How can Governance enable quality in data?

Today, organizations want to derive more value than before from their data – they want their data, their understanding of the data and the insights they can gain from the data to be an asset and a competitive advantage. A key enabler has been more sophisticated analytics. Analytics capabilities have exploded in multiple ways in the recent years. We are now able to consume and analyze larger volumes of data in less time. There have been vast improvements in how structured or unstructured data can be analyzed. Statistical engines can be accessed from most analytics packages and this has led to wider usage of multivariate analysis, principal component analysis etc. Visualization capabilities

Sustainable Data Governance

The usage of the term data governance might be only second to the amount of data we seem to generate in today’s digital world. Though widely used, the term means different things depending on the perspective one has. This is not unique to any one company or sector – I have seen this at almost all my clients across a range of sectors. What are some of the common contexts in which you hear the word data governance? Teams trying to build business intelligence and analytics capabilities within a company struggle with data quality. An example could be an E&P company trying to reconcile between well names from multiple sources – land administration, measurement, allocation, geology and production

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