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Data Specification Standards Deliverable Template

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This article is currently Under Construction. It is undergoing major changes as it is in the early stages of development. Users should help contribute to this article to get it to the point where is ready for a Peer Review.
This deliverable template is used to describe a sample of the MIKE2.0 Methodology (typically at a task level). More templates are now being added to MIKE2.0 as this has been a frequently requested aspect of the methodology. Contributors are strongly encouraged to assist in this effort.
Deliverable templates are illustrative as opposed to fully representative. Please help add examples to this template that are representative of the proposed output.


Data Specification Standards govern the definition of data. Data specification standards are used to ensure that data definition is consistent and of high quality. High-quality data specification standards encompass the enterprise use of data, are managed and enforced by data stewards, and provide clarity such that compliance can be assessed.

Data Specification Standards include:

  • Common naming conventions
  • Common use of data types
  • Common formats for text fields
  • Data presentation standards
  • Use of common Domains
  • Use of Class Words

Example Data Specification Standards

Listed below is an example of data specification standards to be addressed:

The Data Specification Standards should address the following issues identified during the data quality assessment project:

  • XXX Code formats differ across systems. In systems where prospects originate, XXX Code is 8 characters. Only first 4 characters are transmitted central customer system because of system constraints. System appends a zero to the end of the 4 digits creating a 5 digit SIC Code.
  • Pending policy change will require the XXXCode at the obligation level to reflect the primary source of repayment, not the obligor’s primary SIC Code.
  • The Data Warehouse will implement business rules when populating reference data (e.g. Customer Name selection). Knowledge workers will need to understand these to interpret the data.
  • Obsolete fields which are no longer used should be removed/hidden
  • Fields used for new purposes should be corrected identified (e.g., Facility code was placed in the Collateral Code field)
  • There have been occurrences where Mr./Mrs. And other name identification information has crept into unintended fields. They are mostly older records, but they still exist
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