Self-Service Analytics enables business users and analysts to explore data, build ad-hoc reports, and create dashboards without requiring IT intervention or dedicated data engineering support. These platforms solve the bottleneck of analyst-to-engineer dependencies by providing direct access to data warehouses and databases through intuitive interfaces. The category spans several distinct modalities: spreadsheet-like interfaces that query live data sources, collaborative notebook environments combining SQL and Python, warehouse-native query workbenches with governed semantic layers, and hybrid platforms blending code-first exploration with point-and-click visualization. Originally focused on simplifying SQL access, the category has evolved to incorporate natural language querying and AI-assisted analysis, while maintaining emphasis on iterative exploration rather than static reporting. Most platforms now support both technical analysts comfortable with code and business users requiring visual interfaces.