We can provide predictive and inferential rather than simple descriptive analytics, using data modelling.
From time series forecasting models and charts, through extended models such as ARIMA and multiple regression, we keep things clear and not black box. That includes pushing as much of the statistical data back into the database for visualisation, rather than trapped inside Python or R code (where only the programmers can see, rather than the domain or business users).
Supervised or unsupervised Machine Learning (ML): clustering, classification, consolidation, linear and non-linear models can be immensely useful to understand data and behaviours, leading to insights and actionable decisions.