Business Intelligence (BI) improves through the use of analytical data streams that help companies overcome market challenges and create internal growth mechanisms. Because the international business environment is complex and large it needs improved analytical tools to be successful. Small, medium, and large businesses are increasingly relying on BI to help them make strategic decisions. A paper by Khan & Quadri (2014) discusses the growing use of BI in everyday business decisions and how to improve on exiting models.
Proper BI requires the collection of data, analysis of that data, and providing a conclusion on the meaning of that data. BI uses proper analytical methods based in scientific research to achieve its goals. The same principles that apply to any research study would also apply to the business intelligence and strategy formation; in theory anyways.
BI has been defined as, “The process of collection, treatment, and diffusion of information that has an objective, the reduction of uncertainty in the making of all strategic decisions” (Zeng, et al. 2007). Such information is collected analyzed and then disseminated among those who can use the information to the advantage of the organization.
BI relies in part on the collecting and analysis of information from the market environment. This can be difficult when there is data scattered all over the place. This is even more possible when even more data makes its way into cyber sphere and creates a type of data collection net that offers higher possibilities for global analysis.
Data mining can be defined as the search for relationships and patterns that exist among data (Holsheimer & Sibes, 1994). In essence, data is an amebic entity that doesn’t necessary show anything in and of itself. It is up to the user to find patterns and make predictions of this information based upon what they understand and which type of data they can capture.
The data’s fundamental practicality is the ability to put it to strong use. According to Stackowaik, et al. (2007), BI is the process of taking large sections of data, analyzing it, and then presenting useful report for managers to help them make accurate decisions. BI becomes more of an analytical tool that continually updates based on algorithms for real time decision making.
BI has the ability to help companies grow and develop beyond their current decision-making processes. Proper strategy formation requires understanding how data can help narrow down the options and choose that which is most likely to influence and improve upon the successes of the business. Data is getting stronger and so will the need to analyze that data in new and more accurate ways.
Holsheimer, M., & Siebes, A. (1994). Data mining: The search for knowledge in databases. CWI (Centre for Mathematics and Computer Science), Amsterdam, The Netherlands .
Khan, R. & Quadri, S. (2014). Business intelligence: an integrated approach. International Journal of Management & Innovation, 6 (2).
Stackowiak et. al. (2007). Oracle data warehousing and business intelligence solutions. Indianapolis: Wiley Publishing, Inc.
Zeng, et. al. (2007). Techniques, process, and enterprise solutions of business intelligence, 6, 4722.