of training programs 2. Building internal communities for knowledge sharing


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D2 Task 2

Task 2

Establish recognition practices for people at all levels who improve information quality and display desired behaviors, by providing incentives and controls in order to establish and sustain the information quality environment and culture.

Knowledge of:

1. Motivation theories 2. Characteristics of organizational culture 3. Organizational characteristics that facilitate or hinder data quality management and

improvement 4. Critical success factors of information quality management 5. IQ International Codeof Ethics and Professional Conduct

Skill in:

1. Developing recognition programs


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D2 Task 3

Task 3

Embed information quality values, standards, methods and practices into the business operations, by integrating and aligning them with business and technology processes, projects and governance structures in order to achieve desirable behaviors in managing information assets.

Knowledge of:

1. Typical business processes of the organization 2. Information lifecycle concepts 3. Organizational characteristics that facilitate or hinder data quality management and

improvement 4. Critical success factors of information quality management 5. Information quality best practices 6. IQ International Codeof Ethics and Professional Conduct 7. Ways in which data quality affects business results and objectives 8. Best practices for assuring the quality of data from external suppliers

Skill in:

1. Recognizing the information quality management as an open system, influenced and being influenced by its environment

2. Identifying how data is created, updated, retained, exchanged and used by the various activities of the organization

3. Incorporating information quality responsibilities in job descriptions across the organization 4. Facilitating the identification, transfer and adoption of information quality best practices 5. Leading change


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D2 Task 4

Task 4

Establish information quality accountabilities, stewardship roles and responsibilities, working relationships and structures for collaboration across all functions, through organizational and stakeholder analysis in order to enable effective decision-making and process execution in support of the overall governance model.

Knowledge of:

1. Data stewardship models and best practices 2. Organizational characteristics that facilitate or hinder data quality management and

improvement 3. Decision making models and processes 4. Techniques for process and information chain analysis (internal and external) 5. Ways in which data quality affects business results and objectives 6. Employee involvement processes 7. Team structures and processes

Skill in:

1. Identifying and meeting the needs of internal and external customers 2. Stakeholder identification and analysis 3. Identifying how data is created, updated, retained, exchanged and used by the various

activities of the organization 4. Incorporating information quality responsibilities in job descriptions across the organization 5. Leading change


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D2 Task 5

Task 5

Educate all stakeholders in information quality principles, policies, standards and practices, by using a variety of communication tactics in order to raise awareness, obtain broad organizational adoption, management sponsorship and demonstrate integration of information quality into the corporate culture.

Knowledge of:

1. Diffusion of innovations concepts 2. Characteristics of organizational culture 3. Critical success factors of information quality management 4. IQ International Codeof Ethics and Professional Conduct 5. Communications methods and best practices 6. Facilitation techniques

Skill in:

1. Developing a communication plan 2. Assessing the effectiveness of a communications program 3. Stakeholder identification and analysis 4. Identifying and meeting the needs of internal and external customers 5. Assessing commitment 6. Verbal and written communications, with a technical or business audience 7. Communicating effectively with all levels of the organization


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DOMAIN 3 - Information Quality Value and Business Impact

D3 Task 1

Task 1

Evaluate information quality and business issues, objectives, and opportunities by establishing and confirming business relevance and impact, in order to improve and increase the value of information assets.

Knowledge of:

1. Ways in which data quality affects business results and objectives 2. Techniques for process and information chain analysis 3. Approaches to managing data as an asset 4. Organizational characteristics that facilitate or hinder data quality management and

improvement 5. Various techniques for assessing the cost, value and business impact of data quality 6. Data quality dimensions/characteristics 7. Strategy and strategic planning fundamentals 8. Data quality standards, laws and regulations 9. Information quality best practices 10. Enterprise architecture concepts 11. IQ International Codeof Ethics and Professional Conduct

Skill in:

1. Eliciting business needs and requirements 2. Identifying an organization’s most important data 3. Conducting objective assessments and subjective assessments 4. Assessing an organization’s information quality management maturity 5. Interpreting data quality assessment findings and articulating their impact on business results 6. Measuring and communicating the cost of poor quality information data and the business value

of high quality information 7. Determining and communicating the ROI of data quality improvement projects 8. Synthesis 9. Systems thinking 10. Stakeholder identification and analysis


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D3 Task 2

Task 2

Prioritize information quality initiatives, projects, and tasks by developing business justification and trade-offs in order to provide the basis for decisions and investments.

Knowledge of:

1. Prioritization techniques and tools 2. Typical causes of information quality problems 3. Organizational decision-making and planning processes 4. Various techniques for assessing the cost, value and business impact of data quality 5. Organizational characteristics that facilitate or hinder data quality management and

improvement 6. Strategy and strategic planning fundamentals 7. Capital budgeting 8. Risk analysis 9. Financial management fundamentals 10. Project management fundamentals 11. IQ International Codeof Ethics and Professional Conduct

Skill in:

1. Defining IQ projects with manageable scope 2. Determining and communicating the return on investment (ROI) of data quality improvement

projects 3. Identifying an organization’s most important data 4. Leading change 5. Articulating the costs of poor quality information and the business value of high quality

information 6. Issue tracking and resolution 7. Meeting facilitation 8. Negotiation, consensus-building 9. Conflict resolution 10. Systems thinking 11. Verbal and written communications, with a technical or business audience


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D3 Task 3

Task 3

Obtain decisions on information quality initiatives, projects or tasks, by providing recommendations and priorities to decision makers so they designate sponsorship and initiate execution.

Knowledge of:

1. Organizational decision-making and planning processes 2. Prioritization techniques and tools 3. Various techniques for assessing the cost, value and business impact of data quality 4. Organizational characteristics that facilitate or hinder data quality management and

improvement 5. Critical success factors of information quality management 6. Various types of project sponsorship 7. Strategy deployment 8. IQ International Codeof Ethics and Professional Conduct

Skill in:

1. Project scoping, planning and costing 2. Communicating effectively with all levels of the organization 3. Leading change 4. Assessing commitment 5. Articulating the costs of poor quality information and the business value of high quality

information 6. Issue tracking and resolution 7. Meeting facilitation 8. Effective presentations 9. Negotiation, consensus-building 10. Conflict resolution 11. Verbal and written communications, with a technical or business audience


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D3 Task 4

Task 4

Provide stakeholders with the results of information quality initiatives, projects and tasks, by determining expected versus realized outcomes, in order to demonstrate the value to the business and the effectiveness of the information quality function.

Knowledge of:

1. Project review and evaluation techniques 2. Critical success factors of information quality management 3. Various techniques for assessing the cost, value and business impact of data quality 4. Organizational characteristics that facilitate or hinder data quality management and

improvement 5. IQ International Codeof Ethics and Professional Conduct

Skill in:

1. Conducting objective assessments and subjective assessments 2. Assessing an organization’s information quality management maturity 3. Interpreting data quality assessment findings and articulating their impact on business results 4. Measuring and communicating the cost of poor quality information and the business value of

high quality information 5. Defining information quality scorecard and metrics 6. Determining and communicating the return on investment (ROI) of data quality improvement

projects 7. Synthesis 8. Systems thinking 9. Issue tracking and resolution 10. Conflict resolution 11. Verbal and written communications, with a technical or business audience 12. Stakeholder identification and analysis


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DOMAIN 4 - Information Architecture Quality

D4 Task 1

Task 1

Participate in the establishment of standard definitions, business terms and rules when changes to the information architecture are proposed, by preventing, identifying and removing defects in order to achieve consistent understanding and usage of information throughout the enterprise and across its boundaries.

Knowledge of:

1. Definition of information architecture 2. Typical business and IT processes that lead to changes to the information architecture 3. The various ways in which the quality of the Information architecture affects data quality 4. Purpose of data standards 5. Typical Information architecture quality dimensions/characteristics 6. Data modeling concepts (conceptual, logical and physical data models) 7. Enterprise Architecture frameworks and concepts 8. Purpose of a metadata repository

Skill in:

1. Articulating the business value of quality data definitions and architecture 2. Negotiation, consensus-building 3. Meeting facilitation 4. Formulating quality business definitions and business/data quality rules 5. Conceptual/taxonomic thinking


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D4 Task 2

Task 2

Assess the quality of the information architecture components through rigorous testing against standards and needs, in order to identify defects.

Knowledge of:

(a) Typical information architecture components (b) Definitions of clarity, stability, flexibility and reusability in the context of information

architecture (c) Typical information architecture quality dimensions/characteristics (d) Data modeling concepts (conceptual, logical and physical data models) (e) Information architecture best practices (f) Fundamental database concepts

Skill in:

1. Eliciting business needs and requirements 2. Understanding data models 3. Measuring, interpreting and reporting information architecture quality 4. Planning and conducting objective and subjective assessments 5. Assessing the business impact of poor information architecture


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D4 Task 3

Task 3

Drive the quality of information architecture components by leading improvement processes in order to achieve information architecture stability, flexibility and reuse.

Knowledge of:

1. Definition of information architecture 2. Typical information architecture components 3. The various ways the quality of the information architecture affects data quality 4. Typical information architecture quality dimensions/characteristics 5. Definitions of clarity, stability, flexibility and reusability in the context of information

architecture 6. Purpose of a metadata repository 7. Information architecture best practices

Skill in:

1. Articulating the business value of information architecture quality 2. Translating business customer needs and requirements into information architecture

specifications 3. Leading improvement projects and teams 4. Structured problem-solving and root-cause analysis 5. Leading change 6. Applying process management to the metadata lifecycle 7. Process mapping and documentation 8. Negotiation, consensus-building 9. Meeting facilitation 10. Project management 11. Verbal and written communications, with technical or business audience


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D4 Task 4

Task 4

Coordinate the ongoing gathering and maintenance of business metadata by working with IT and business partners, in order to assure that data usage and meaning is consistent across the

enterprise.

Knowledge of:

1. Typical business metadata 2. Typical data quality dimensions/characteristics 3. Metadata management and delivery 4. Establishing business metadata standards 5. Implementing data quality through metadata 6. Purpose of a metadata repository

Skill in:

1. Translating business needs and objectives into business metadata requirements 2. Articulating the business value of business metadata 3. Treating metadata as data and applying information quality principles to metadata 4. Process mapping and documentation 5. Verbal and written communications, with technical or business audience 6. Ability to derive and compare implied meanings and inferences from business rules and

definitions 7. Negotiation, consensus-building 8. Applying process management to the metadata lifecycle 9. Conceptual/taxonomic thinking


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DOMAIN 5 - Information Quality Measurement and Improvement

D5 Task 1

Task 1

Gather additional business and data quality rules through appropriate techniques (such as facilitated sessions, rule discovery, etc.), in order to complete the understanding of business requirements for the specific data set to be assessed.

Knowledge of:

1. Rules discovery techniques and tools 2. Data profiling 3. Data quality assessment 4. Roles of data stewards 5. Data quality laws, regulations and standards

Skill in:

1. Eliciting business needs and requirements 2. Translating data quality problems and business customer needs into data quality rules 3. Interpreting data profiling and data quality assessment results and translating them into data

quality rules 4. Translating data quality laws, regulations and standards into data quality rules 5. Using data quality dimensions/characteristics to solicit and classify data quality requirements 6. Formulating quality business/data quality rules 7. Meeting facilitation 8. Negotiation, consensus-building 9. Conflict resolution 10. Verbal and written communications, with a technical or business audience 11. Ability to translate business needs into technical language and visa versa.


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D5 Task 2

Task 2

Determine the data quality targets by reviewing business objectives with business customers in order to prioritize improvement efforts to close gaps.

Knowledge of:

1. Prioritization techniques and tools 2. Data quality planning and target-setting best practices 3. IQ International Codeof Ethics and Professional Conduct

Skill in:

1. Eliciting business needs and requirements 2. Translating business customer needs and requirements into data quality targets 3. Linking data quality targets to business objectives 4. Project scoping and planning 5. Determining and communicating the ROI of data quality improvement projects 6. Meeting facilitation 7. Negotiation, consensus-building 8. Conflict resolution 9. Verbal and written communications, with a technical or business audience


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D5 Task 3

Task 3

Measure the actual data quality level of specific data sets using various techniques and the conformance to a set of pre-established business and data quality rules, in order to identify data and process improvement opportunities.

Knowledge of:

1. Data quality dimensions/characteristics 2. Data quality assessment techniques 3. Data profiling 4. Accuracy assessment techniques 5. Sampling techniques 6. Basic statistics 7. Data flow/information chain measurement techniques 8. Data quality metrics design 9. Relational database concepts 10. Basic SQL 11. IQ International Codeof Ethics and Professional Conduct

Skill in:

1. Defining the objectives of DQ assessments in order to define the most appropriate assessment method

2. Measuring the quality of data against various data quality dimensions/characteristics 3. Translating data profiling, statistical, and other assessment results into data quality

measurements 4. Interpreting, explaining and communicating data quality measurements 5. Identifying the best improvement techniques for various types of data quality defects 6. Articulating the value of process improvement 7. Documenting and reporting data quality assessment findings


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D5 Task 4

Task 4

Determine the root causes of data quality issues using a structured problem-solving methodology in order to identify the most effective way to fix and prevent the problem.

Knowledge of:

1. Typical causes of data quality problems 2. Root cause problem-solving techniques and tools 3. Error proofing techniques 4. Techniques for process and information chain analysis and improvement 5. IQ International Codeof Ethics and Professional Conduct

Skill in:

1. Root cause analysis 2. Systems thinking 3. Meeting planning and facilitation 4. Negotiation, consensus-building 5. Conflict resolution 6. Logical thinking, intuitive thinking 7. Analyzing problems at multiple levels of perspective 8. Identifying inter-relationships and inter-dependencies 9. Ability to translate business needs into technical language and visa versa


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D5 Task 5

Task 5

Coordinate the implementation of prioritized data improvement efforts using data quality methods, practices and data standards, in order to eliminate data errors and resolve data issues identified.

Knowledge of:

1. Fundamental quality principles and their application to information quality 2. Information quality best practices 3. Philosophies and methodologies of information/data quality pioneers 4. Data governance and data stewardship 5. Data improvement techniques (cleansing, enrichment, entity extraction and resolution, etc.) 6. IQ International Codeof Ethics and Professional Conduct

Skill in:

1. Leading improvement teams 2. Project management fundamentals 3. Leading several concurrent projects 4. Measuring and communicating the cost of poor quality data and the value of high quality data 5. Determining and communicating the ROI of data quality improvement projects 6. Balancing error correction with prevention through process improvement 7. Leading change 8. Managing expectations 9. Conflict resolution


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D5 Task 6

Task 6 Improve processes and establish controls by working with appropriate teams, in order to

permanently eliminate the root causes of the problem and reduce the probability of similar problems occurring in the future.

Knowledge of:

1. Statistical Process Control (SPC) 2. Error-proofing techniques 3. Process improvement methods, techniques and tools 4. Fundamental quality principles and their application to information quality 5. Information quality best practices 6. Organizational characteristics that facilitate or hinder data quality management and

improvement 7. Data quality pioneers and their methodologies 8. Data governance and data stewardship 9. Techniques for process and information chain analysis and improvement 10. Information lifecycle management 11. IQ International Codeof Ethics and Professional Conduct

Skill in:

1. Formulating information quality metrics to monitor processes 2. Leading improvement teams 3. Project management fundamentals 4. Leading several concurrent projects 5. Measuring and communicating the cost of poor quality data and the value of high quality data 6. Determining and communicating the ROI of data quality improvement projects 7. Balancing error correction with prevention through process improvement 8. Developing a data quality scorecard 9. Auditing fundamentals 10. Managing expectations 11. Conflict resolution


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DOMAIN 6 - Sustaining Information Quality

D6 Task 1

Task 1 Answer questions about data content by acting as an internal consultant in order to increase

business customers’ knowledge and understanding of the data.

Knowledge of:

1. Typical business and technical metadata 2. Typical causes of data quality problems 3. Data categories 4. Data quality dimensions/characteristics 5. Enterprise Architecture frameworks and concepts 6. Data modeling concepts (conceptual, logical and physical data models) 7. IQ International Codeof Ethics and Professional Conduct

Skill in:

1. Internal consulting 2. Mapping business problems back to data quality root causes 3. Mapping data flows and business processes 4. Verbal and written communication, with both a business or technical audience 5. Listening 6. Meeting Facilitation 7. Mapping data quality problems or needs to the appropriate data quality dimensions /

characteristics 8. Structured problem-solving, research 9. Logical thinking, intuitive thinking 10. Facilitating the identification, transfer and adoption of information quality best practices


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D6 Task 2

Task 2 Continuously monitor and report data quality levels through ongoing DQ monitoring in order to

assure data quality levels are maintained.

Knowledge of:

1. Differences between ongoing data quality monitoring and baseline/one-time assessments 2. Data quality dimensions/characteristics 3. Accuracy measurement 4. Data profiling 5. Information chain analysis 6. Random sampling techniques 7. Statistical Process Control (SPC) 8. Philosophies and methodologies of information/data quality pioneers 9. IQ International Codeof Ethics and Professional Conduct

Skill in:

1. Planning and conducting objective and subjective assessments 2. Translating business customer needs and requirements into data quality specifications 3. Defining a data quality scorecard/dashboard 4. Interpreting data quality measurements and articulating their implications to business process

results 5. Detecting, interpreting and resolving data quality anomalies 6. Using data quality monitoring results to formulate and implement process improvement and

error prevention recommendations 7. Structured problem-solving and root-cause analysis 8. Leading improvement projects and teams 9. Leading change 10. Negotiation, consensus-building


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D6 Task 3

Task 3 Participate in the system development lifecycle by working with project teams, providing

input and reviewing project plans and deliverables, in order to ensure that information quality best practices are incorporated in all IT development and support processes.

Knowledge of:

1. Typical system development lifecycle approaches (e.g. waterfall, agile) 2. Information quality best practices for application and database design 3. Data modeling concepts (conceptual, logical and physical data models) 4. Enterprise Architecture concepts 5. Data stewardship roles in system development 6. Metadata management

Skill in:

1. Internal consulting 2. Quality assurance 3. Process auditing 4. Ability to turn information quality best practices into system development policies,

procedures, roles and requirements specifications 5. Negotiation, consensus-building 6. Project management fundamentals 7. Leading change


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D6 Task 4

Task 4 Participate in data conversion and migration by engaging in the establishment of the project

plan and the methodology, including checkpoints, certification and migration sign-off, in order to ensure information quality principles and best practices are implemented throughout the data conversion and migration program.

Knowledge of:

1. Various types of data conversion/migration projects 2. Typical reasons why data conversion/migration projects fail 3. Typical system development lifecycle approaches (e.g. waterfall, agile) 4. Data quality problems caused by improper data migrations or system consolidations 5. Data modeling concepts (conceptual, logical and physical data models) 6. Data quality dimensions/characteristics 7. Accuracy measurement 8. Data profiling 9. Rule-based data quality assessment 10. Techniques for process and information chain analysis 11. Techniques for data cleansing, data matching, entity extraction and resolution, data enrichment 12. Categories of data quality tools and when to use them

Skill in:

1. Assessing data conversion/migration risk 2. Incorporating data quality best practices in data migration project plans 3. Source-to-target mapping techniques 4. Data gap analysis between source and target systems 5. Developing data transformation rules 6. Using findings from the data quality assessment to formulate and implement process

improvement and error prevention recommendations 7. Meeting planning and facilitation 8. Negotiation, consensus-building 9. Project management fundamentals


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Appendix B: Who Responded to the Survey? Respondents’ Demographics

Personal Profile

In which region of the world do you work?

Greater than half of all respondents reported that they work in North America, which includes Canada, the United States, and Mexico (64.7%). One fifth of respondents reported working in Europe (24.41%) while less than ten percent of respondents reported working in Africa, Asia or Australia (1.7%, 1.7%, and 7.6%, respectively). No respondents to this survey reported that they work in Central or South America.

Geographical Location (n=119)

North America (Canada, US,

Mexico)64.7%

Europe24.4%

Australia / Oceania

7.6%

Africa1.7%

Asia (includes Middle East)

1.7%

Central and South America

0.0%


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Gender and age

As indicated in Table 24 and Figure 24, more than twice as many men (69.5%) than women (30.5%) responded to this survey.

Gender (n=118)

Male69.5%

Female30.5%

The large majority of respondents indicated that they are either between the ages of 42 and 49 (37.8%) or 50 and 60 (30.3%). All respondents reported being older than the age of 26 while approximately 26% of candidates indicated being between the ages of 26 and 41.

Age (years) (n=119)

8.4%

17.6%

37.8%

30.3%

5.9%

0.0%0%

10%

20%

30%

40%

21-25 26-33 34-41 42-49 50-60 More than60 yrs old

Perc

ent


Page 62 of 74

What is the highest level of education that you have completed (if international, please select closest US equivalent)?

Respondents were asked to indicate the highest level of education completed. For respondents who answered this question, an equal number of candidates reported having either a Bachelor’s degree or Master’s degree (40.0% and 37.5%, respectively). These two groups made up the majority of survey respondents. Ten percent of candidates reported achieving a degree at the Doctorate level.

Highest Level of Education Achieved (n=120)

Bachelor’s degree40.0%

Master’s degree37.5%

Doctorate10.0% Associate

degree8.3%

High-School or less0.8%

Some college courses

3.3%


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What was the major of your highest degree/diploma?

119 responses to this question were collected and summarized below.

• Accounting • Analytical Chemistry • Applied Economics (Statistics) • Art History • Bachelor's Degree • Banking and Finance • Biochemistry • Biostatistics • BSEE • Business (2) • Business & Information Technology • Business Administration / MBA (14) • Business Administration (MIS emphasis) • Business Analysis • Business Information Systems/ Minor in

Business Administration • Business Management (2) • Comparative Literature • Computational linguistics • Computer & Information Science • Computer Engineering (2) • Computer Information Systems • Computer Science (10) • Criminal Justice • Data Processing • DEA & Engineering degree • Economics (2) • Electrical & Information Engineering • Electrical Engineering (3) • Electronic Engineering (2) • Electronics • English Literature • European Studies • Finance • Finance/MIS • Food Science & Management Studies • Geography • Geology • health information • Health Services Research & Policy /

Health Information Mgmt

• History/Political Science • HR mgmt • Information Management • Information Quality • Information Science • Information Systems Management (7) • Information Technology • International Leadership • IT (2) • Liberal Arts • MA in I/O Psychology; MBA in

Finance/Strategy • MA in International Affairs • management • Master in health administration • Master in Information Management • math • Mathematics (5) • medicine • MIS • N/A • None • Nuclear Physics • Project Management • Psychology (2) • Psychology and Sociology • Public Health Administration • Science • signal processing • Social Science • Sociology / Statistical Research • Software Development and

Management • Statistics (2) • Statistics and Info. Tech. • Statistics and Mgmt Sci • Strategic Marketing • technology management • telecommunications • Theater


Page 64 of 74

To what professional organizations do you belong?

Note that since this question allowed respondents to check all options that apply to them, the total number of responses will exceed the overall sample size. The most common professional organizations to which respondents belong is IQ International (shown as IAIDQ) (91) followed by DAMA (30). Many respondents belong to professional organizations that were not included as options.

* The responses written by the respondents were AAQAP, SEI, ASQ (2), ACM (2), IEEE-CS, IRMA, AIPMM ASQ (3), ACM, Aust. Computer Society, BCS, British Computer Society, The Institution of Engineering and Technology (formally the IEE - not IEEE), CAS (2), AAA, SOA, Chartered Quality Institute (UK), CIPS - Canadian Information Processing Society, CWG, ASUG, Dansk IT, Data Quality Pro, Fellow of Irish Computer Society, ICCP, ISACA (2), ICS, ISSA, Software Association of Oregon, SPE (2), TDWI (3), and WITI (2).

Professional Organizations (n=119)

25.2%

11.8%

0.8%

1.7%

1.7%

2.5%

2.5%

4.2%

5.9%

25.2%

76.5%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90%

Other*

None

SHRM

BCS

ICS

ACM

IDMA

ASQ

PMI

DAMA

IAIDQ


Page 65 of 74

What certifications/credentials do you currently hold?

Note that since this question allowed respondents to check all options that apply to them, the total number of responses will exceed the overall sample size. The most common certification or credential that which respondents hold is the PMP (11) followed by the CDMP (5). Many respondents have attained credentials that were not included as options, as indicated below the Table. It should also be noted that many candidates reported not holding any certification or credential (75).

Certifications/Credentials Held (All That Apply) (n=117) Frequency Percent

None 75 64.1% Project Management professional (PMP) 11 9.4% Certified Data Management Professional (CDMP) 5 4.3% Certified Business Intelligence Professional (CBIP) 4 3.4% Certified Business Analysis Professional (CBAP) 2 1.7% Certified Manager of Quality/Organizational Excellence (CMQ/OE)

2 1.7%

Six Sigma Green Belt 2 1.7% Associate Insurance Data Manager (AIDM) 1 0.9% Certified Quality Engineer (CQE) 1 0.9% Certified Public Accountant (CPA) 0 0.0% Certified Information Systems Security Professional (CISSP) 0 0.0% Certified Insurance Data Manager (CIDM) 0 0.0% Certified Quality Improvement Associate (CQIA) 0 0.0% Six Sigma Black Belt 0 0.0% Lean 0 0.0% Other* 22 18.8%

*The “Other” responses written by the respondents were CCP, Certified IBM Information Mgmt Software Professional, Chartered Engineer, Chartered IT Professional, Registered European Engineer CISA (3), CISM (2), CSQE, CPHIMS, FCAS (2), MAAA, FSA, CPCU, FCIBS, PRINCE 2, FLMI (2), ACS, I.S.P. - Information Systems Professional of Canada, ISEB, ITIL (3), MBCS, MIT Certificate in Data Quality, OCP, PAHM, SPHR, IPMA-CP, CWCP, AIS, and TIQM Certified.


Page 66 of 74

Professional Profile

Which functional area best describes the work that you do?

The following tables display the results of the survey responses for the area of the organization in which they perform their work. The largest functional area represented by the respondents is IT/IS( 36.7), followed by Business (non-IT/IS) (30%) and Consultants (20%). Very few respondents (2.5%) reported working in an academic environment.

Functional Area (n=120)

Other*8.3%

Consultant20.0%

Software vendor2.5%

Academia2.5%

Business line or ANY other

non-IT / IS function

30%

Information Technology

(IT) / Information

Systems (IS) function36.7%

* The “Other” responses written by the respondents were: Data Governance, Data Manager, Data Stewart, Center of Excellence, Finance, Information Management, Data Quality Metrics and Improvement, IS Auditor, Statistical/Epidemiological Methodologist, Unemployed; setting myself as consultant.


Page 67 of 74

What role do you currently play in your organization?

The following tables display the results of the survey responses for the organizational role in which respondents reported participating. More than 50% of respondents are in a managerial or supervisory position (36.7% and 14.2%, respectively). Greater than 20% of respondents indicated holding a staff position. The respondents remaining categorized their role as an executive, an owner or a Professor (5.8%, 5.0%, and 4.2%, respectively).

Organizational Role (n=120)

Manager36.7%

Staff 25.8%

Team Lead / Supervisor

14.2%

Other*8.3%

Executive 5.8%

Owner5.0%

Professor4.2%

* The “Other” responses written by the respondents were: Architect, Consultant (2), Data Quality and Security Officer, Data Quality Specialist, Developer, Expert, Global Lead – Data Quality Metrics, Internal Consultant, and IQ Policy Director.


Page 68 of 74

How many years of experience do you have in information/data quality?

Slightly more than 45% of respondents reported tenure of at least ten years in the field, with close to 16% boasting more than twenty years.

Years of IQ/DQ Experience (n=120)

Fewer than 2 years3.3%

2-5 years25.0%

6-10 years25.8%

11-15 years19.2%

16-20 years10.8%

More than 20 years15.8%

Is your current role as an information/data quality practitioner a full-time or part-time role?

It is clear that respondents are equally likely to work as a full-time information/data quality practitioner than those respondents that perform IDQ tasks on a part-time basis within a broader organizational role.

Full-Time vs. Part Time IQ/DQ Focus (n=120)

Part-time role within a broader organizational role ( I have

other duties not related to IQ/DQ)

48%

I am not an IQ/DQ

practitioner3%

Full-time role (IQ/DQ is what I

do full time)49%


Page 69 of 74

How many total employees do you supervise directly or indirectly?

More survey respondents than not have direct or indirect reports. The most common number of direct reports was 1 to 9 (40.8%) followed by 10 to 19 (14.2%). A third of respondents indicated not having any direct reports.

0 or none33.3%

1 to 9 40.8%

10 to 1914.2%

20 to 495.8%

50 to 995.0%

100 or more0.8%

Number of Direct Reports (n=120)

How many information/data quality practitioners do you supervise directly or indirectly?

Table 10 and Figure 10 illustrate the number of employees that are actually IDQ practitioners and report directly to the respondent. Equal numbers of respondents indicated that they either have zero or 1 to 5 direct reports that fall into this category (32.6% and 32.6%, respectively). From the data in this table and Table 9, one can conclude that for respondents who have employees directly reporting to them, not all of them are always necessarily IDQ practitioners.

Number of Direct Reports Who Are IQ/DQ Practitioners (n=120)

0 or none39.2%

1 to 5 39.2%

21 to 503.3%

More than 501.7%

11 to 204.2%

6 to 1012.5%


Page 70 of 74

Organizational Profile

In which department is your position located?

With regard to the specific department to which survey respondent’s position is located, the largest amount of candidates indicated the IT/IS/ITC department (31.9%). There was much variation in responses to this question as every other area attracted less than ten percent of respondents. After IT/IS/ITC, the most common departments among this group were Marketing/Sales, Quality, and Finance (4.9%, 7.6%, and 5.6%, respectively). Many categories were described via the “Other” response option, as indicated in the list below.

Department Location (n=119) Frequency Percent

IT/IS/ITC 46 38.7%

Quality 11 9.2%

Not applicable; I am self-employed 8 6.7%

Finance 8 6.7%

Marketing/Sales 7 5.9%

Manufacturing/Production/Operations/Maintenance/Construction 5 4.2%

Process Management 3 2.5%

Purchasing/Supply Chain Management 2 1.7%

Auditing 1 0.8%

Engineering 1 0.8%

Compliance / Risk 0 0.0%

Legal 0 0.0%

Human Resource 0 0.0%

Safety, Health and Environment 0 0.0%

Facilities/Building 0 0.0%

Other* 27 22.7%

The responses written by the respondents to “Other” categories included Academic Department, Actuarial, BIU, Chief Information Office (2), CMMI Compliance, Consulting, Customer Service, Data Excellence Business Unit, Enterprise Data Governance, Enterprise Information Management, Executive, Exploration and Production, Information Science Education, Information Strategy and Management, Information Systems Consulting, Internal Audit, Legislation Enforcement, Methodology, Operations, Product Management (2), Project Leader Risk Management, Research and Information Services, Risk Management (2), and Sector Strategy.


Page 71 of 74

What part of your organization will your answers to this survey cover?

Greater than half of survey respondents indicated that the entire organization was the source of information for this survey (54.9%). Nearly 30% of respondents reported that only a subset of the organization was referenced.

The entire organization /

company / enterprise

65.8%

A subset of the

organization / company / enterprise

34.2%

Part of Organization Covered by Survey Response (n=120)

How large is your organization?

Nearly 40% of responses indicated ranges between 2,500 and 99,000 employees. Relatively equal numbers of respondents chose the categories 100 to 999 employees or 1,000 to 2,499 employees (11.1% and 11.8%, respectively). The organization size range that attracted the least amounts of respondents was 25-99 employees (3.5%).

1 to 24 employees

8.3% 25 to 99 employees

4.2%

100 to 999 employees

13.3%

1,000 to 2,499

employees 14.2%

2,500 to 9,999

employees 23.3%

10,000 to 99,999

employees 25.0%

100,000 or more 10.0%

Don’t know 1.7%

Organization Size (n=120)


Page 72 of 74

What is the primary industry associated with your organization?

With respect to the primary industry of organizations where respondents work, Financial Services industry was the most popular answer (18.6%) followed by Consulting/Professional Services Industry (12.4%). Other Industries with more than 5% of respondents include Insurance, Energy/Oil & Gas, Healthcare, Telecommunications/Communications, Government: Federal/National and Software / Internet. All other options were chosen less than 4% of the time by respondents.

Organization’s Primary Industry (n=113) Frequency Percent Financial Services 21 18.6% Consulting / Professional Services 14 12.4% Insurance 11 9.7% Energy / Oil & Gas 9 8.0% Healthcare 9 8.0% Telecommunications / Communications 8 7.1% Government: Federal / National 7 6.2% Software / Internet 6 5.3% Education 4 3.5% Manufacturing 4 3.5% Bio-technology / Pharmaceuticals 3 2.7% Government: State / Local 3 2.7% Advertising / Marketing / Public Relations 2 1.8% Hospitality / Travel 2 1.8% Retail / Wholesale Distribution 2 1.8% Utilities 2 1.8% Chemical 1 0.9% Food / Beverage / Agriculture 1 0.9% Logistics / Transportation 1 0.9% Media / Entertainment / Publishing 1 0.9% Non-profit / Trade Association 1 0.9% Other* 1 0.9% Aerospace 0 0.0% Construction / Architecture / Engineering / Real Estate 0 0.0% Law 0 0.0%

The responses written by the respondents were: Computer HW SW Services, Data Processing, High Tech (2), Information Quality, Not for profit Health Research, and Systems Integrator.

Documents

The Job of the Information/Data Quality Professional · The Job of the Information/Data Quality Professional January 2011/May 2017 Page 4 of 74 Job Analysis Panel Members • Walid