Big Data-driven strategies for business decision-making with data science.

Abstract

Organizations uses a mechanism for data analytics using data-driven techniques which helps to improve their business-related Decision. The benefits can include more effective marketing strategy, new revenue generation opportunities, customer personalization and improved operational efficiency. Initially the data is collected for the data analytics which has been examined later. This large volume data which is to accumulate for identification of market trends also to find the insights from the data is being handled by big data technique to identify patterns for taking competitive business decisions. This information is available quickly and efficiently so that companies can make plans to maintain their competitive advantage. The identified trends are used to formulate insights helping in the making of strategic business modeling and decisions. The large impact due to this have also changed the business age. A day by date growth in the data is increasing the necessity to provide concrete solution using data processing and insights extraction forming the valuable information from it. The diversified data from everyday operations from various platforms such as Customer Relations to social medias has increased. In the view of this growth and diversification, this paper is aimed at the crux of big data concepts from the foundation of data science and decision science for the business cases.