An in-depth analysis of SQL Data Insights (SDI) from both technical and business perspectives: Technically, we explore which columns to select, the effects of normalization, data type simplification, and correlation. In summary: How can data preparation enhance the accuracy of an SDI model? From a business perspective, we focus on identifying use cases and evaluating models. Instead of relying solely on technical metrics like accuracy, we assess models based on business metrics such as profit and savings. Measuring business value is essential for its pursuit. Using SDI avoids data transfer and replication, enabling us to measure business benefits immediately after creating a view, training, and executing semantic queries. In numbers: 4 hours from idea to valuation. 

Thomas Baumann,Data Evangelist, Swiss Mobiliar