business intelligence

Architectural Approaches and Trends in GenAI Systems for Automated Interactive Dashboard Generation: A Systematic Review

This article presents a systematic analysis of the architectural and algorithmic foundations of Generative Artificial Intelligence (GenAI) systems designed for the autonomous synthesis of interactive dashboards. The review focuses on the transition from manual, code-intensive Business Intelligence (BI) workflows toward conversational, agentic paradigms enabled by Large Language Models (LLMs). It explores the 'Analysis-Presentation Decoupling' principle and the use of structured Intermediate Representations (IR) to enhance structural controllability.

NATURAL LANGUAGE–DRIVEN CHART SPECIFICATION AND GENERATION IN SUPERSET

Business intelligence dashboards provide powerful visualization capabilities, but creating diagrams typically requires manual configuration of visualization parameters, which limits accessibility for non-technical users. This paper presents a natural language interface for Superset that automatically generates visualization specifications from a user’s textual query.

Principles of constructing a software system of the aggregated data formation

This paper is devoted to the principles of constructing a software system of the aggregated data formation. The main principles of constructing a software system of the aggregated data formation are considered and their comparative analysis are carried out. An alternative principle of constructing a software system is proposed. This principle of constructing allows to eliminate the problems of fast and reliable data processing, scaling, automation of the software system components, improve data quality and security.