Digital transformation requires a unique and vastly experienced skill set, and for our experience the required skill gap can be classified as solution and data architects. At Easymatics we have experienced solution and data architects, pragmatically enabling organisations to build a future-proof platform. Being an architect purest in the age of technology disruption will not advance your business goals. Our team can help you fill that gap to grow business skills and confidence.
Generally organisations have enterprise architects in-house focussing on general applications, and of quite a purest agenda that organisations find it hard to implement the intent of a digital transformation. The architecture domain is typically structured around an Enterprise Framework but the model can vary, this model preference becomes key requirement for architects to work on projects, but still doesn't move the digital transformation agenda forward. In fact we find that most organisations with the high costs of whatever the chosen enterprise within the organisation, and the business users are left not realising their requirements.
Regardless of Enterprise Framework deploys, there are common themes which can enable a more pragmatic conversation on how to move forward. The architecture can be described across four pillars;
- Business architecture
- Data architecture
- Applications architecture
- Technology architecture
The Enterprise Framework though should describe the application of architecture principles and practices to guide organisations through the business, information, process, and technology changes necessary to execute their strategies. The business goals can typically be quantified by; effectiveness, efficiency, agility, and durability.
In a digital transformation program we refer to all components as enterprise, as we need to connect to all users and information to realise the benefits across all users who are touched by the tools.
Digital Transformation fundamental themes;
there are many expectations in this area, which are normally based on cost reductions. In general though one of the more business effective benefits is agility. Cloud computing relies on sharing of resources to achieve coherence and economy of scale, similar to a utility. A correctly designed cloud computing model can be rapidly provisioned and released with minimal management effort. Strong independent guidance is required to avoid the pitfalls of software as a service (SaaS) models offering quick fixes.
a significant evolution from a data warehouse and the concept provides a single store of all data (structured or unstructured) in the enterprise ranging from raw data to transformed data which is used for various tasks including reporting, visualisation, analytics and machine learning. The data lake therefore creates a centralised data store accommodating all forms of data and is a critical component of a digital transformation journey.
a significant shift from traditional SOA models, allows an application to be structured as a collection of loosely coupled services, which can be an effective approach to understanding the services required to be consumed in a SaaS model. The benefit of decomposing an application into different smaller services is that it improves modularity and makes the application easier to understand, develop and test. Microservices-based architectures enable small autonomous teams to develop, deploy and scale their respective services independently as well as enabling continuous delivery and deployment.
Continuous improvement is one of our key tenants of a digital transformation, refer to digital transformation services for further details, embedding the concept in an organisation is critical to sustained benefits.
We have the skills to support end-to-end digital transformation architecture needs, and the skill sets are classified as follows;
convert requirements into the architecture and design that ultimately constitute the blueprint for the solution. Relies on design patterns from their previous engagements, published reference architectures, balance architectural concerns of the projects with the concerns of the enterprise.
design, create, deploy and manage an organisation's data architecture. Define how the data will be stored, consumed, integrated and managed by different data entities and IT systems, as well as any applications using or processing that data in some way. Describes the behaviour of applications used in a business, focused on how they interact with each other from a data consumption and user perspective.