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Principles and Rules Listing Page

Engage the Vendors in Data Quality Program

A Vendor of your system can be a good source to provide the possible problems in terms of Data Quality, related to his system.
 
This page of 'Principles and Rules' is linked to:  Data Quality,

With adequate expectation setting and taking vendors into confidence, a Vendor can bring out the issues on Data Quality, with following advantages:

  • having a very high technical understanding of the system.
  • Having a clarity of the road-map of the underlying platforms. For example if a Vendor is a strategic partner to Oracle, he will be aware of the system gaps (which are resulting in data quality issues), which are planned to be fixed under the product road-map of Oracle.
  • having a greater connect to the industry in general. He can share on what kind of data quality issues are generic or unique and also where do we stand vis-a-vis others on our data quality standards and their implementations.

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    Relevant Links to this page
    TOPIC - Data Quality Program Approach → Data Quality Analysis considerations → Principles & Rules → Data Quality is a subject of business ownership and not of IT-ownership → Principles & Rules → Don't create a hype on Data Quality Program. → Principles & Rules → Sponsor for a Data Quality Program → Practice Techniques → Business Case for Data Quality → Principles & Rules → Data Quality is not Perfect Quality → Practice Techniques → How to get more data along with Sales leads → Practice Techniques → Ask for dates instead of number of years → Principles & Rules → How to Maximize the effectiveness of Data Stewardship → Practice Techniques → Field Tips Series#1- Data Mapping and Assessment → Principles & Rules → Data Management Standards for Data Entities will be a mix of collaboration and top-down → Principles & Rules → Data Management standards for data entities are not only for IT systems → Principles & Rules → Cascade your standards and guidelines to business partners and Vendors → Principles & Rules → Data quality assurance and control guidelines are no-brainer. Publish one immediately and evolve thereafter. → 
     
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    Relevant links to this page
    Data Quality Program Approach
    Data Quality Analysis considerations
    Data Quality is a subject of business ownership and not of IT-ownership
    Don't create a hype on Data Quality Program.
    Sponsor for a Data Quality Program
    Business Case for Data Quality
    Data Quality is not Perfect Quality
    How to get more data along with Sales leads
    Ask for dates instead of number of years
    How to Maximize the effectiveness of Data Stewardship
    Field Tips Series#1- Data Mapping and Assessment
    Data Management Standards for Data Entities will be a mix of collaboration and top-down
    Data Management standards for data entities are not only for IT systems
    Cascade your standards and guidelines to business partners and Vendors
    Data quality assurance and control guidelines are no-brainer. Publish one immediately and evolve thereafter.
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