Part 8/13:
AI tools, especially language models like LLMs, now rapidly extract data elements from unstructured sources such as invoices, contracts, customer reviews, and PDFs. This automates data ingestion, reducing manual effort and accelerating availability.
2. Data Quality and Cleaning
AI-powered algorithms can detect inconsistencies, duplicates, and errors across massive datasets, performing automated data validation and cleansing. This ensures high-quality data feeds into subsequent stages.
3. Data Modeling and Harmonization
Generating unified data schemas and source-to-target mappings has traditionally been laborious. AI facilitates schema inference and data harmonization, aligning diverse datasets into cohesive data models with minimal human intervention.