- Augmented analytics in ABI platforms (augmented ABI) transforms and democratizes how business people explore, analyze and act on insights by surfacing key insights in data through ML and AI assisted data preparation, insight generation and insight explanation.
- By automating many aspects of DSML development, management and deployment augmented analytics in DSML platforms (augmented DSML), expert data scientists become more productive. This also extends DSML model building to a broader range of less skilled users including new citizen data science roles (business analysts, developers and others).
- Explainability is increasingly becoming an important capability to give users confidence in using machine-generated insights and recommendations.
- Natural language interfaces such as search via text and voice combined with augmented analytics make analytics more accessible and consumable by a broader set of users.