Part 8/13:

• Semantic Tagging in Vectorization: Embedding URIs or data source identifiers with each vector to enhance explainability and traceability.

• Knowledge Graphs: Creating entity-relationship models for organizational data—such as data products, dashboards, KPIs—that facilitate targeted querying.

• Layered Architecture: Combining data ingestion, validation, contextual services (vector store, knowledge graph), and governance tools (like Azure Purview) into a unified system.

Handling Unstructured Data and Vectorization Strategies

Transforming unstructured data involves:

• Text Embeddings and Chunking: Converting PDFs, PPTs, etc., into textual formats for embedding.

• Optical Character Recognition (OCR): Extracting text from images and scanned documents.