• David Heath

What is Data Warehouse modernisation

We are now in the midst of an era where data is a being generated at a previously unprecedented rate, in a myriad of formats; no longer just structured data that fits neatly into a database table.

The most successful of organisations are those that are able to leverage business value from all the data that is at their disposal, using that to support growth and efficiency.

For many decades industry commentators and academics have used variations of the DIKW (data information knowledge wisdom) pyramid to illustrate how the value of data can be leveraged to ultimately deliver wisdom in the context of foresight.

These fundamental principles are as relevant now in the digital era as they have ever been. Yet, how this is achieved in practice is often the frustration of many businesses.

Many organisations will have previously invested in either siloed departmental BI solutions or corporate data warehouse projects in the recent past to try and deliver analytical insights from their core (usually on premise) systems. The technology world has changed a lot in recent years and unless these systems have been continually developed to keep pace with new data sources, modern infrastructure and more advanced tooling, their business value will have eroded over time.

Modernising the Data Warehouse can take many forms. Simply upgrading software or hardware to take advantage of modern technology advancements such as in-memory processing or massively parallel processing (MPP). Moving to a cloud or hybrid infrastructure to take advantage of the benefits that come with the public cloud; high-performance, elasticity, and cost-control.


More often than not, organisations are not sun-setting their existing core Data warehouses, more so expanding their platform into a complex or hybrid infrastructure. Surrounded by modern tools and systems, the traditional data warehouse is still at the core of many modern data warehouse environments.

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