Mean Standard Deviation Target
A framework for implementing a scalable business intelligence system 83 memory issues. Furthermore, Figure 3-19 and Figure 3-20 illustrate that increasing the report size influences the report's refresh time rather than its failure rate.
However, having many reports refresh at the same time can have negative consequences on the PowerBI gateway because the PowerBI gateway’s available memory is limited, and as the number of reports increases, the PowerBI gateway machine will need to be scaled up to handle the rise in demand.
The PowerBI gateway is hosted on a cloud-hosted virtual computer, and the memory may be simply scaled up or down as needed. As a result, the implemented BI system is both adaptable and scalable. This is further demonstrated by the fact that the BI reports are embedded in XYZ's consulting web application, which can be viewed by a wide range of users from a wide range of devices from anywhere in the world.
In terms of system quality, Figure 3-18 demonstrates that the number of refresh failures is minimal when compared to the number of successful report refreshes. Furthermore, Figure 3-19 illustrates that the size of the report that users create has no effect on the report's failure rate. As a result, the BI system does not restrict the user in terms of the type or size of report that they can create.
Figure 3-20, on the other hand, shows that the report size influences the refresh time, which is expected given that more rows are generated in the report, but the survey results show that more than 60% of respondents are satisfied with the timeliness of the BI system, which may indicate that the refresh times are acceptable.
Going deeper into the survey results, most respondents were generally satisfied with all the BI system's covered aspects, apart from being able to construct the exact reports that they require. This indicates that many respondents are either not experts in using PowerBI or are reluctant to develop new expertise in PowerBI.
To improve this, it is evident that an organisation must be ready to invest in training users for them to get the most out of the technologies that they use. For example, if users take a PowerBI advanced training course, they may be able to build unique reports that fit their requirements.
Furthermore, PowerBI was chosen as the platform for creating the BI system. If a new tool is requested, this can always be changed later without affecting the entire BI system because the only major modification required is the creation of new report templates.
In terms of system usage, Figure 3-22 demonstrates a decrease in the number of monthly reports created. This isn't a bad thing and is explained by the fact that Figure 3-22 only shows the number of unique reports available on the system. Each report is also updated on a regular basis with several revisions, which are made using the BI system.
Thus, the fact that 72 unique reports were produced using the BI system in a year is a good sign that the BI system has been adopted and accepted as a data analysis tool by a variety of different users at XYZ consulting.
A framework for implementing a scalable business intelligence system 84 The success of the BI system also has a positive impact on the organisation. For starters, a broad range of users have adopted the BI system and are actively utilising it on various projects. As a result, the organisation's data becomes more valuable. When the value of data increases, the organisation can be more confident in making well-informed data-driven decisions.
Furthermore, thanks to embedded analytics, the data insights obtained from the BI system can now reach a broader spectrum of clients. Because the BI system scales to a larger audience, the organisation can expand their offering to their clientele. This may eventually have a favourable impact on the organisation's efficiency, reliability as well as earnings.
Overall, the framework was able to produce a system that provided good system and information quality. This resulted in increased system usage and, finally, a high level of user satisfaction which has a resulted in a positive impact on the organisation.
SUMMARY
Using the proposed framework from Chapter 2, this chapter implemented a BI system for an ESCo company called XYZ consulting. To improve the system's scalability, the BI system was created using a cloud-based data warehouse as well as embedded analytics. In addition, PowerBI was chosen as the BI platform to be used.
Following the deployment of the BI system, various XYZ consulting project teams created reports using the implemented BI systems. These reports were utilised for a variety of projects, including tracking statistics on electricity, cooling, compressed air, and water usage. As well as budget, mining commodity, and internal data monitoring.
This chapter also included results from the established BI system. These findings addressed a variety of characteristics of the BI system, such as system quality, information quality, system usage, and user satisfaction. This chapter also demonstrated that the implemented BI system was successful in meeting the research objectives.
The BI system was used to construct 72 reports, which resulted in at least 2.5 GB of data being used by the reports. Furthermore, the implemented BI system was reliable, with a low refresh failure rate of 7% and report refresh intervals that were deemed acceptable by various BI system users.
Furthermore, more than 60% of users were pleased with the system's usability, information quality, and the overall system itself. However, some features, such as the capability to construct specific reports that fit the user's exact requirements, obtained a poor user satisfaction rating.
In the end, a general discussion of the findings was provided. This discussion reviewed all the outcomes presented and demonstrated that, while the BI system has limitations, it is overall successful in terms of providing good system quality and information quality, which translates into system usage and, eventually, user satisfaction.
A framework for implementing a scalable business intelligence system 85