Big Data
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Analytics are crucial for decision making, minimization of risks, and to unearth
valuable insights that would otherwise remain hidden below the surface. McKinsey
spotted that for example for tax agencies an automated algorithm concentrating on
risk evaluation of tax payers can help flagging potential candidates for further
examination. Potential algorithms for Big Data analysis include rule-based systems,
statistical analysis, and machine-learning techniques such as neural networks.
5.
Innovating new business models, products and services
Big Data does not only enable companies to gain more relevant information to
improve business processes, but also generates new products, services and even
jobs. An example for a new job, which is focused solely on Big Data, is a data
scientist. A data scientist can be described as a mixture between a hacker, an
analyst, a communicator and a trustworthy counselor. Tasks involve ad-hoc
analysis, generation of hypotheses based on Big Data, as well as formulating
business relevant decisions (Davenport & Patil, 2012, pp. 35-37) & (Manyika, et al.,
2011,
pp. 97-100).
The case study implies that Big Data provides potential opportunities for business
purposes including improvement of performance, deeper segmentation of
customers, or the creation of innovative business models.
