A thorough understanding of as-is and to-be environments is necessary to be able to plan for proper big data solutions since the implementation options are so broad. For organizations that have not done this yet, we have experience in performing assessments of technologies, processes and people within divisions or across the enterprise. This is critical in determining the scope of potential solutions to be deployed, as well as capturing the business and technical requirements in support of transition planning and change management.
Planning and Design
An architecture provides a good framework and blueprint for the actual implementation of services. With our extensive domain and technical knowledge, we can help you to design a solution framework, or architecture, that supports legacy and future solutions. We will look at our core products and services in big data, analytics, visualization, and mobile technologies to develop the best framework and solution for each customer. This also includes workload and capacity planning, information access and distribution, security and privacy and overall performance and interoperability within your enterprise and with your external business partners. A roadmap and transition plan assist in this migration to a new big data infrastructure.
Our hands on experience with big data architectures and solutions ensure that we will get your project up and running quickly and efficiently. We can also bring in our technology partners as part of an integrated implementation team, as situations dictate. Many big data implementations suffer from the lack of integration of disparate components and we are keenly aware of these factors that disrupt interoperable and integrated solutions, but which are still based upon open standards and loose coupling to provide flexibility and breadth of implementation.
The pace of technology change requires an operations and maintenance strategy that not only keeps existing solutions running at peak efficiency, but also managing for the technology changes and improvements needed to move transparently into the future. This includes updates to software versions, improvement/replacement of APIs, security model improvements and integration of additional solution components into the core architecture to enhance functionality and performance.