Applying data models to big data architectures

A key message from the early adopters of big data is that technologies such as Hadoop®, NoSQL (Not Only Structured Query Language) databases, and stream computing should not be seen as completely separate technologies but are more valuable when deployed in conjunction with more traditional data management components. There is an urgent need for an overall blueprint for treating both the new and traditional data management components in a holistic and integrated manner. A models-driven approach ensures consistency across this data management landscape in terms of management, governance, and efficiency. This paper focuses on the data modeling considerations relating the big data deployment using the examples of transaction data and mixed unstructured data to ensure that data components are evolved to maximize business value and development efficiencies.