Business Intelligence Analysis Process Essay

Business Intelligence Systems In The Decision Making Process

The most common purpose for (BI) systems is to aid in the decision making process. BI systems collect data, store the gathered information in data warehouses, analyze the data and then present the data in easy to understand applications for the decision making process. The following studies research the role that BI systems play in the decision making process.
The Role of BI in Decision Making
Overview. Isik, Jones, and Sidorova (2013) conducted a study that explored the following research questions “(1) What is the relationship between various BI capabilities and BI success? and (2) What is the influence of the decision environment on the relationship between BI capabilities and BI success?” (p. 13, para. 4). The research model used explored the relationships between BI success, technological BI capabilities (data quality, integration with other systems, user access), organizational BI capabilities (flexibility, risk management support), and decision environment (decision types, information processing needs) (Isik et al., 2013, p. 17).
Methodology. The study completed by Isik et al. (2013) was started with a four part survey that included participant demographic information, measurements of BI success, measurements of BI capabilities, and measurements of decision environments. The survey was analyzed by academic experts and adjusted according to their suggestions. A pilot study was then conducted using 24 BI professionals and the results suggested that the survey required no further changes. The final survey was sent to over 3000 mangers that utilized BI systems in their businesses. Of those surveys only 92 were returned and useable for data collection. The data from the pilot study and final survey were combined to provide 116 participant responses. The data from the respondents was then analyzed using t-tests to determine the differences and relationships between BI success, BI capabilities, and decision environment. (Isik et al., 2013).
Results and Conclusions. According to Isik et al. (2013) the results of the study suggest that BI success is significantly related to the ‘integration with other systems, user access and flexibility’ BI capabilities. Contrary to the research model and hypotheses BI success is not significantly related to ‘data quality and risk management’ BI capabilities. The results do suggest that BI success is directly related to the type of decision environments, although this study only focused on two types. The study findings indicate that BI success in an organization depends on the appropriate BI capabilities in the correct decision environment. The study concludes that further research is required to analyze why BI success is not significantly affected by data quality and risk management. In addition more research is needed to explore the relationship between BI success and additional environment decisions. (Isik et al., 2013).
BI Tools in Decision Making
Overview. Al-ma’aitah (2013) completed a study to...

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Business Intelligence

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Business Intelligence for competitive advantage

In the beginning, businesses used information technology for automating the processes primarily to reduce labor costs. Subsequently, information technology is used for delivering information with speed and accuracy.

Currently, businesses want to use the information effectively for competitive advantage to make better decisions that improve and optimize business processes, predict the market dynamics accurately, optimize forecasts to adequately maintain resources to name a few reasons.

Businesses reached a critical juncture in global competition and the business intelligence capabilities and analytic prowess will play critical roles in the most competitive sectors of global economy.

First of all, business intelligence analysis requires the capturing of information and storing in a single location for effective data analysis. Currently, data analysis is supported by transactional systems, business specific data marts, and other ad-hoc processes. Information is distributed making it difficult and time-consuming to access. Business teams have adapted to this environment by creating user maintained databases and manual “work-arounds” to support new types of reporting and analysis. This has resulted in inconsistent data, redundant data storage, significant resource use for maintenance, and inefficient response to changing business needs.

A data warehouse comprised of disparate data sources enables the “single version of truth” through shared data repositories and standards and also provides access to the data that will expand frequency and depth of data analysis. Due to these reasons, data warehouse is the foundation for business intelligence.

As a Technical Architect, I am involved in the design and development of the Enterprise Data Warehouse at Target. I and many of my colleagues worked hard to make the business case of the importance of the data warehouse and its value addition to the company.

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