example for creating a DQ program agreement, once Data Quality Initiation Phase completion report is reviewed and signed off by the stakeholders, and we have a clarity on the scope of DQ program, which is going to be funded.">
Institute for Building Intelligent and Performing Enterprises
Building Intelligent and Performing Enterprises
data quality practice kit
 
Login or Register  
 
Join Professional Network of Business Intelligence and Performance Management
BiPM Practice Tool Listing Page
Data Quality Program Proposal and Agreement
This work-tool gives you a template, guidelines and text example for creating a DQ program agreement, once Data Quality Initiation Phase completion report is reviewed and signed off by the stakeholders, and we have a clarity on the scope of DQ program, which is going to be funded.
This BiPM Practice Tool is linked to:  Data Quality,
This page is part of Data Quality Practice and Tool-Kit Package package, which is a paid service. To supplement the paid products, BiPMinstitute.com provides over 1000 pages of premium content as a Free service.
Our products provide a level of detail, that you need for 'on the ground and hands-on' implementations.
  • If you have already bought this service, please login to access this service.
  • If you have not bought this service, please refer Data Quality Practice and Tool-Kit Package to review and buy our offering.

    • ABSTRACT

    Header Information

    • Tool-Code: DQ01WT23
    • Product-Code: BIPM-DQPACK02
    • Help File (excluding FAQs and Tips): 10 pages
    • Relevant FAQs- 8
    • Relevant TIPs- 6

    Table of Contents

    • EXECUTIVE SUMMARY
      • Back-Ground
      • DQ Program Objectives
      • Program Scope
      • Program Deliverables
      • Program Timelines
      • Program Funding and Resources
      • Business Benefits and Measures
      • Program Assumptions
    • BACK-GROUND
    • Scope of Data Quality Program
    • Resource and Funding Estimation
    • Timelines and Responsibilities
    • DQ program initiation phase organization
    • Communication Framework
    • Risk Management Plan
    • Assumptions
    • Risks and Mitigation
    • Next Steps
    • APPENDIX

    Overall Usage Guide

    Purpose of this document

    This work-tool gives you a template, guidelines and text example for creating a DQ program agreement, once Data Quality Initiation Phase completion report is reviewed and signed off by the stakeholders, and we have a clarity on the scope of DQ program, which is going to be funded.

    Relevant FAQ:

    • When we submitted out DQ initiation phase completion report, we did not add any buffer in the estimates. However, as we are creating our project plans, we feel that we should place some safety factor. If we do this, it will create a credibility issue with the stakeholders. What should we do?
    • Out of 13 projects within the data quality program, 7 are being done as part of large programs by different IT units. Do we need to track them, as it seems that there is duplication in managing these projects?
    • Is there a minimum or maximum number of projects, which can be in a data quality program?
    • If there are multiple initiatives in a data quality program and each initiative can have a different owner, why do we need a data quality program? Why can't we simply have a tracking sheet of independent initiatives?
    • Can we have multiple data quality programs running at the same time?
    • We started a big data quality program. There were 7 projects, within that program. Some-how the three projects, never took-off and the stakeholders have chosen to post-pone them to a later stage. Should we close the DQ program or keep it open till these three projects are also completed?
    • Should tracking of change controls (and not projects), be part of Data Quality program?
    • In our Data quality initiation phase completion report, we came out with recommendation for 10 initiatives to address more than 30 critical data quality issues. However, we got the OK for only 3 of them. The DQ team has lost its motivation. What should we do?

    Relevant TIPs:

    • Data Quality is for business and business is not for data quality.
    • Not everything related to Data Quality issues need to be resolved through a data quality program
    • Don’t create hype on data quality program.
    • If data quality agenda is a treadmill, we should set it up on 'Cardio' program.
    • Data Quality Program should be aligned with larger data management initiatives.
    • Data quality Initiatives should piggy-back on larger funded projects.
    Tags    -     See all
     
    Back