Tools: Building Ai-powered Data Analytics With Mindsdb Enterprise: From...

Posted on Jan 19

• Originally published at mindsdb.com

Data analytics traditionally requires writing SQL queries, understanding database schemas, and manually creating visualizations. This creates a significant barrier for business users who need insights but lack technical expertise. With MindsDB Minds you could simply ask questions in plain English and receive both answers and charts automatically.

In this tutorial, I will show how to build an AI-powered analytics system using MindsDB Minds that can:

By the end of this tutorial, you'll have a working system that transforms questions like "What's the total sales revenue by product category?" into actionable insights complete with visualizations.

You can install the required packages with the following command:

This tutorial uses a web sales dataset stored in PostgreSQL available in your Minds dashboard. The dataset consists of four related tables that model an e-commerce business:

This schema supports a wide range of analytical questions — from product performance and customer segmentation to shipping analysis and regional trends.

For simplicity and to keep the focus on the Minds features, in this tutorial we used an existing dataset. Readers not familiar with the notion of data sources in MindsDB are invited to read this piece of documentation to learn how to make existing databases available for querying in MindsDB.

To start coding, let's import the necessary libraries for API communication, data handling, and MindsDB client operations:

The OpenAI library will be used as the API for communicating with a Mind. It's a popular choice of API supported by many chatbot and LLM providers. MindsDB supports it as well.

Source: Dev.to