What types of data are collected and analyzed in an eDiscovery platform?
Structured Data
- Data stored in relational databases, spreadsheets, or enterprise systems
- Includes customer records, financial transactions, CRM entries, and log files
- Often used to demonstrate timelines, system activity, or user behavior
- Requires normalization for analysis within eDiscovery workflows
- Enables pattern detection, fraud analysis, and regulatory compliance reviews
Unstructured Data
- Free-form content such as emails, documents, PDFs, and text files
- Includes contracts, memos, reports, and legal correspondence
- Represents the majority of data processed in legal investigations
- Requires indexing, keyword searching, and metadata extraction
- Often analyzed for intent, communication history, and policy violations
Communications Data
- Emails, instant messages, chat logs (e.g., Slack, Teams, WhatsApp)
- Captures conversations between custodians and stakeholders
- Key for investigating internal fraud, harassment, or collusion
- Includes timestamps, attachments, and participant metadata
- Enables sentiment analysis and communication mapping
Multimedia and Rich Media Content
- Audio files (calls, recordings), video footage (security, Zoom), and images
- Often collected in workplace misconduct, surveillance, or IP theft cases
- May require transcription, redaction, or voice recognition processing
- Can contain metadata such as location, device, and timestamps
- Supports cross-referencing with written communications and file access logs
System and Metadata Logs
- Metadata such as file creation dates, access logs, IP addresses, and user actions
- Provides context to who accessed, modified, or deleted documents
- Tracks document version history, permissions, and transfer records
- Critical for proving chain of custody and authenticity of evidence
Supports technical forensics in data breach or insider threat cases