Our six steps
Data as a product
Build and manage data product outputs which are a collection of data assets.
Add a layer to trade data products. Adding this will clearly show integrity across data products, adding confidence to domains.
Domain level architecture
Focus more on building data solutions for each domain which will add value per domain. Different domains are more or less and as complicated as one another.
Front to back design
Leading on from domain level architecture, put the end consumer first. How are they going to use the data?
Management of metadata produced through all these products is critical to track not only redundant data, but to govern the landscape.
Remove constant dependency on end-of-day processing when streams are available. Enhance the platform by supplying up to-date data so that information value may be gained sooner.
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“As time moves on, new data capabilities and architectural methods are developing as we speak. This point of view looks to walk through the data evolution, to explore where we are currently, with the modern data platform.”