There is a Lack of Intelligent Automation in Business Intelligence

BI is targeted at data consumers, such as business users, and it is suitable for descriptive analytics to uncover which KPI or metric has changed. Business Intelligence lacks intelligent automation such as NLQ, automated visualizations, Automated Insights, Automated Prep, AutoML, and Proactive Intelligence which are offered by Decision Intelligence.

    

It has often been necessary for businesses to balance the tradeoff between sacrificing the quality of their insights by limiting the analysis to a small set of variables. In addition, they have invested a significant amount of time in data preparation, analysis, and model building to get the detailed, granular data they need. The reality, however, is that no firm can afford to make this compromise in practice. It is imperative to have a short time-to-insight if you want to benefit fully from fresh insights. It is essential to use all the information at your disposal in order to make the most informed decision.

Wouldn't it be helpful if everyone in the organization could answer data-driven ad hoc questions instantly and relieve analysts and data scientists of some of their burdens? Tellius helps Financial Services Analytics Companies discover new opportunities, improve service, and differentiate themselves from the competition through portfolio analysis, customer segmentation, and cash flow analysis.

By building on traditional paradigms of data analysis, the latest generation of Business Intelligence technology makes insights accessible to a wide range of business users. This includes those without considerable technical expertise. The use of augmented analytics can actually allow data analysts and citizen data scientists to extract more detailed insights within minutes. Compared to what a professional data scientist might be able to do with a traditional BI system in the same period of time, this is significantly more efficient.