This video shows the working of Banks on Big Data. Big data represents a new way that banks can interact with and leverage their data. As a result, banks need to shift the paradigm for designing, developing, deploying, and maintaining big data solutions.
A wave of technologies has emerged to provide the flexibility and scalability required to support the shift. New approaches to data storage (e.g., NoSQL databases) can eliminate the burden of structure definition and enable cheap storage. Maturity of distributed-computation software frameworks (e.g., Hadoop) can provide the performance expected of a modern platform, while leveraging data on a scale never before attempted. Such visualization and reporting platforms offer a view into information not previously available. And such tools are at virtually everyone’s fingertips.
Just as banks need to reevaluate technologies, the approach to big data implementation also needs to change. Agile-development methodologies have evolved to provide rapid, iterative, and incremental deployment of solutions in a way that aligns well to the speed at which the underlying data are measured, understood, and parsed. While seemingly counterintuitive given the large scale of required information and complexity of analysis, effectively-executed big data development programs greatly shrink time-to-market and reduce development costs relative to traditional SDLC.