The business intelligence applications industry is growing each year with research reports from organisations like Forex Tribune projecting significant growth. There are several reasons for this growth, the proliferation of big data, the expansion of IoT and the need to better understand the collected information are all contributing factors in the growth of BI. However, despite the high value of its contributions, BI can still come with a few improvements. Improvements made thanks to Artificial Intelligence (AI). Hence, I will explain what BI is, how AI improves technology and what it means to organisations.
Business Intelligence – What does it entail?
For those not in the know, business intelligence (BI) refers to systems designed to streamline the collection, processing and analysis of big data. Organisations can make sense of the large volumes of data they collect to sharpen their business processes and make smart decisions. As useful as BI is, there are some shortcomings that hamper the value it contributes to businesses. For example, there is a limit to BI capacity and the sheer volume of data collected is pushing that limit. BI will benefit tremendously from the application of AI because the latter augments the former.
How AI boosts business intelligence applications
AI expands BI functionality
Artificial intelligence boosts the functionality of business intelligence applications. With AI, business intelligence is better placed to breakdown large volumes of big data into granular insights, allowing organisations to better understand the value of smaller components into a larger picture.
Then, there is the issue of real-time insights, given that in their current iteration, BI can process and visualise big data, but cannot predict trends or generate real-time insights. However, AI incorporates the latest technology, like machine learning to deliver real-time insights about trends that will take place in the future. Thus, expanding the functionality of business intelligence applications and improving its value to organisations.
Close the gap
AI-enabled BI allows businesses to develop critical insights into data not examined before. Business intelligence applications powered by AI can examine fresh data and identify any trends relevant to the organisation. AI also allows BI to utilise the latest technology, like predictive analytics, machine learning and natural language processing to expand insights presented. Organisations are no longer satisfied with a visual dashboard of big data trends, they need tools that can close the gap between visual representation and actionable insights. AI-powered BI can help close this gap.
Simplifying a complex process
Surveying big data is often a complex process even with business intelligence applications. Professional data analysts have to survey 100s of charts and dashboards to get the insights needed. However, AI technology can simplify the process. The simplification happens because AI-based technologies, like NLP and machine learning, are closing the gap between machine and human communication. AI technologies allow machines to better understand human language and vice versa, making it easier for data analysts to find connections and insight. AI-powered BI allows organisations to tackle a much larger variety of data, including structured and unstructured data to get more detailed, comprehensive insights.
Solve problems related to talent storage
Business intelligence presents data findings on a visual dashboard, however, with data coming in from multiple sources, it becomes harder for dashboards to present the data in an easy to read format. However, with AI, the information can be defined at scale, making it easier to gain actionable insights. There is also the issue of talent. As of 2019, there is a severe shortage of data analysts. The right processing software can help alleviate some of the problems from a talent shortage by performing some of the functions normally delegated to a data analyst.
AI is the future of business intelligence applications
Business intelligence applications have been a tremendous asset to organisations, allowing them to better understand big data. However, times change and the needs of organisations evolve. They not only need intelligence software that can process and present data into visual findings, but they also require software that can predict trends, anticipate actionable insights in real-time and process a variety of data. This is where AI comes in since artificial intelligence allows organisations to breakdown big data into granular levels, so it is easier for organisations to make smarter decisions.