Python / AI / ML Case Study
Data AnalystAI
Data AnalystAI lets ERP users ask questions in natural language and get answers in text, tables, and dashboards without writing SQL.
- Natural language queries in multiple languages.
- Automatic SQL generation with secure database access.
- Answers delivered in text, tables, and interactive dashboards.
Query automation, multilingual access, and dashboard-ready insights
OpenAI GPT, PandasAI, SQL Server, and AWS analytics tools
3-4 months for integration, AI setup, dashboards, and testing
How this case study was approached
The PDF shows how Data AnalystAI was built to remove the reporting bottleneck for ERP users who depend on SQL knowledge or technical teams for insights.
The solution uses natural language processing, SQL automation, and dashboard generation to return real-time answers in a more accessible format.
Project Goals
What the project needed to achieve
The PDF centers this project on making ERP analytics easier, faster, and more accessible for non-technical decision-makers.
Let business users query ERP data in natural language instead of SQL.
Return secure answers in text, DataFrames, charts, and dashboards.
Support multilingual reporting while keeping query performance reliable.
Solution Approach
How the solution was shaped
The project was shaped around natural language access first, then built out with SQL automation, dashboard output, multilingual support, and security controls.
ERP teams had access to large volumes of operational data, but insight generation was slowed by technical reporting requirements.
Data AnalystAI translated user questions into secure SQL, returned results in multiple formats, and generated dashboard-ready outputs in real time.
The platform reduced reporting delays and made KPI tracking easier for teams that previously depended on manual report generation.
What the work focused on
- Built multilingual natural language query handling for ERP data access.
- Automated SQL generation with secure database permissions and controlled execution.
- Delivered text responses, charts, and dashboard outputs for faster operational reporting.
How delivery stayed structured
- OpenAI GPT and PandasAI for natural language query interpretation.
- Microsoft SQL Server with secure access controls and serverless query execution.
- AWS services for model hosting, dashboards, and infrastructure support.
Why this delivery direction matters
The PDF reports an 80% reduction in report generation time, with sales questions that once took hours answered in seconds and KPI tracking improved in real time.
- 80% reduction in report generation time.
- Sales queries that took hours were answered in seconds.
- Real-time KPI visibility improved strategy and decision-making.
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