"Talk to My Data" Agent¶

Access this application template on GitHub

Use the "Talk to My Data" Agent application template to ask questions about your tabular and structured data from a .csv or database using agentic workflows. This application allows you to rapidly gain insight from complex datasets via a chat interface to upload or connect to data, ask questions, and visualize answers with insights.

Decision-makers depend on data-driven insights but are often frustrated by the time and effort it takes to get them. They dislike waiting for quick answers to simple questions and are willing to invest significantly in solutions that eliminate this frustration. This application directly addresses this challenge by providing a plain language chat interface to your spreadsheets and databases. It transforms raw data into actionable insights through intuitive conversation. With the power of AI, teams get faster analysis helping them make informed decisions in less time.

This application is useful for those that want to:

• Generate reports and dashboards for stakeholders and operationalize work from data analysts and data scientists.

• Track, report, and analyze the performance of department activities, ad hoc analytic requests, and development and automation of regular reports.

• ​​Empower faster decision-making by rapidly extracting insights from your data.

• Gain control over deployment security and governance.

• Scale operations that align with enterprise demands.

Key features¶

• Agentic workflows: Combine multiple steps to answer questions about data, including data preparation, dictionary generation, and code generation.
• No data size limitations: This application manages large amounts of data without restrictions. While the number of rows is unlimited, the number of data columns depends on the LLM selected.
• Seamless data connectivity: Integrates with the AI Catalog to seamlessly blend data from diverse sources, including external datasets like weather, financial data, and supports the incorporation of ad hoc local files with data from virtually any other source for comprehensive analysis.
• Natural language-powered, context-aware Q&A: Use everyday language and easy prompts to ask specific business questions, leveraging your proprietary datasets for precise answers in a conversational chat experience.
• Domain expertise: Incorporate industry-specific logic in order to generate highly nuanced and accurate analyses of your data.
• Ease of use for all skill levels: A user-friendly interface enables non-technical users to analyze data with plain English queries, while technical users can review the generated code providing transparency as needed.
• Data analytics and visualization: Rapidly analyze large datasets using BigQuery or Snowflake SQL, complemented by customizable, industry-specific visualizations for actionable insights.
• Minimize risk and maintain compliance at scale: MLOps ensures operational reliability with scalable governance and robust monitoring, empowering executives and analysts to confidently drive insights while adhering to organizational and regulatory standards.

Use cases¶

Review some use cases that are suited for using the "Talk to My Data" Agent:

• Sales and marketing analytics: Analyze tabular data to perform customer segmentation, churn analysis, campaign effectiveness, ROI from marketing spend, sales pipeline, and customer sentiment analysis.

• Financial analysis: Quickly gain actionable insights with financial analysis to evaluate cash flow, expenses, revenue, and profitability. Leverage demand forecasting to predict future revenue or expenses using historical data, and conduct business performance analysis to assess overall performance and pinpoint opportunities for improvement.

• Supply chain analytics: Optimize operations with insights into inventory management, identifying high carrying costs and opportunities to reduce stock-out without compromising service. Evaluate supplier performance to identify reliable partners consistently delivering quality materials, and improve quality control by addressing manufacturing processes that contribute to defects.

Architecture¶

Each template provides an end-to-end AI architecture, from raw inputs to deployed application, while remaining highly customizable for specific business requirements.

App Templates contain three families of complementary logic. For this template, you can opt-in to fully custom AI logic and a fully custom front-end or utilize DataRobot's off-the-shelf offerings:

• AI logic: Necessary to service AI requests, generate predictions, and manage predictive models.

• App logic: Necessary for user consumption, whether via a hosted front-end or integrating into an external consumption layer.

• Operational logic: Necessary to turn on all DataRobot assets.