Research Report: Intelligent Systems for Analytics (MITS5509)

This report provides an analysis of Intelligent Systems for Analytics, focusing on the application of Business Intelligence (BI) and Artificial Intelligence (AI) in business contexts. It explores the role of BI in enhancing business functions, supported by technologies like Big Data. The report delves into the significance of data warehousing and data mining as foundational elements of modern business strategies. It also highlights the impact of BI investments on organizational performance, emphasizing the use of data for prediction and decision support. The conclusion emphasizes the positive outcomes of BI systems and investments, providing a review of a selected academic paper that supports the analysis. The report also mentions the importance of BI systems and their impact on organizational performance. The report analyzes the selected paper, which offers a comprehensive review of BI systems and their influence on organizational performance, though it does not include a quantitative analysis of various frameworks. This assignment is a valuable resource for students seeking to understand the practical applications of intelligent systems in the field of analytics. This report is available on Desklib for students.

INTELLIGENT SYSTEMS
FOR ANALYTICS
Business intelligence

BUSINESS INTELLIGENCE
• Business is a process that includes different functions for growth and success
in the market places. In addition, Business Intelligence (BI) is a tool that
provides help to manage business functions in an efficient manner. A firm
can use technologies for improving the performance of its business functions
(Collier, 2012).

ROLE OF BI IN GROWTH
• Artificial intelligence (AI) has provided solutions and opportunities in the field
of businesses (Castelluccio, 2017).
• Big Data (BD) is another tool, which has used for improving performance
(Chen, Chiang, & Storey, 2012).
• In addition, the decision support system was based on the Bis systems and it
has managed using data mining and data warehouse. Moreover, BI systems
have used for improving the efficiency of a firm using proper decision support
mechanisms (Chowdhury, 2014).

DATA WAREHOUSING
• Data mining and data warehouse are the base of a business in the present
era (Shmueli, Bruce, Yahav, Patel, & Lichtendahl Jr., 2017).
• Besides, the BI system is in trends, which is a good way to manage all the
things (Obeidat, North, Richardson, & Rattanak, 2015).
• In addition, BI investment makes a huge impact on the performance of an
organization, as BI systems have provided data and information for
prediction and decision support (Trieu, 2017).

ROLE OF INTELLIGENT SYSTEM
• According to surveys, BI systems are a better choice for improvement in the
performance of an organization (Vercellis, 2011).
• Ultimately, data warehouses can be used for improving the performance of
an organization. BI investment is a good feature, which is based on BI assets.
In addition, non-BI investment is also considered in the article as well (Trieu,
2017).
• BI is a technique for reading statistics and deriving insights to assist
businesses to make selections. In an effective BI procedure, analysts and
statistics scientists discover meaningful hypotheses and may solution them
the use of available records.

CONCLUSION
• In conclusion, BI systems and BI investment have provided better results for
organizational performance.
• Finally, this article has provided a proper review of the sample paper, which
is a good way for a literature survey. This report has analysed that selected
paper has provided a better review of BI systems and their impacts on
organizational performance.
• However, it has not included a quantitative analysis of different frameworks.

REFERENCES
• Trieu, V.-H. (2017). Getting value from Business Intelligence systems: A review and research agenda.
Decision Support Systems, 93, 111-124. doi:https://doi.org/10.1016/j.dss.2016.09.019.
• Collier, K. (2012). Agile analytics: A value-driven approach to business intelligence and data
warehousing. London: Addison-Wesley.
• Castelluccio, M. (2017). Artificial intelligence in business. Strategic Finance, 98(10), 55.
• Chen, H., Chiang, R., & Storey, V. (2012). Business intelligence and analytics: from big data to big
impact. MIS quarterly, 1165-1188. Retrieved from https://www.jstor.org/stable/41703503
• Chowdhury, S. (2014, May 27). Big data and data warehouse augmentation. Retrieved from IBM:
https://www.ibm.com/developerworks/library/ba-augment-data-warehouse1/index.html
• Obeidat, M., North, M., Richardson, R., & Rattanak, I. (2015). Business intelligence technology,
applications, and trends. International Management Review, 11(2), 47-56.

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