Venture’s ‘Discover, transform, manipulate’ methodology

Ian Jones offers some hints on mitigating data entropy—with help from Venture’s DTM methodology.

An interesting new contribution to Venture Information Management’s knowledge exchange from consultant Ian Jones discusses data quality and ‘extracting the truth from multiple data sources.’ Jones observes how poor management leads to data ‘entropy’ and an inexorable slide down the quality ladder. A Shell study found that quality can decline by ‘up to 5% per month’ due to incompleteness, conflicting sources of the same data and inaccuracies such as incorrect values, names and poor control over edits.

There is a natural tension between user preferences for particular nomenclature and formats and a consistent, managed approach. The solution outline is simple—identify the correct version, correct bad data and render such cleansed information accessible and secure. But the devil is, of course, in the detail.

Enter Venture’s ‘discover, transform manipulate’ (DTM) methodology, a structured process for moving a data resource from chaos to order. DTM leverages Venture’s V-DAT Oracle/PPDM-based staging database to hold and QC data before loading to ‘gold’ level corporate systems. Read the presentation here.

This article originally appeared in Oil IT Journal 2012 Issue # 7.

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