Data Analyst AI
Empowering Businesses with AI-Driven ERP Insights
Introduction
DataAnalystAI is an intelligent analytics platform designed to simplify access to complex ERP data. It empowers non-technical users to interact with organizational databases through natural language queries, generating instant insights, reports, and dashboards without requiring SQL or BI expertise. The system bridges the gap between raw data and actionable intelligence for faster decision-making.
Tech stack
- AI/ML - OpenAI GPT API, PandasAI
- Database - Microsoft SQL Server (SSMS)
- Visualization - React, Streamlit, Plotly, Matplotlib
- Cloud (AWS) - RDS, SageMaker, Lambda, IAM, QuickSight
Objectives
Simplify Data Access
Enable users to retrieve ERP insights using simple, conversational language.
Automate Reporting
Reduce manual dependency on SQL and report generation through AI-driven automation.
Enhance Decision-Making
Deliver real-time, visual, and text-based analytics for data-driven business strategies.
Support Multilingual Users
Provide natural language query support in multiple languages to serve global teams.
Ensure Secure and Scalable Analytics
Maintain robust performance, security, and scalability using AWS-based cloud infrastructure.
Development Process
Requirement Analysis
- Identified user pain points in ERP data access and defined key functional goals for AI-based querying.
Data Integration
- Connected ERP databases to Microsoft SQL Server and configured secure access through AWS RDS.
Model Design & Training
- Utilized OpenAI GPT and PandasAI to interpret natural language queries and generate optimized SQL commands.
Backend Development
- Implemented AWS Lambda functions for serverless query execution and SageMaker for AI model hosting.
Frontend & Visualization/h5>
- Built an intuitive React and Streamlit interface for real-time text, table, and chart-based insights.
Multilingual Support
- Integrated multi-language processing to handle global ERP users across different regions.
Testing & Optimization
- Conducted accuracy, performance, and security testing to ensure stable real-time analytics.
Deployment & Monitoring
- Deployed on AWS with IAM-based access control and continuous monitoring for performance and usage analytics.
CHALLENGES
Natural Language Understanding
- Accurately interpreting queries across multiple languages and business contexts.
SQL Optimization
- Generating efficient queries to handle large ERP datasets without performance lag.
Data Accuracy & Relevance
- Ensuring AI responses align precisely with user intent while avoiding irrelevant data.
Security & Access Control
- Managing secure database connections and user-specific data permissions.
Real-Time Performance
- Maintaining speed and reliability during dynamic, on-demand analytics.
Results
Faster Insights
Report generation time reduced by 80%, enabling instant query responses.
Improved Efficiency
Teams could access critical ERP metrics in seconds, enhancing daily operations.
Better Decision-Making
Real-time analytics empowered managers to make data-backed strategic decisions.
Reduced Technical Dependency
Non-technical users gained independence from SQL experts and IT teams.
Enhanced Scalability
The cloud-based architecture supported multiple users and ERP modules simultaneously.
Solution
AI-Powered Query Engine
Implemented GPT and PandasAI for natural language understanding and SQL generation.Automated Dashboard Creation
Designed real-time dashboards that visualize data instantly through user interaction.Secure Cloud Infrastructure
Used AWS services (RDS, IAM, Lambda, SageMaker) for safe, scalable, and serverless execution.Optimized Query Execution
Applied caching and indexing techniques to accelerate data retrieval.Multilingual Support System
Integrated NLP pipelines to process and respond in multiple languages seamlessly.Conclusion
DataAnalystAI transformed ERP data accessibility by eliminating the technical barrier of SQL. The platform empowered decision-makers with real-time insights, improving reporting efficiency by 80% and enabling faster, more informed business decisions.
