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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.
A London based company was taking back ownership of the server and end-user computing assets from their existing IT outsourcers. To date, there had been little ongoing validation of the service billing figures or of the physical estate numbers in general. The already deployed discovery and operational tools (e.g. AD, AV, CMDB) had been under the management of the outsourcer too, so there had also been limited day to day involvement of the specific asset figures.
An initial consultative assessment was proposed to determine the scope of the transfer and discuss the impact to the company in terms of the required refresh, software licensing, service design, roles and responsibilities and how the future mode of operation would operate. In this case, the billing figures would have been used to understand the estate and plan the above activities. However, lack of confidence in these figures, or the data held within the sources led to further action being required. This work would have been equally as important if the outsourcer was to continue billing and there was not an ongoing transfer. It is also worth noting that a change in Outsourcer agreements will often give rise to higher software publisher attention – compounding the issues already being faced.
The sources needed to validate billing were identified and used to populate a “Data Hub” and carry out a targeted reconciliation. Further analysis identified where data was incorrect and in which sources the processes needed to change to remediate and update existing information and to put in place actions so the data did not deteriorate; support was provided in this area. Benefits were realised such as correction of asset status, removal of duplicates/invalid assets and populating missing fields. This supported more accurate billing and the transfer of the asset ownership. The client had more confidence in the figures and would be able to more accurately predict the refresh and manage it. The transfer of ownership is now in final stage of completion, and the Client is actively considering an ongoing data quality process to perform regular check points and maintain a high degree of ongoing data accuracy.
This customer engagement provided an initial advisory project to evaluate their existing ITAM maturity. They are a multinational banking sector corporation with approximately 10,000 seats. During this engagement, it was found that there would be a large transformation project for the majority of the company’s IT hardware.
Phase 1 included delivery of a workshop, detailing a Service Design Overview (with descriptions and RACI), identification of the data sources supporting the operational configuration management function and in depth analysis as to how the transformation will be run and the effect of it on the current mode of operation. Data quality was clearly an area for improvement to ensure the assets to be supported were known and that the new configuration database could be populated with fit for purpose, accurate information.
Phase 2 the data sources identified in phase 1 (e.g. AD, CMDB, AV & Discovery) were fed into a ‘data hub’ where a reconciliation exercise was carried out. The analysis identified where data was incorrect and in which sources the processes needed to change to update existing information and to put in place actions so the data did not deteriorate; support was provided in this area. An advisory group was set up with all involved stakeholders, so that the optimisation would be felt across all the operational areas and the buy-in would support the actions. Benefits were realised such as correction of asset status, removal of duplicates and populating missing fields. On-going full technical and data services were provided for the customer in support of this work. Tangible savings will be realised when maintenance and support contracts are based on more accurate data.
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