# Vertex Software Solutions — Help Desk Dataset

Vertex Software Solutions is a B2B SaaS company providing workflow and data management software to mid-market and enterprise customers. The support operation handles 12,000 historical tickets across 3,000 customer accounts, staffed by 140 agents across four teams (Billing, Customer Success, Engineering, Support). The customer base spans Standard, Professional, and Enterprise tiers, each with distinct SLA commitments.

## File Inventory

| File | Format | Records | Description |
|------|--------|---------|-------------|
| customer_accounts.csv | CSV | 3,000 | Customer accounts with tier, region, industry, contract value, and status |
| agents.csv | CSV | 140 | Support agent roster — unified ID space used across tickets, history, and audit log |
| tickets.csv | CSV | 12,000 | Support tickets with dates, tier-driven priority/SLA, category-routed team, and KB link |
| escalations.csv | CSV | 950 | Escalation records, overwhelmingly High/Urgent priority tickets |
| ticket_history.json | JSON | 12,000 | Chronological event pipeline per ticket (creation → assignment → resolution) |
| agent_notes.txt | TXT | 6,553 | Category-specific diagnostic and resolution notes, tagged to ticket/agent/time |
| knowledge_base.md | MD | 19 articles | Distinct troubleshooting articles, one or more per ticket category |
| sla_reports.xlsx | XLSX | 42 months + breakdowns | SLA compliance by month, account tier, and category — derived directly from tickets.csv |
| audit.log | LOG | 22,000 | System audit trail with timestamps, unified agent IDs, and target entities |

## Date Range

Tickets, ticket history, agent notes, and the audit log span **January 2023 – June 2026**, with ticket volume growing over time reflecting business growth.

## SLA Tiers

| Tier | First Response Target | Resolution Target |
|------|----------------------|-------------------|
| Enterprise | 4 hours | 24 hours |
| Professional | 8 hours | 48 hours |
| Standard | 24 hours | 72 hours |

Enterprise tickets resolve faster and breach SLA less often (~16.5%) than Standard tickets (~25.6%), reflecting better-resourced handling for higher-value accounts.

## Support Workflow

```
Ticket Created → Agent Assigned → [Status Updates / Customer Replies] → [Engineering Review, if technical] → Resolution Provided
                                              ↓
                                   Escalation (if High/Urgent + SLA risk, priority account, or repeated failure)
```

## Key Relationships

- `tickets.customer_id` → `customer_accounts.customer_id`
- `tickets.agent_id` → `agents.agent_id`
- `tickets.kb_article_id` → `knowledge_base.article_id`
- `escalations.ticket_id` → `tickets.ticket_id`
- `ticket_history.ticket_id` → `tickets.ticket_id`
- `audit.agent_id` → `agents.agent_id`

## ID Format Conventions

| Prefix | Entity |
|--------|--------|
| CUS | Customer Account |
| TKT | Ticket |
| AG | Agent (unified across tickets, ticket_history, escalations, and audit.log) |
| ESC | Escalation |
| KB | Knowledge Base Article |
| AUD | Audit Log Event |

## Notes

`agents.csv` resolves what was previously two incompatible identifier systems (AG-prefix in ticket history, USR-prefix in the audit log) into one unified agent roster used consistently across all agent-attributed records.
