AI-powered Business Intelligence. A hype or reality?
We live in a fascinating time when Artificial Intelligence (AI) is transforming the way we do things. This includes data pipeline design and analytics. Today Iād like to talk about how AI powers automated big data analysis and reporting. Iām sure you are familiar with Business Intelligence (BI) if you are reading this post. Throughout my almost 15-year career in analytics, there was a persistent discussion about the impact of artificial intelligence on BI. Itās quite difficult to say whatās bigger: AIās BI merge and its great potential, or all the buzz around it. This narrative reflects my personal views and beliefs regarding the evolving role of AI in analytics and Business Intelligence.
Companies aim to make better decisions based on the huge data volumes they collect every minute. BI as a discipline aims to analyse that data to generate insights that might have a certain monetary value. This in return grants a competitive advantage. However, BI effects on this are somewhat limited. Thatās where AI comes into play bringing all the benefits of AI-powered enhanced process automation. So how does it work exactly?
AI-powered Business Intelligence. A hype or reality?
Is it just another ephemeral spark or is it going to change the way we do analytics?
AI/BI merge and its benefits
No doubt, BI is an important piece of any data platform design but it has intrinsic flaws that restrict the value it can provide to a business.
The analysis is an intrinsic BI task and BIās primary focus was on data visualization for many years. The problem with it is that BI itself canāt predict data results and canāt create suggestions.
Predictive AI features
Take, for example, Sisense capabilities to predict trends [1]. Itās a very basic linear regression exercise incorporated into a robust BI tool. Itās a managed feature so analysts donāt need to worry about the regression model itself. BI tools does it all and its AI engine has the following models under the hood: