These days, customers have multiple data platforms at their disposal (for example: data warehouses, data lakes, etc.). These platforms are usually designed to quickly deliver value for employees by providing access to a lot of data, performing rapid analyses and enabling them to answer ad hoc questions. In time, these initiatives often come up against challenges in terms of control – it proves impossible to find data, carry out analyses and compare results.

KPMG has developed a framework to exercise greater control over data platforms in which repeatable reports, ad hoc analyses, data exploration and experiments are performed. This framework describes standards and control measures that help achieve a mature data platform throughout the life-cycle of the data and the code that enables these analyses.

The framework includes:

  • A method of following datasets during their life-cycle by means of a waybill;
  • Standardised better-practice data processing procedures for supplying data, approving data initiatives and working with data;
  • Models that simplify the provision of information about the data to end users such as data analysts, data scientists and data owners within the organisation.

KPMG has ample experience in providing advisory services around data platforms. For instance, we are involved in many of the Netherlands’ best known data ecosystems within the FMCG, retail, real estate and healthcare sectors. With our team of specialists, we also advise large internationally operating companies on more effective deployment of data platforms across the entire spectrum from financial institutions and chemicals companies to web shops.

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Chris Hoffman

Director, Data Management

KPMG Advisory N.V.

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