Do you actually have an architecture?
As Steve Miller, formerly at Gresham Tech pointed out:
“One fundamental barrier is that most banks and large enterprises rely on architectures that have evolved over time. In fact, ‘architecture’ may not even be the right term, as that implies a level of intent and design that can often be wholly absent. In a sense these landscapes are more like application ecosystems, consisting of a patchwork of inter-dependent systems that provide the underlying services the company relies upon to conduct its day-to-day business.”
Steve Miller, Gresham.
With properly prepared data to fuel information production, the next task is an engineering one: to ensure that information production systems operates efficiently & effectively. Data processing is an intensive, resource-hungry task where the application of engineering principles can help optimise the production of information so that it is efficient, effective, scalable and performant.
The digital expectations of management and end users or consumers, means that data circulation should not be constrained at any point within the domain, especially where cloud and bandwidth is concerned. Cloud is a commoditised service and thus subject to change. Networks are prone to service provision bottlenecks. So data migration, workflow modelling & master information concepts (consistent with strategic information requirements) are important aspects of the successful engineering & management of data-centric cloud (or hybrid) platforms.
Platforming is a common way forward for digital but platforms must produce reliable information at scale, at speed across an evolving ecosystem if they are to meet digital expectations. To achieve that with piecemeal systems is a huge challenge if information architecture remains the ad hoc organic environment which is usually the case. F1 performance requires holistic design, smart engineering, innovating with state-of-the-art interoperable components, to produce winning thrust for skilled drivers.