Case Study: The Golden Record
In our three-part whitepaper series on ‘IT Asset Data Quality’, we highlighted the issues that can be caused by inaccurate IT asset data within multiple areas of the organisation such as outsourcer billing optimisation, CMDB and ITSM controls, licence management optimisation, security and far more.
For organisations to have complete confidence in their IT asset data we recommended creating a ‘Golden Record’.
A customer of ours recently asked for a brief explanation as to what a Golden Record is and how it is created, this is how our consultant explained it:
A Golden Record is a single, well defined, version of specific data, held within a company, about a device or asset. It is also known as the ‘single version of the truth’. It is where to go, to ensure you have the correct version of a piece of information.
A Golden Record can be created by reconciling several sources of data that may have a different ‘view’ of the asset. The aim of creating these is to have a set of records that the company knows are accurate and can rely on. The Golden Record can be held in a separate repository but it will not be the master. The master data will always sit within the source it was created and the Golden Record will be updated each time a reconciliation is carried out.
Data to be taken from the sources will need to be optimised initially to give the best possible opportunities for matching the records and a repository will need to be created to accept all the prepared data. Data must then be extracted from the sources, within the same time period, to reduce the risk of time effecting the field values.
The work to carry out the analysis in identifying assets that are the same and creating the Golden Record will be very time consuming. The best matches will be from the identification of the key fields. Even once this match has been made, the other fields must then be analysed to see which values should go through to the Golden Record and which are incorrect.
Once the analysis is complete, it can be investigated where the inaccuracies lie and what needs to be done to correct them. The processes that support the data population for each source will need to be reviewed and adjusted if necessary. For historically incorrect data, manual work may be required to change the data. This may also involve changing roles and responsibilities in some teams to ensure the work gets done.
Improving data quality should be an ongoing process. The initial reconciliation will yield a tremendous amount of work and raise many questions but will lead to the largest immediate benefits. Repeating these activities will show trends over time and support that the work being done is producing improvements. New, or enhanced, processes will ensure data does not deteriorate.
If you have a question regarding any of the points raised, would like more information on ‘Data Hub’ our IT Asset Data Reconciliation Service, a demonstration of the capabilities of the service or to investigate a no risk no fee engagement, please call ITAMS on +44 (0)1582 464740 or email your enquiry to firstname.lastname@example.org.
For further information on managing IT Asset Data Quality please visit: Data Hub
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