Big Data and its impact on enterprise architecture

BI & DA have been used for years to evaluate bulk data but these technologies reach their limits when the data involved is ever more ephemeral, unstructured and high-volume. Big Data, which support BI & DA, are enabled by recent advances in technologies and architecture to handle unstructured and high volume data. However, Big Data problems are complex to analyze and solve. Challenges include classifying Big Data so as to be able to choose Big Data solution(s) to fit into the Enterprise Architecture (EA) of an organization. It is important to efficiently deliver real-time analytic processing on constantly changing streaming data and enable descriptive, predictive and prescriptive analytics to support real-time decisions for BI. When a significant amount of data needs to be processed quickly in near real-time to gain insights, this is a form of streaming data. Streaming data changes constantly and can be in many forms e.g. web data, audio/video data and external data. Using streaming data for BI and DA is a new paradigm in analytics and will have impacts on technology infrastructure components and data architectures, since most data is directly generated in digital format today. The technology infrastructure components and the technology architectures as well as data architectures changes must be captured by an organization’s existing EA to enable conducting BI and DA, using a holistic approach at all times, for the successful development and execution of an organization’s strategy.