Technology Evaluation Centers<br />From Data Quality to Data Governance<br />Jorge García, Research Analyst<br />ComputerW...
Technology Evaluation Centers<br />1. Introduction<br />No, I don’t seeanyproblemwiththe data!<br />Source: www.wolaver.or...
Technology Evaluation Centers<br />1. Introduction (What is Data Quality?)<br />The totality of features and characteristi...
Technology Evaluation Centers<br />1. Introduction (What is Data Quality?)<br />Data Quality Management:<br />Entails the ...
Technology Evaluation Centers<br />1. Introduction (Data Quality features)<br />- Accuracy<br />- Reliability<br />- Compl...
Technology Evaluation Centers<br />1. Introduction (From Data Quality to Data Governance)<br />At what level of Data Quali...
Technology Evaluation Centers<br />1. Introduction (From Data Quality to Data Governance)<br />At what level of Data Quali...
Technology Evaluation Centers<br />1. Introduction (From Data Quality to Data Governance)<br /> Data Management<br />Data ...
Technology Evaluation Centers<br />1. Introduction (What is Data Governance?)<br />- “Data Governance is a system of decis...
 Data cleansing
 Extract, transform and load data (ETL)
 Data warehousing
 Database design</li></ul>Data governance can be applied to these disciplines, but is not included in any of them.<br />
Technology Evaluation Centers<br />1. Introduction (From Data Quality to Data Governance)<br />Data Rules<br />Business Ru...
Technology Evaluation Centers<br />1. Introduction (From Data Quality to Data Governance)<br />Data Rules<br />Business Ru...
Technology Evaluation Centers<br />1. Introduction (From Data Quality to Data Governance)<br />Data stewardship  = Functio...
Resolveconflictsand facilitate data</li></ul>Key Issues:<br /><ul><li> Security
Quality
Sharing</li></li></ul><li>Technology Evaluation Centers<br />2. Some Facts (Top 6 Functionality features)<br />
Technology Evaluation Centers<br />2. Some Facts (Initiatives priorities)<br />Source: Programs or Initiatives, Initiate D...
Technology Evaluation Centers<br />2. Some Facts (Company Size)<br />Source: Company Size, Initiate Data Governance Survey...
Technology Evaluation Centers<br />2. Some Facts (Industry)<br />Source: Industry, Initiate Data Governance Survey Report<...
Technology Evaluation Centers<br />3. DG- Benefits<br /><ul><li>Shortens the compilation of data
 Reduces corporate data redundancy
 Encourages control over valuable data and information assets
 Assists in making more effective use of data assets.
 Transforms and manages data more effectively and securely
 Improves business decisions by the provision of accurate data
 Increases end user trust in data</li></li></ul><li>Technology Evaluation Centers<br />3. DG- Must Have<br />A DG initiati...
 Define all necessary data requirements
 Define cross-functional initiatives
Upcoming SlideShare
Loading in …5
×

From DQ to DG

518 views

Published on

0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total views
518
On SlideShare
0
From Embeds
0
Number of Embeds
16
Actions
Shares
0
Downloads
0
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide
  • “Data Governance is a system of decision rights and accountabilities for information-related processes, executed according to agreed-upon models which describe who can take what actions with what information, and when, under what circumstances, using what methods.” (The Data GovernanceInstitute)“Data governance is a set of processes that ensures that important data assets are formally managed throughout the enterprise. Data governance ensures that data can be trusted and that people can be made accountable for any adverse event that happens because of low data quality..” (Wikipedia)
  • Shortening the compilation of data for business decision-making purposes Corporate reduction in data redundancy Gaining control over valuable data and information assets Assisting in making more effective use of data assets. Transforming and managing data as a valuable organizational asset Improving business decisions by guarantying the provision of accurate data from all original sources Increasing end user trust in data stored within all organization&apos;s data repositories.
  • A DG initiativemust:Define, monitor and manage policies to control how data assets are used Define all necessary data requirements for decisions at all levels: operational, tactical and estrategical. Define cross-functional initiatives in order to promote awareness of how data is used within all areas of the company Define and managetheproperdocumentation for managing data acrosstheenterprise and promoteitsadoptiontoimprovedailyoperations in allareas
  • Call to ActionPlace data governance as a priority initiative.2. Understand data governance as part of the larger scope of knowledge asset management. 3. Understand data governance must be properly planned and chartered. Start with a limited scope initiative.4. Leverage a maturity model for planning manageable phases in data governance.5. Engage the business side of government in data governance.
  • Begin now to develop expertise and governance for managing data, information and knowledge assets.2. Begin to build awareness through communications and marketing initiatives.3. Understand the scope of data governance.4. Ensure that data governance has appropriate representation from business stakeholders, i.e., the real owners of the information. 5. Implement data governance within existing enterprise and data architecture practice.
  • Data Governance role is to enhance data quality management strategies to act as part of the specific business in order to serve the needs of all data consumers.Data governance is a program, a permanent work in progress that needs to be improved progressively. Data governance policies are made by humans, for which has an imperfect element , which has to be reviewed constantly in search for improvent.Data Governance initiatives will need to have 100% support from all levels of leadership (strategic , tactic and operational) in order to improve chances of success.
  • From DQ to DG

    1. 1. Technology Evaluation Centers<br />From Data Quality to Data Governance<br />Jorge García, Research Analyst<br />ComputerWorld Technology Insights, Toronto , 10/2011.<br />www.technologyevaluation.com<br />
    2. 2. Technology Evaluation Centers<br />1. Introduction<br />No, I don’t seeanyproblemwiththe data!<br />Source: www.wolaver.org<br />
    3. 3. Technology Evaluation Centers<br />1. Introduction (What is Data Quality?)<br />The totality of features and characteristics of data that bears on their ability to satisfy a given purpose.<br />
    4. 4. Technology Evaluation Centers<br />1. Introduction (What is Data Quality?)<br />Data Quality Management:<br />Entails the establishment and deployment of roles, responsibilities, and procedures concerning the acquisition, maintenance, dissemination, and disposition of data.<br />
    5. 5. Technology Evaluation Centers<br />1. Introduction (Data Quality features)<br />- Accuracy<br />- Reliability<br />- Completness<br />- Appropriatness<br />- Timeliness<br />- Credibility<br />Ideal features of Data<br />
    6. 6. Technology Evaluation Centers<br />1. Introduction (From Data Quality to Data Governance)<br />At what level of Data Quality is your organization?<br />Incidental<br /> Data Quality<br />Proactive<br />prevention<br />Optimization<br />Limited<br />data analysis<br />Addressing<br />root causes<br />Data profiling,<br />Data cleansing,<br />ETL<br />Continuous<br />DQ process <br />improvements<br />Repairing<br />source data<br />and programs<br />Enterprise-wide<br />DQ methods &<br />techniques<br />
    7. 7. Technology Evaluation Centers<br />1. Introduction (From Data Quality to Data Governance)<br />At what level of Data Quality is your organization?<br />Incidental<br /> Data Quality<br />Proactive<br />prevention<br />Optimization<br />Limited<br />data analysis<br />Addressing<br />root causes<br />More<br />- Management complexity<br />- Cross Functionality<br />- Security concerns<br />
    8. 8. Technology Evaluation Centers<br />1. Introduction (From Data Quality to Data Governance)<br /> Data Management<br />Data Quality<br />Data Quality<br />Business Process<br />Data Governance<br />Policy<br />People<br />Technology<br />Governance comes into play when individual managers find that they cannot – or should not – make independent decisions.The Data Gov. Institute<br />
    9. 9. Technology Evaluation Centers<br />1. Introduction (What is Data Governance?)<br />- “Data Governance is a system of decision rights and accountabilities for information-related processes.” (The Data GovernanceInstitute)<br /><ul><li>“Data governance is a set of processes that ensures that important data assets are formally managed throughout the enterprise.” (Wikipedia)</li></li></ul><li>Technology Evaluation Centers<br />1. Introduction<br />What Data Governance is not:<br /><ul><li> Change management
    10. 10. Data cleansing
    11. 11. Extract, transform and load data (ETL)
    12. 12. Data warehousing
    13. 13. Database design</li></ul>Data governance can be applied to these disciplines, but is not included in any of them.<br />
    14. 14. Technology Evaluation Centers<br />1. Introduction (From Data Quality to Data Governance)<br />Data Rules<br />Business Rules<br />Policy<br />DQ<br />BPM<br />DG<br />
    15. 15. Technology Evaluation Centers<br />1. Introduction (From Data Quality to Data Governance)<br />Data Rules<br />Business Rules<br />Policy<br />DQ<br />BPM<br />DG<br />A data stewardshipstrategy can help data to<br />become a corporateasset<br />
    16. 16. Technology Evaluation Centers<br />1. Introduction (From Data Quality to Data Governance)<br />Data stewardship = Function<br />Role:<br /><ul><li> Data definition and coordination
    17. 17. Resolveconflictsand facilitate data</li></ul>Key Issues:<br /><ul><li> Security
    18. 18. Quality
    19. 19. Sharing</li></li></ul><li>Technology Evaluation Centers<br />2. Some Facts (Top 6 Functionality features)<br />
    20. 20. Technology Evaluation Centers<br />2. Some Facts (Initiatives priorities)<br />Source: Programs or Initiatives, Initiate Data Governance Survey Report<br />
    21. 21. Technology Evaluation Centers<br />2. Some Facts (Company Size)<br />Source: Company Size, Initiate Data Governance Survey Report<br />
    22. 22. Technology Evaluation Centers<br />2. Some Facts (Industry)<br />Source: Industry, Initiate Data Governance Survey Report<br />
    23. 23. Technology Evaluation Centers<br />3. DG- Benefits<br /><ul><li>Shortens the compilation of data
    24. 24. Reduces corporate data redundancy
    25. 25. Encourages control over valuable data and information assets
    26. 26. Assists in making more effective use of data assets.
    27. 27. Transforms and manages data more effectively and securely
    28. 28. Improves business decisions by the provision of accurate data
    29. 29. Increases end user trust in data</li></li></ul><li>Technology Evaluation Centers<br />3. DG- Must Have<br />A DG initiativemust:<br /><ul><li>Define, monitor and manage data assets
    30. 30. Define all necessary data requirements
    31. 31. Define cross-functional initiatives
    32. 32. Define and managetheproperdocumentation</li></li></ul><li>Technology Evaluation Centers<br />4. DG – Challenges<br />Policy Definition, Initiate Data Governance Survey Report<br />
    33. 33. Technology Evaluation Centers<br />4. DG - Challenges<br />Source Board or Council, Initiate Data Governance Survey Report<br />
    34. 34. Technology Evaluation Centers<br />4. DG- Challenges<br />MajorChallenges:<br /><ul><li> Treating a DG as a program, not as a project
    35. 35. Encouraging commitment to keep the program alive and moving
    36. 36. Effective Collaboration
    37. 37. Effective execution</li></li></ul><li>Technology Evaluation Centers<br />4. DG-Failure causes<br /><ul><li> Cultural barriers.
    38. 38. Lack of senior-level sponsorship
    39. 39. Underestimating the amount of work involved
    40. 40. Long on structure and policies, short on action
    41. 41. Lack of business commitment
    42. 42. Lack of understanding that business definitions vary
    43. 43. Trying to move too fast from no-DG to enterprise-wide- DG</li></ul>SearchDataManagement.com<br />
    44. 44. Technology Evaluation Centers<br />5. DG- Tips (Call to Action)<br />Place DG as a priority initiative.<br />2. Consider DG as part of the larger scope of knowledge asset management.<br />3. Understand DG must be properly planned and chartered.<br />4. Leverage a maturity model for planning manageable phases in DG.<br />5. Engage the business side of government in DG.<br />
    45. 45. Technology Evaluation Centers<br />5. DG- Tips (Starting point)<br />Begin now to develop expertise and governance for managing data<br />2. Begin to build awareness through communications<br />3. Understand the scope of data governance<br />4. Ensure that DG has appropriate representation from business stakeholders<br />Implement DG within existing enterprise and data architecture practice.<br />Start with a limited scope initiative.<br />
    46. 46. Technology Evaluation Centers<br />5. DG- Tips (Drivers)<br />Source: Data Governance Part III: Frameworks – Structure for Organizing Complexity, NASCIO<br />
    47. 47. Technology Evaluation Centers<br />5. DG- Tips (Roles and Functions)<br />Business:<br /><ul><li>Specify information needs
    48. 48. Clarifyconstraints and drivers
    49. 49. Participate in Analysis</li></li></ul><li>Technology Evaluation Centers<br />5. DG- Tips (Roles and Functions)<br />Technology:<br /><ul><li>Perform projects:
    50. 50. Adhering to requirements and standards
    51. 51. Efficiently</li></li></ul><li>Technology Evaluation Centers<br />5. DG- Tips (Roles and Functions)<br />Data Governance:<br /><ul><li>Identify patterns
    52. 52. Provideguidelines and standards
    53. 53. Participategovernancerequirements
    54. 54. Control and Monitoring</li></li></ul><li>Technology Evaluation Centers<br />6. Conclusion<br /><ul><li> DG role is to enhance data quality management strategies
    55. 55. DG is a program, a permanent work in progress
    56. 56. DG policies are made by humans, for which has an imperfect element
    57. 57. DG initiatives need to have 100% support to have more chance of success</li></li></ul><li>Technology Evaluation Centers<br />Thankyou!<br />Jorge García, Research Analyst<br />1 514 954 3665 ext. 258<br />jgarcia@tec-centers.com<br />www.technologyevaluation.com<br />

    ×