Content area
Full Text
1. Introduction
Many definitions can be found in the literature for business intelligence (BI)[1]. According to Negash (2004), “BI systems combine data gathering, data storage, and knowledge management with analytical tools to present complex internal and competitive information to planners and decision makers.”
Sherman (2014), in his book, notes that companies faced with the data deluge could not benefit from their data for decision-making alone. Data present various issues in organizations, such as inconsistencies, incompleteness, missed values and non-confirmed and outdated data. To help ameliorate these issues, BI solutions can be helpful and justifiable. All data in the organization should be audited to create a data warehouse. BI tools can use such data warehouses to present information to business personnel. This process is not simple, as there are traps and best practices which should be considered.
The purpose of this paper is to show that the use of BI tools by librarians can help academic researchers. BI tools can be used to inspect the status of research on Internet of Things (IoT) that deals with privacy.
2. Businesss intelligence tools in academia
There are important differences between using BI tools in academic situation and in their typical use by business organizations. Using BI tools in academic applications does not need technical or business justification. To use such tools for academic applications, researchers define their question(s) and use collected data to develop effective reports. Researchers and librarians may use data sets available in repositories and extract data from research papers or from the internet. Clean data are critical, and there are two options for using those available, easy-to-use tools or custom programming. When data are cleaned, they can be imported into BI tools for analysis. Figure 1 illustrates this process....