Business intelligence derives insights from data to help businesses make right decisions for their business processes. These business processes can range from back end IT operations, to designing and executing a marketing campaigns, to creating a business strategy among many others. Automated business intelligence attempts to automate this process by removing dependency on human as much as possible. The importance of data driven business intelligence is widely accepted. With the recent advances in machine learning, and in particular, in natural language processing, automated business intelligence has gained a lot of momentum in the research community, leading to several new research areas such as augmented intelligence, AI powered analytics, composable data analytics, low-code/no-code business intelligence tools, to name a few. In the last few years, advances in the deep learning, and particularly the emergence of large language model, has opened up new horizons for the businesses to interact with the data. Specifying a SQL query in natural language, let the data speak for itself in human understandable text, being able to converse with the data and get insights are few examples of such interactions.