Automated Data Querying and Visualization Tool for Business Analysts

The client requires a comprehensive toolkit that enables Business Analysts to seamlessly query, visualize, and manage data across multiple databases without extensive reliance on IT support. Current manual processes hinder rapid decision-making and data-driven insights, leading to increased time and resource allocation toward content research and data retrieval.

A large telecommunication enterprise seeking to empower business analysts with self-service data access and visualization capabilities to enhance decision-making and reduce reliance on IT resources.

• Enable Business Analysts to independently query diverse databases via natural language or verbal questions.
• Implement real-time code generation for data visualization and dashboard creation using integrated AI capabilities.
• Automate retrieval and refreshment of database schemas and datasets to ensure analysts have access to the most current data.
• Streamline decision-making processes by providing rapid, visual insights through web-based dashboards and charts.
• Reduce data retrieval and processing times, aiming for significant performance improvements.

• Natural language/voice question translation to structured SQL queries suitable for multiple database types (e.g., MS SQL, PostgreSQL, Redshift, MongoDB).
• AI-driven code generation to convert queried datasets into web-based dashboards featuring charts, time series, and graphs.
• Automated schema detection and query generation based on user input by leveraging a vector database storing DDL and schema information.
• Integration of Python-based pipelines to automatically update schema and table metadata for accuracy.
• Web-based application interface, with options for deployment on cloud platforms such as AWS or Azure.
• Ability to send visualizations directly to communication tools like Slack.

• Multiple database systems (MS SQL, PostgreSQL, Redshift, MongoDB) for dynamic querying
• Communication platforms (e.g., Slack) for sharing dashboards and alerts
• Data storage solutions for schema and DDL metadata (using a vector database or equivalent)
• Cloud hosting services for deployment and scaling

• Response time for data retrieval and query execution: under 1 second for standard queries
• System availability and scalability to support concurrent users with minimal latency
• Automated error detection and correction in generated code to ensure high-quality visualizations
• Secure data access and user authentication compliant with industry standards

The implementation of this autonomous data querying and visualization platform aims to significantly reduce data retrieval times and decrease reliance on IT resources, enabling Business Analysts to independently access and visualize up-to-date data with minimal delays. Anticipated outcomes include a near 0% increase in data retrieval latency, improved decision-making efficiency, and optimized allocation of IT support toward strategic initiatives.