AI integration in Power BI improves reports with automated insights, explanations, and predictive analytics. Integration can be achieved through Power Automate, Azure OpenAI, or Python scripts within Power BI. Power Automate enables AI-based responses to trigger based on report interactions; Azure OpenAI APIs can be utilized for on-the-fly insight generation; and Python scripts within Power Query can be undertaken for sentiment analysis or forecasting using AI models.
APIs and Power BI visuals may be used for AI insight embedding. Power BI itself comes with its AI visuals, such as Key Influencers or Smart Narratives, which can be used for built-in AI-driven insights. For custom AI responses, an API-based approach would be to invoke Power Query or Power Automate by sending queries to the OpenAI API and injecting the AI-generated text or analysis back inside Power BI. A chatbot-like interface embedded within Power BI would offer interactive AI-based insights into the data visualizations.
Security and performance management should include API authentication methods (OAuth, Azure AD), information restriction via row-level security (RLS), and optimization of API calls to avoid performance bottlenecks. In the case of Python, use Azure Databricks or Azure Machine Learning for computations and avoid performing the same in Power BI. These best practices will ensure seamless integration of AI tools while securing performance.
