The term big data refers to the very large volume of data both structured and unstructured. The big data consists of very diverse sets of data. The size of the data and the speed at which the data must be processed differentiate the big data from traditional database. The source of data for big data mainly includes the scientific instrumentation and experiments, sensors and RFIDs and the social networking platforms. However, the internet of things is bringing more raw data into the system. Virtually every electronic device can be connected to the internet which generates huge amount of data in daily basis. The variation in the type and the application of the data requires the big data to be equipped with different architecture and software tools which are different from the software tools that are used to handle traditional data(Rouse, 2016)
The big data analytics is transforming the way the business decision are made. The big data provides a scientific and statistical way to view the business operation and process. Hence, the business can make decision based on the objective information and data. The decision made using big data analytics are likely to be more balanced and risk averse. The fact that the data are generated and analyzed in real time allows business to make action quickly and gain better time value. Though many business have turn to big data many still have to utilize the big data in their decision making process. The business organization must be able to figure out the appropriate tools, technologies and analytics to take advantage of big data in the process of decision making. The traditional tools which are based on relational database are not well suited for the big data. The software also cannot handle the large computational demand present in the big data technology. The NoSQL database and Hadoop and the similar tools provides solution for the modern application using big data. NoSQL database is able to work with the dynamic data which may be structured or unstructured. Some business might uses the Hadoop and the NoSQL database as the preliminary entry point for the data before passing it through data analytics(Rouse, 2017). The process may transform the data into the form which is resemble a relational structure.
The business strategy to use big data for the process of making decision must consider its business objective. The framework must be developed on the basis of which the big data strategy and technology can be deployed.
The framework consist of four business strategy using the big data technology and analytics to enhance the business decision making process.
1. Performance Management
This strategy involves the process of understanding the meaning of big data. The business organization are equipped with the business intelligence tools which can answer the queries related to the regular business process. The data generated from the regular business process can be used to answer the questions like the most profitable product or customers and make decision. Different visual analytics software can be used to visualize trends. The real time gathering and the analysis of the structured data can help to make plan and decision in quickly.
A business organization name BizTech, a technology firm, has used business intelligence to increase its business revenue. The company witnessed the growth in sales to approximately to 14 million USD. The company has used the business intelligence application to improve the business activity and customer’s satisfaction. The business sales department was able to generate new reports which include information extracted from business data analytics. Those reports was also used for developing skills and knowledge of the sales representatives.
2. Data Exploration
Data exploration refers to the process of applying statistical tools and techniques to find answers to the business questions. The exploration techniques encompass many modelling techniques which can predict and analyze the business environment, market landscape or customers behavior.In Cluster analysis the customer’s behavior can be analyzed and classified into various groups based on some similar attributes they possess to launch customized marketing plan.
The data mining can also be used to extract information related to the customer behavior and their buying habit. Target, for example, determined that a customers was going through pregnancy by analyzing the customer buying behavior. Target identified the product such as vitamins and lotions and other 25 items as the product related to the pregnancy. It then assigned a score based on customer’s buying behavior involving these items.
Akter, S., Wamba, S.F., Gunasekaran, A., Dubey, R. and Childe, S.J., 2016. How to improve firm performance using big data analytics capability and business strategy alignment?. International Journal of Production Economics, 182, pp.113-131.
Erevelles, S., Fukawa, N. and Swayne, L., 2016. Big Data consumer analytics and the transformation of marketing. Journal of Business Research, 69(2), pp.897-904. Abbasi, A., Sarker, S. and Chiang, R.H., 2016. Big Data Research in Information Systems: Toward an Inclusive Research Agenda. Journal of the Association for Information Systems, 17(2).