0
Data Quality Engineering           TITLE            This presentation provides guidance to            organizations consid...
TITLE                   Commonly Asked Questions           PRODUCED BY                                                    ...
TITLE                   Commonly Asked Questions               1) Will I get copies of                       the slides af...
TITLE                   Commonly Asked Questions               1) Will I get copies of                       the slides af...
Get Social With Us!           TITLE                    Live Twitter Feed                                                  ...
4 - datablueprint.com   10/16/2012   ©   Copyright this and previous years by Data Blueprint - all rights reserved!
Meet Your Presenter: Dr. Peter Aiken  • Internationally recognized thought-    leader in the data management    field - 30...
Data Quality                                                                       Engineering             Data Quality En...
Data Quality                                                                       Engineering             Data Quality En...
Data Quality                                                                       Engineering             Data Quality En...
Data Quality                                                                       Engineering             Data Quality En...
TITLE                   Outline                                                                                           ...
TITLE                   Outline           1. Data Management Introduction                                                 ...
TITLE                   Outline           1. Data Management Introduction           2. Data Quality Definitions & Overview...
TITLE                   Outline           1. Data Management Introduction           2. Data Quality Definitions & Overview...
TITLE                   Outline           1. Data Management Introduction           2. Data Quality Definitions & Overview...
TITLE                   Outline           1. Data Management Introduction           2. Data Quality Definitions & Overview...
TITLE                   Outline           1. Data Management Introduction           2. Data Quality Definitions & Overview...
TITLE                   Outline           1. Data Management Introduction           2. Data Quality Definitions & Overview...
TITLE                   Outline           1. Data Management Introduction           2. Data Quality Definitions & Overview...
TITLE                   Outline           1. Data Management Introduction           2. Data Quality Definitions & Overview...
TITLE           The DAMA Guide to the Data Management Body of Knowledge                                                   ...
TITLE           The DAMA Guide to the Data Management Body of Knowledge           Published by DAMA           Internationa...
TITLE           The DAMA Guide to the Data Management Body of Knowledge           Published by DAMA           Internationa...
TITLE           The DAMA Guide to the Data Management Body of Knowledge           Published by DAMA           Internationa...
TITLE           The DAMA Guide to the Data Management Body of Knowledge           Published by DAMA           Internationa...
TITLE           The DAMA Guide to the Data Management Body of Knowledge           Published by DAMA           Internationa...
TITLE           The DAMA Guide to the Data Management Body of Knowledge           Published by DAMA           Internationa...
TITLE           The DAMA Guide to the Data Management Body of Knowledge           PRODUCED BY                             ...
TITLE           The DAMA Guide to the Data Management Body of Knowledge                                                   ...
TITLE           The DAMA Guide to the Data Management Body of Knowledge                                                   ...
TITLE                     What is the CDMP?            • Certified Data Management              Professional            • ...
TITLE                                                                                  Data Management       PRODUCED BY  ...
TITLE                                                                                  Data Management                Data...
TITLE                                                                                  Data Management                    ...
TITLE                                                                                  Data Management                    ...
TITLE                                                                                   Data Management                   ...
TITLE                                                                                   Data Management                   ...
TITLE                                                                                   Data Management                   ...
TITLE                                                                                     Data Management           PRODUC...
TITLE                                    Overview: Data Quality Engineering                                               ...
TITLE                                    Overview: Data Quality Engineering                                               ...
TITLE                   Outline           1. Data Management Introduction           2. Data Quality Definitions & Overview...
TITLE                   Outline           1. Data Management Introduction           2. Data Quality Definitions & Overview...
TITLE                   Definitions                                                                                   from...
TITLE                   Definitions            Data Quality Management                                                    ...
TITLE                   Definitions            Data Quality Management            • Planning, implementation and control a...
TITLE                   Definitions            Data Quality Management            • Planning, implementation and control a...
TITLE                   Definitions            Data Quality Management            • Planning, implementation and control a...
TITLE                   Overview: DQM Concepts and Activities            1)          Data Quality Management Approach     ...
TITLE                   Concepts and Activities                                                                           ...
TITLE                   Concepts and Activities                   Data quality expectations provide the inputs            ...
TITLE                   Concepts and Activities                   Data quality expectations provide the inputs            ...
TITLE                   Outline           1. Data Management Introduction           2. Data Quality Definitions & Overview...
TITLE                   Outline           1. Data Management Introduction           2. Data Quality Definitions & Overview...
TITLE                   The DQM Cycle            The general approach to DQM            is a version of the Deming        ...
TITLE                   The DQM Cycle            The general approach to DQM            is a version of the Deming        ...
TITLE                   The DQM Cycle: (1) Plan            Plan for the assessment of            the current state and    ...
TITLE                   The DQM Cycle: (2) Deploy            Deploy processes for            measuring and improving      ...
TITLE                   The DQM Cycle: (3) Monitor            Monitor the quality of data as            measured against t...
TITLE                   The DQM Cycle: (4) Act            Act to resolve any              identified issues to            ...
TITLE                   Outline           1. Data Management Introduction           2. Data Quality Definitions & Overview...
TITLE                   Outline           1. Data Management Introduction           2. Data Quality Definitions & Overview...
TITLE                   Develop and Promote DQ Awareness                                                                  ...
TITLE                   Develop and Promote DQ Awareness            •       Promoting data quality awareness is           ...
TITLE                   Develop and Promote DQ Awareness            •       Promoting data quality awareness is           ...
TITLE                   Develop and Promote DQ Awareness            •       Promoting data quality awareness is           ...
TITLE                   Develop and Promote DQ Awareness            •       Promoting data quality awareness is           ...
TITLE                   Polling Question #1            Which is not a step to promote data quality            awareness?  ...
TITLE                   Develop and Promote DQ Awareness: Steps                                                           ...
TITLE                   Develop and Promote DQ Awareness: Steps            1) Training on the core               concepts ...
TITLE                   Develop and Promote DQ Awareness: Steps            1) Training on the core               concepts ...
TITLE                   Develop and Promote DQ Awareness: Steps            1) Training on the core               concepts ...
TITLE                   Define DQ Requirements            • Data quality must be understood within the context of ‘fitness...
TITLE                   Data Quality Dimensions                                                                           ...
TITLE                   Profile, Analyze and Assess DQ            Data assessment using 2 different approaches:           ...
TITLE                   Define DQ Metrics            • Metrics development occurs as part of the              strategy/des...
TITLE                   Test and Validate DQ Requirements            • Data profiling tools              analyze data to f...
TITLE                   Set and Evaluate DQ Service Levels            • Data quality inspection and monitoring are used to...
TITLE                   Measure and Monitor DQ            • DQM procedures depend on available data              quality m...
Clean & Correct                Manage DQ Issues                                                                           ...
Manage DQ Issues: Example           TITLE             Data quality incident tracking focuses on training staff to recogniz...
Design and Implement                                                                              Monitor Operational     ...
TITLE                   Outline           1. Data Management Introduction           2. Data Quality Definitions & Overview...
TITLE                   Outline           1. Data Management Introduction           2. Data Quality Definitions & Overview...
TITLE                   Example: Data Quality Interview Session Summary              • During mid-February, the Data Gover...
TITLE                   Which Activities Support Quality Data?              • Data quality best practices depend on both  ...
TITLE                   Quality Dimensions            Practice-oriented causes            • Stem from a failure to rigor w...
TITLE                   Practice-Oriented Activities             • Affect the Data Value Quality and Data Representation  ...
TITLE                   Structure-Oriented Activities             • Affect the Data Model Quality and Data Architecture Qu...
Data-Ed Online: Engineering Solutions to Data Quality Challenges
Data-Ed Online: Engineering Solutions to Data Quality Challenges
Data-Ed Online: Engineering Solutions to Data Quality Challenges
Data-Ed Online: Engineering Solutions to Data Quality Challenges
Data-Ed Online: Engineering Solutions to Data Quality Challenges
Data-Ed Online: Engineering Solutions to Data Quality Challenges
Data-Ed Online: Engineering Solutions to Data Quality Challenges
Data-Ed Online: Engineering Solutions to Data Quality Challenges
Data-Ed Online: Engineering Solutions to Data Quality Challenges
Data-Ed Online: Engineering Solutions to Data Quality Challenges
Data-Ed Online: Engineering Solutions to Data Quality Challenges
Data-Ed Online: Engineering Solutions to Data Quality Challenges
Data-Ed Online: Engineering Solutions to Data Quality Challenges
Data-Ed Online: Engineering Solutions to Data Quality Challenges
Data-Ed Online: Engineering Solutions to Data Quality Challenges
Data-Ed Online: Engineering Solutions to Data Quality Challenges
Data-Ed Online: Engineering Solutions to Data Quality Challenges
Data-Ed Online: Engineering Solutions to Data Quality Challenges
Data-Ed Online: Engineering Solutions to Data Quality Challenges
Data-Ed Online: Engineering Solutions to Data Quality Challenges
Data-Ed Online: Engineering Solutions to Data Quality Challenges
Data-Ed Online: Engineering Solutions to Data Quality Challenges
Data-Ed Online: Engineering Solutions to Data Quality Challenges
Data-Ed Online: Engineering Solutions to Data Quality Challenges
Data-Ed Online: Engineering Solutions to Data Quality Challenges
Data-Ed Online: Engineering Solutions to Data Quality Challenges
Data-Ed Online: Engineering Solutions to Data Quality Challenges
Data-Ed Online: Engineering Solutions to Data Quality Challenges
Data-Ed Online: Engineering Solutions to Data Quality Challenges
Data-Ed Online: Engineering Solutions to Data Quality Challenges
Data-Ed Online: Engineering Solutions to Data Quality Challenges
Data-Ed Online: Engineering Solutions to Data Quality Challenges
Data-Ed Online: Engineering Solutions to Data Quality Challenges
Data-Ed Online: Engineering Solutions to Data Quality Challenges
Data-Ed Online: Engineering Solutions to Data Quality Challenges
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Data-Ed Online: Engineering Solutions to Data Quality Challenges

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This webinar originally aired on Tuesday, October 9th, 2012. It is part of Data Blueprint's ongoing webinar series on data management with Dr. Aiken.

Sign up for future sessions at http://www.datablueprint.com/webinar-schedule.

Abstract:
This presentation provides guidance to organizations considering or preparing for data quality initiatives. We will illustrate how organizations with chronic business challenges often can trace the root of the problem to poor data quality. Showing how data quality can be engineered provides a useful framework in which to develop an organizational approach. This in turn will allow organizations to more quickly identify data problems caused by structural issues versus practice-oriented defects. Participants will also learn the importance of practicing data quality engineering quantification.

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  • Transcript of "Data-Ed Online: Engineering Solutions to Data Quality Challenges"

    1. 1. Data Quality Engineering TITLE This presentation provides guidance to organizations considering data quality initiatives or preparing for data quality initiatives. This talk will illustrate how organizations with chronic business challenges often can trace the root of the problem to poor data quality. Showing how data quality can be engineered provides a useful framework in which to develop an organizational approach. This in turn will allow organizations to more quickly identify data problems caused by structural issues versus practice-oriented defects. Participants will also Starting learn the importance of practicing data quality point for new system Metadata Creation • Define Data Architecture • Define Data Model Structures Metadata Refinement • Correct Structural Defects • Update Implementation engineering quantification. development architecture data architecture refinements Metadata Structuring Data Refinement • Implement Data Model Views • Correct Data Value Defects • Populate Data Model Views corrected • Re-store Data Values data data Date: October 9, 2012 architecture and Metadata & data models Data Storage data performance metadata Data Creation facts & Data Assessment • Create Data meanings • Assess Data Values Time: 2:00 PM ET • Verify Data Values shared data updated data • Assess Metadata Starting point for existing Presented by: Dr. Peter Aiken Data Utilization Data Manipulation systems • Inspect Data • Manipulate Data • Present Data • Updata Data PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 110/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    2. 2. TITLE Commonly Asked Questions PRODUCED BY CLASSIFICATION DATE SLIDE EDUCATION 209/10/12 DATACopyright this and previous years by Data W. BROAD reserved! © BLUEPRINT 10124-C Blueprint - all rights ST, GLEN ALLEN, VA 23060
    3. 3. TITLE Commonly Asked Questions 1) Will I get copies of the slides after the event? PRODUCED BY CLASSIFICATION DATE SLIDE EDUCATION 209/10/12 DATACopyright this and previous years by Data W. BROAD reserved! © BLUEPRINT 10124-C Blueprint - all rights ST, GLEN ALLEN, VA 23060
    4. 4. TITLE Commonly Asked Questions 1) Will I get copies of the slides after the event? 2) Is this being recorded so I can view it afterwards? PRODUCED BY CLASSIFICATION DATE SLIDE EDUCATION 209/10/12 DATACopyright this and previous years by Data W. BROAD reserved! © BLUEPRINT 10124-C Blueprint - all rights ST, GLEN ALLEN, VA 23060
    5. 5. Get Social With Us! TITLE Live Twitter Feed Like Us on Facebook Join the Group Join the conversation! www.facebook.com/ Data Management & Follow us: datablueprint Business Intelligence @datablueprint Post questions and Ask questions, gain insights comments and collaborate with fellow @paiken Find industry news, insightful data management Ask questions and submit content professionals your comments: #dataed and event updates. PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 310/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    6. 6. 4 - datablueprint.com 10/16/2012 © Copyright this and previous years by Data Blueprint - all rights reserved!
    7. 7. Meet Your Presenter: Dr. Peter Aiken • Internationally recognized thought- leader in the data management field - 30 years of experience – Recipient of multiple international awards – Founder, Data Blueprint (http://datablueprint.com) • 7 books and dozens of articles • Experienced w/ 500+ data management practices in 20 countries • Multi-year immersions with organizations as diverse as the US DoD, Deutsche Bank, Nokia, Wells Fargo, the Commonwealth of Virginia and Walmart4 - datablueprint.com 10/16/2012 © Copyright this and previous years by Data Blueprint - all rights reserved!
    8. 8. Data Quality Engineering Data Quality EngineeringDATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12
    9. 9. Data Quality Engineering Data Quality EngineeringDATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12
    10. 10. Data Quality Engineering Data Quality EngineeringDATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12
    11. 11. Data Quality Engineering Data Quality EngineeringDATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12
    12. 12. TITLE Outline Tweeting now: #dataed PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 610/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    13. 13. TITLE Outline 1. Data Management Introduction Tweeting now: #dataed PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 610/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    14. 14. TITLE Outline 1. Data Management Introduction 2. Data Quality Definitions & Overview Tweeting now: #dataed PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 610/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    15. 15. TITLE Outline 1. Data Management Introduction 2. Data Quality Definitions & Overview 3. DQM Cycle Tweeting now: #dataed PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 610/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    16. 16. TITLE Outline 1. Data Management Introduction 2. Data Quality Definitions & Overview 3. DQM Cycle 4. DQ Awareness & Requirements Tweeting now: #dataed PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 610/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    17. 17. TITLE Outline 1. Data Management Introduction 2. Data Quality Definitions & Overview 3. DQM Cycle 4. DQ Awareness & Requirements 5. DQ Dimensions Tweeting now: #dataed PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 610/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    18. 18. TITLE Outline 1. Data Management Introduction 2. Data Quality Definitions & Overview 3. DQM Cycle 4. DQ Awareness & Requirements 5. DQ Dimensions 6. Data Quality Tools Tweeting now: #dataed PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 610/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    19. 19. TITLE Outline 1. Data Management Introduction 2. Data Quality Definitions & Overview 3. DQM Cycle 4. DQ Awareness & Requirements 5. DQ Dimensions 6. Data Quality Tools 7. Guiding Principles Tweeting now: #dataed PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 610/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    20. 20. TITLE Outline 1. Data Management Introduction 2. Data Quality Definitions & Overview 3. DQM Cycle 4. DQ Awareness & Requirements 5. DQ Dimensions 6. Data Quality Tools 7. Guiding Principles Tweeting now: 8. References and Q&A #dataed PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 610/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    21. 21. TITLE Outline 1. Data Management Introduction 2. Data Quality Definitions & Overview 3. DQM Cycle 4. DQ Awareness & Requirements 5. DQ Dimensions 6. Data Quality Tools 7. Guiding Principles Tweeting now: 8. References and Q&A #dataed PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 610/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    22. 22. TITLE The DAMA Guide to the Data Management Body of Knowledge Data Management Functions PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 710/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    23. 23. TITLE The DAMA Guide to the Data Management Body of Knowledge Published by DAMA International Data Management Functions PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 710/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    24. 24. TITLE The DAMA Guide to the Data Management Body of Knowledge Published by DAMA International • The professional association for Data Managers (40 chapters worldwide) Data Management Functions PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 710/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    25. 25. TITLE The DAMA Guide to the Data Management Body of Knowledge Published by DAMA International • The professional association for Data Managers (40 chapters worldwide) DMBoK organized around Data Management Functions PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 710/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    26. 26. TITLE The DAMA Guide to the Data Management Body of Knowledge Published by DAMA International • The professional association for Data Managers (40 chapters worldwide) DMBoK organized around • Primary data management functions focused around data delivery to the organization Data Management Functions PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 710/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    27. 27. TITLE The DAMA Guide to the Data Management Body of Knowledge Published by DAMA International • The professional association for Data Managers (40 chapters worldwide) DMBoK organized around • Primary data management functions focused around data delivery to the organization • Organized around several environmental elements Data Management Functions PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 710/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    28. 28. TITLE The DAMA Guide to the Data Management Body of Knowledge Published by DAMA International • The professional association for Data Managers (40 chapters worldwide) DMBoK organized around • Primary data management functions focused around data delivery to the organization • Organized around several environmental elements Data Management Functions PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 710/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    29. 29. TITLE The DAMA Guide to the Data Management Body of Knowledge PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 810/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    30. 30. TITLE The DAMA Guide to the Data Management Body of Knowledge Environmental Elements PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 810/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    31. 31. TITLE The DAMA Guide to the Data Management Body of Knowledge Amazon: http:// www.amazon.com/ DAMA-Guide- Management- Knowledge-DAMA- DMBOK/dp/ 0977140083 Or enter the terms "dama dm bok" at the Amazon search engine Environmental Elements PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 810/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    32. 32. TITLE What is the CDMP? • Certified Data Management Professional • DAMA International and ICCP • Membership in a distinct group made up of your fellow professionals • Recognition for your specialized knowledge in a choice of 17 specialty areas • Series of 3 exams • For more information, please visit: – http://www.dama.org/i4a/pages/ index.cfm?pageid=3399 – http://iccp.org/certification/ designations/cdmp #dataed PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 5/15/2012 9© Copyright this and previous years by Data Blueprint - all rights reserved!
    33. 33. TITLE Data Management PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 101/26/201010/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    34. 34. TITLE Data Management Data Program Coordination Organizational Data Integration Data Stewardship Data Development Data Support Operations PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 111/26/201010/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    35. 35. TITLE Data Management Manage data coherently. Data Program Coordination Organizational Data Integration Data Stewardship Data Development Data Support Operations PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 111/26/201010/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    36. 36. TITLE Data Management Manage data coherently. Data Program Coordination Share data across boundaries. Organizational Data Integration Data Stewardship Data Development Data Support Operations PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 111/26/201010/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    37. 37. TITLE Data Management Manage data coherently. Data Program Coordination Share data across boundaries. Organizational Data Integration Data Stewardship Data Development Assign responsibilities for data. Data Support Operations PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 111/26/201010/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    38. 38. TITLE Data Management Manage data coherently. Data Program Coordination Share data across boundaries. Organizational Data Integration Data Stewardship Data Development Assign responsibilities for data. Engineer data delivery systems. Data Support Operations PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 111/26/201010/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    39. 39. TITLE Data Management Manage data coherently. Data Program Coordination Share data across boundaries. Organizational Data Integration Data Stewardship Data Development Assign responsibilities for data. Engineer data delivery systems. Data Support Operations Maintain data availability. PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 111/26/201010/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    40. 40. TITLE Data Management PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 1210/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    41. 41. TITLE Overview: Data Quality Engineering from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 131/26/201010/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    42. 42. TITLE Overview: Data Quality Engineering from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 141/26/201010/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    43. 43. TITLE Outline 1. Data Management Introduction 2. Data Quality Definitions & Overview 3. DQM Cycle 4. DQ Awareness & Requirements 5. DQ Dimensions 6. Data Quality Tools 7. Guiding Principles Tweeting now: 8. References and Q&A #dataed PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 1510/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    44. 44. TITLE Outline 1. Data Management Introduction 2. Data Quality Definitions & Overview 3. DQM Cycle 4. DQ Awareness & Requirements 5. DQ Dimensions 6. Data Quality Tools 7. Guiding Principles Tweeting now: 8. References and Q&A #dataed PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 1510/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    45. 45. TITLE Definitions from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/2012 10/09/12 1610/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    46. 46. TITLE Definitions Data Quality Management from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/2012 10/09/12 1610/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    47. 47. TITLE Definitions Data Quality Management • Planning, implementation and control activities that apply quality management techniques to measure, assess, improve, and ensure the fitness of data for use from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/2012 10/09/12 1610/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    48. 48. TITLE Definitions Data Quality Management • Planning, implementation and control activities that apply quality management techniques to measure, assess, improve, and ensure the fitness of data for use • Entails the establishment and deployment of roles, responsibilities concerning the acquisition, maintenance, dissemination, and disposition of data.” http://www2.sas.com/proceedings/sugi29/098-29.pdf from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/2012 10/09/12 1610/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    49. 49. TITLE Definitions Data Quality Management • Planning, implementation and control activities that apply quality management techniques to measure, assess, improve, and ensure the fitness of data for use • Entails the establishment and deployment of roles, responsibilities concerning the acquisition, maintenance, dissemination, and disposition of data.” http://www2.sas.com/proceedings/sugi29/098-29.pdf • Critical support process in organizational change management • Continuous process for defining the parameters for specifying acceptable levels of data quality to meet business needs and for ensuring that data quality meets these levels Data Quality • Synonymous with information quality, since poor data quality results in inaccurate information and poor business performance from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/2012 10/09/12 1610/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    50. 50. TITLE Overview: DQM Concepts and Activities 1) Data Quality Management Approach 2) Develop and promote data quality awareness 3) Define data quality requirements 4) Profile, analyze and assess data quality 5) Define data quality metrics 6) Define data quality business rules 7) Test and validate data quality requirements 8) Set and evaluate data quality service levels 9) Measure and monitor data quality 10) Manage data quality issues 11) Clean and correct data quality defects 12) Design and implement operational DQM procedures 13) Monitor operational DQM procedures and performance from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 1710/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    51. 51. TITLE Concepts and Activities from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 1810/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    52. 52. TITLE Concepts and Activities Data quality expectations provide the inputs necessary to define the data quality framework: – Requirements – Inspection policies – Measures, and monitors that reflect changes in data quality and performance from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 1810/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    53. 53. TITLE Concepts and Activities Data quality expectations provide the inputs necessary to define the data quality framework: – Requirements – Inspection policies – Measures, and monitors that reflect changes in data quality and performance • The data quality framework requirements reflect 3 aspects of business data expectations 1) A manner to record the expectation in business rules 2) A way to measure the quality of data within that dimension 3) An acceptability threshold from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 1810/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    54. 54. TITLE Outline 1. Data Management Introduction 2. Data Quality Definitions & Overview 3. DQM Cycle 4. DQ Awareness & Requirements 5. DQ Dimensions 6. Data Quality Tools 7. Guiding Principles Tweeting now: 8. References and Q&A #dataed PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 1910/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    55. 55. TITLE Outline 1. Data Management Introduction 2. Data Quality Definitions & Overview 3. DQM Cycle 4. DQ Awareness & Requirements 5. DQ Dimensions 6. Data Quality Tools 7. Guiding Principles Tweeting now: 8. References and Q&A #dataed PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 1910/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    56. 56. TITLE The DQM Cycle The general approach to DQM is a version of the Deming cycle. Deming proposes a problem–solving model known as “plan-do-study-act” or “plan-do-check-act” The cycle begins by: 1) Identifying data issues that are critical to the achievement of business objectives 2) Defining business requirements for data quality 3) Identifying key data quality dimensions 4) Defining business rules critical to ensuring high quality data from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 2010/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    57. 57. TITLE The DQM Cycle The general approach to DQM is a version of the Deming cycle. Deming proposes a problem–solving model known as “plan-do-study-act” or “plan-do-check-act” The cycle begins by: 1) Identifying data issues that are critical to the achievement of business objectives 2) Defining business requirements for data quality 3) Identifying key data quality dimensions 4) Defining business rules critical to ensuring high quality data from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 2010/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    58. 58. TITLE The DQM Cycle: (1) Plan Plan for the assessment of the current state and identification of key metrics for measuring quality • The data quality team assesses the scope of known issues • This involves: – Determining cost and impact – Evaluating alternatives for addressing them from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 2110/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    59. 59. TITLE The DQM Cycle: (2) Deploy Deploy processes for measuring and improving the quality of data: • Data profiling • Institute inspections and monitors to identify data issues when they occur • Fix flawed processes that are the root cause of data errors or correct errors downstream • When it is not possible to correct errors at their source, correct them at their earliest point in the data flow from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 2210/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    60. 60. TITLE The DQM Cycle: (3) Monitor Monitor the quality of data as measured against the defined business rules • If data quality meets defined thresholds for acceptability, the processes are in control and the level of data quality meets the business requirements • If data quality falls below acceptability thresholds, notify data stewards so they can take action during the next stage from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 2310/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    61. 61. TITLE The DQM Cycle: (4) Act Act to resolve any identified issues to improve data quality and better meet business expectations • New cycles begin as new data sets come under investigation or as new data quality requirements are identified for existing data sets from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 2410/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    62. 62. TITLE Outline 1. Data Management Introduction 2. Data Quality Definitions & Overview 3. DQM Cycle 4. DQ Awareness & Requirements 5. DQ Dimensions 6. Data Quality Tools 7. Guiding Principles Tweeting now: 8. References and Q&A #dataed PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 2510/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    63. 63. TITLE Outline 1. Data Management Introduction 2. Data Quality Definitions & Overview 3. DQM Cycle 4. DQ Awareness & Requirements 5. DQ Dimensions 6. Data Quality Tools 7. Guiding Principles Tweeting now: 8. References and Q&A #dataed PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 2510/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    64. 64. TITLE Develop and Promote DQ Awareness from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 2610/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    65. 65. TITLE Develop and Promote DQ Awareness • Promoting data quality awareness is essential to ensure buy-in of necessary stakeholders in the organization from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 2610/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    66. 66. TITLE Develop and Promote DQ Awareness • Promoting data quality awareness is essential to ensure buy-in of necessary stakeholders in the organization • Ensure that the right people in the organization are aware of the existence of data quality issues from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 2610/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    67. 67. TITLE Develop and Promote DQ Awareness • Promoting data quality awareness is essential to ensure buy-in of necessary stakeholders in the organization • Ensure that the right people in the organization are aware of the existence of data quality issues • Awareness increases the chance of success of any DQM program from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 2610/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    68. 68. TITLE Develop and Promote DQ Awareness • Promoting data quality awareness is essential to ensure buy-in of necessary stakeholders in the organization • Ensure that the right people in the organization are aware of the existence of data quality issues • Awareness increases the chance of success of any DQM program • Awareness includes: – Relating material impacts to data issues – Ensuring systematic approaches to regulators – Oversight of the quality of organizational data – Socializing the concept that data quality problems cannot be solely addressed by technology solutions from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 2610/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    69. 69. TITLE Polling Question #1 Which is not a step to promote data quality awareness? a) Training on the core concepts of data quality b) Establish data governance framework for data quality c) Create a data architecture map PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 2710/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    70. 70. TITLE Develop and Promote DQ Awareness: Steps from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 2810/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    71. 71. TITLE Develop and Promote DQ Awareness: Steps 1) Training on the core concepts of data quality from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 2810/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    72. 72. TITLE Develop and Promote DQ Awareness: Steps 1) Training on the core concepts of data quality 2) Establish data governance framework for data quality from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 2810/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    73. 73. TITLE Develop and Promote DQ Awareness: Steps 1) Training on the core concepts of data quality 2) Establish data governance framework for data quality 3) Create a data quality oversight board that has a reporting hierarchy associated with the different data governance roles from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 2810/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    74. 74. TITLE Define DQ Requirements • Data quality must be understood within the context of ‘fitness for use’ • Data quality requirements are often hidden within defined business policies • Incremental detailed review and iterative refinement of business policies helps to identify those information requirements which become data quality rules • Steps for incremental detailed review: – Identify key data components associated with business policies – Determine how identified data assertions affect the business – Evaluate how data errors are categorized within a set of data quality dimensions – Specify the business rules that measure the occurrence of data errors – Provide a means for implementing measurement processes that assess conformance to those business rules from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 2910/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    75. 75. TITLE Data Quality Dimensions from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 3010/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    76. 76. TITLE Profile, Analyze and Assess DQ Data assessment using 2 different approaches: 1) Bottom-up 2) Top-down Bottom-up assessment: • Inspection and evaluation of the data sets • Highlight potential issues based on the results of automated processes Top-down assessment: • Engage business users to document their business processes and the corresponding critical data dependencies • Understand how their processes consume data and which data elements are critical to the success of the business application from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 3110/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    77. 77. TITLE Define DQ Metrics • Metrics development occurs as part of the strategy/design/plan step • Process for defining data quality metrics: 1) Select one of the identified critical business impacts 2) Evaluate the dependent data elements, create and update processes associate with that business impact 3) List any associated data requirements 4) Specify the associated dimension of data quality and one or more business rules to use to determine conformance of the data to expectations 5) Describe the process for measuring conformance 6) Specify an acceptability threshold from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 3210/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    78. 78. TITLE Test and Validate DQ Requirements • Data profiling tools analyze data to find potential anomalies • Use the same tools for rule validation • Rules discovered or defined during the data quality assessment phase are referenced in measuring conformance as part of the operational process from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 3310/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    79. 79. TITLE Set and Evaluate DQ Service Levels • Data quality inspection and monitoring are used to measure and monitor compliance with defined data quality rules • Data quality SLAs specify the organization’s expectations for response and remediation • Operational data quality control defined in data quality SLAs includes: – Data elements covered by the agreement – Business impacts associated with data flaws – Data quality dimensions associated with each data element – Quality expectations for each data element of the indentified dimensions in each application for system in the value chain – Methods for measuring against those expectations – (…) from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 3410/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    80. 80. TITLE Measure and Monitor DQ • DQM procedures depend on available data quality measuring and monitoring services • 2 contexts for control/measurement of conformance to data quality business rules exist: – In-stream: collect in-stream measurements while creating data – In batch: perform batch activities on collections of data instances assembled in a data set • Apply measurements at 3 levels of granularity: – Data element value – Data instance or record – Data set from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 3510/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    81. 81. Clean & Correct Manage DQ Issues DQ Defects • Supporting the enforcement of Perform data correction the data quality SLA requires a mechanism for reporting and in 3 ways: tracking data quality incidents 1) Automated correction and activities for researching 2) Manual directed correction and resolving those incidents 3) Manual correction • A data quality incident reporting system can provide this capability • It can log the evaluation, initial diagnosis, and actions associated with data quality events from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 3610/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    82. 82. Manage DQ Issues: Example TITLE Data quality incident tracking focuses on training staff to recognize when data issues appear and how they are to be classified, logged and tracked according to the data quality SLA from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 3710/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    83. 83. Design and Implement Monitor Operational Operational DQM DQM Procedures and Procedures Performances 1) Inspection and monitoring 1) Accountability is critical 2) Diagnosis and evaluation to governance of remediation protocols overseeing alternatives data quality control 3) Resolve issues 2) All issues must be 4) Reporting assigned 3) The tracking process should specify and document the ultimate issue accountability from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 3810/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    84. 84. TITLE Outline 1. Data Management Introduction 2. Data Quality Definitions & Overview 3. DQM Cycle 4. DQ Awareness & Requirements 5. DQ Dimensions 6. Data Quality Tools 7. Guiding Principles Tweeting now: 8. References and Q&A #dataed PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 3910/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    85. 85. TITLE Outline 1. Data Management Introduction 2. Data Quality Definitions & Overview 3. DQM Cycle 4. DQ Awareness & Requirements 5. DQ Dimensions 6. Data Quality Tools 7. Guiding Principles Tweeting now: 8. References and Q&A #dataed PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 3910/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    86. 86. TITLE Example: Data Quality Interview Session Summary • During mid-February, the Data Governance Team and Data Blueprint conducted ten qualitative interview sessions with groups of individuals who interact with data on regular basis • A series of patterns emerged as participants shared stories about the impact of poor data quality on the client, its products, and its customers • These patterns highlight gaps in best practices for ensuring data quality, i.e. the extent to which data is “fit for use” • Our preliminary analysis evaluated these stories against attributes of four data quality dimensions • At this early stage of the post-interview process, we are seeking confirmation of our assumptions and method PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 4010/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    87. 87. TITLE Which Activities Support Quality Data? • Data quality best practices depend on both – Practice-oriented activities – Structure-oriented activities Quality Practice-oriented Data Structure-oriented activities focus on activities focus on the capture and the data manipulation of data implementation PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 4110/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    88. 88. TITLE Quality Dimensions Practice-oriented causes • Stem from a failure to rigor when capturing and manipulating data such as: – Edit masking – Range checking of input data – CRC-checking of transmitted data Structure-oriented causes • Occur because of data and metadata that has been arranged imperfectly. For example: – When the data is in the system but we just cant access it; – When a correct data value is provided as the wrong response to a query; or – When data is not provided because it is unavailable or inaccessible to the customer • Developer focus within system boundaries instead of within organization boundaries PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 4210/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    89. 89. TITLE Practice-Oriented Activities • Affect the Data Value Quality and Data Representation Quality • Examples of improper practice-oriented activities: – Allowing imprecise or incorrect data to be collected when requirements specify otherwise – Presenting data out of sequence • Typically diagnosed in bottom-up manner: find and fix the resulting problem • Addressed by imposing more rigorous data-handling governance Practice-oriented activities Quality of Quality of Data Values Data Representatio n PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 4310/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
    90. 90. TITLE Structure-Oriented Activities • Affect the Data Model Quality and Data Architecture Quality • Examples of improper structure-oriented activities: – Providing a correct response but incomplete data to a query because the user did not comprehend the system data structure – Costly maintenance of inconsistent data used by redundant systems • Typically diagnosed in top-down manner: root cause fixes • Addressed through fundamental data structure governance Structure-oriented activities Quality of Quality of Data Models Data Architecture PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 10/09/12 4410/04/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
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