Original LinkedIn Post
Stop manual drag-and-drop: Generate interactive BI dashboard prototypes from a single prompt.
We just ran an end-to-end automated BI pipeline using my open-source Python SDKs, cwprep and cwtwb, connecting data prep, metric definition, and UI design. For a classic scenario like "tracking Free Trial to Premium conversions," the pipeline works in three stages: 1. Automated ETL (cwprep): Translates natural language into SQL and generates a Tableau Prep flow (.tfl), streamlining complex joins to output a clean dataset. 2. Auto-Generated Layout & Models (cwtwb): Once a .hyper extract is generated locally, cwtwb parses it to build a Tableau workbook (.twb). It writes core calculated fields (e.g., Conversion Rate), and most importantly, the AI independently designs the entire UI layout. 3. Zero-Click Interactivity: The AI auto-configures dashboard actions. For example, clicking a regional bar chart automatically filters the time-series trend below, saving hours of manual setup. Here is a conceptual ASCII mockup of the generated prototype layout: Plaintext
Core Value & Next Steps It is important to note that this is a rapid prototype for quick business validation, not a final production dashboard. It still requires a human-in-the-loop for visual fine-tuning. However, it frees analysts to focus entirely on business logic. The heavy lifting is automated. Currently, the .hyper dataset is generated and mounted locally. Our next step is to leverage the Tableau REST API to automate data publishing to the Server, creating a fully closed-loop, code-first analytics pipeline.
#Tableau #DataVisualization #ArtificialIntelligence #BusinessIntelligence #OpenSource #DataAnalytics #MCP #AIAgents #DataEngineering #datafam #gemini #google #ai #bi #agent #cwtwb #codex #chatgpt #mockup #powerbi #tableauprep