Discussion B
Business intelligence came to be not very long ago, but it is evolving at a fast rate. Its rapid evolution can be attributed to the many benefits it has to offer to its users. As many people continue to enjoy its value, many new ideas about its enhancement also continue to emerge. For instance, in the near future, business intelligence tools will allow self-service (Conrad, 2019). Traditionally, business intelligence was a mystery known to selected IT experts. Any person who wanted to gather intelligence would have to seek the guidance of an expert. Such will soon be a thing of the past. With the emergence of business intelligence tools, companies are reducing their dependence on IT departments. It is also expected that business intelligence tools in the future will be more collaborative (Walker, 2009). Most of today’s tools are operated independently and not connected to a broad network. There is a prediction that future generation business intelligence will be better connected to greater systems. Lastly, future business intelligence will have improved data governance, which will allow organizations to comprehend their needs, continually improve their data quality, while at the same time ensuring confidentiality and preventing unauthorized access. Data governance will also enable organizations to use the right data to guide business intelligence decision making and ultimately improve overall organization performance.
Many organizations and IT developers have not fully adopted cloud-based technologies. I believe that there is a need to develop changes that ensure the integration of technology with cloud-based platforms. For instance, more devices need to support the internet of things to collect data efficiently. Doing so will ensure that massive data sets are broken down, visibility and connectivity are improved, and consequently, business processes. Additionally, cloud integration will result in better operational efficiency, less operating costs, and enhanced flexibility and scalability.
Predictive analytics requires efficient data collection and analysis. There is a need to streamline further the processes involved in data collection and analysis in the near future. Some of the areas that may require streamlining include data collection capabilities and high analytic power. Making predictive analytics a real-time process may mean efficient data collection, transmission, and analysis.
References
Conrad, A. (2019). The Future of Business Intelligence (BI) in 2020. SelectHub. https://www.selecthub.com/business-intelligence/future-of-bi/
Walker, R. (2009). The Evolution and Future of Business Intelligence.