Mind the Gap: Bridging PDFs and SQL Server with AI

Every organization has valuable data trapped in PDFs - from invoices to medical records to compliance documents. This session demonstrates a practical solution using OpenAI's Structured Outputs, PowerShell, and SQL Server to automate this tedious process.

Through live demonstrations, I'll show you how to build a reliable pipeline that extracts data from PDFs and loads it directly into SQL Server tables. You'll see real examples using veterinary records, but the techniques apply to any PDF-based data. We'll explore how to handle common challenges like inconsistent formatting and missing data, and discuss strategies for improving accuracy.

The session includes practical demonstrations of:
- Converting PDFs to structured text using AI
- Creating effective JSON schemas for data validation
- Building a PowerShell pipeline for automated processing
- Loading the extracted data into SQL Server

You will learn:
- How to implement OpenAI's Structured Outputs for data extraction
- Techniques for validating and cleaning AI-extracted data
- Methods for handling arrays and nested data structures in PDFs
- Tips for optimizing AI accuracy and reducing processing time
- Best practices for automating PDF-to-SQL workflows

This session is for database professionals looking to automate manual data entry from PDFs. Learn how AI can replace hours of copying and pasting with an automated solution.

- Build an automated pipeline to extract data from PDFs into SQL Server using AI and PowerShell, eliminating manual data entry. - Use OpenAI's Structured Outputs to ensure reliable, validated data extraction from unstructured documents. - See how easy AI implementation can be—it’s mostly JSON schemas and PowerShell, and you already have the skills to do it.