Unstructured Data
Data without a predefined format or schema, such as text documents, images, audio, and video.
In-Depth Explanation
Unstructured data lacks a predefined data model or organised structure. It includes text, images, audio, video, and other formats that don't fit neatly into tables and databases.
Types of unstructured data:
- Text: Emails, documents, social media, chat logs
- Images: Photos, scans, diagrams
- Audio: Calls, voice messages, podcasts
- Video: Recordings, surveillance, meetings
- Rich documents: PDFs with mixed content
Challenges:
- No standardised schema
- Difficult to search and query traditionally
- Requires AI/ML for meaningful analysis
- Storage and processing at scale
- Quality and relevance assessment
AI techniques for unstructured data:
- NLP for text analysis
- Computer vision for images
- Speech recognition for audio
- Multimodal models for combined types
- Vector embeddings for semantic search
Business Context
Unstructured data contains valuable insights (customer sentiment, visual defects, spoken feedback) but requires AI to unlock at scale.
How Clever Ops Uses This
We help Australian businesses unlock value from unstructured data using AI - turning documents, conversations, and images into actionable insights.
Example Use Case
"Analysing thousands of customer support emails to identify common issues, sentiment trends, and improvement opportunities."