Why don’t they simply consolidate their data silos?

Consolidating siloed datasets has been one option for those looking to get a complete understanding of their customers. However, the increased focus on data protection in GDPR makes this increasingly less attractive for a variety of reasons. First, the additional processing of personal data requires a solid legal basis, perhaps bringing together several data sets themselves run on different grounds. Secondly, the creation of a single data pool is an additional point of risk, with one exploit potentially leading to a much bigger breach than if it occured in one silo. Finally, there may be solid business reasons for keeping the data from the different divisions separate and not having entanglements which would, for example, prevent rapid re-organisations or spin offs in the future.

So, continuing with the above example, while the supermarket would likely have a clear legal basis to merge its customer data from its grocery and financial services divisions, the risks and logistics of creating a single data pool are problematic.

The second option, that has been more popular, is to use a Business Intelligence Platform, that brings together various datasets and provides a complete picture of the data. However, the majority of these platforms require the raw data to be physically moved (through the cloud) and combined.

So what’s the answer?