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Problem

Career Services data lives across multiple exports, service lines, and reporting conventions. As a result, leadership decisions required repeated manual reconciliation and inconsistent definitions. The goal was to create a single, decision-ready reporting system spanning appointments, events, employer engagement, platform adoption, and outcomes.

Approach

  • Extracted and consolidated PLM CSV exports into a single reporting-ready dataset using repeatable ETL logic.
  • Defined standardized KPI logic and time windows (last 12 months, totals, unique counts).
  • Authored a data dictionary to align definitions across teams and reduce reporting ambiguity.
  • Designed a recurring report structure covering student support, programs, employer pipeline, and outcomes.

Scope

Multi-year reporting across Career Management, Industry Relations, and Operations/Infrastructure, with consistent KPI definitions and reusable reporting logic.

KPI groups (report structure)

Appointments

  • Completed appointments trend (last 12 months)
  • Total students helped
  • Appointment types and totals
  • In-person vs Zoom split

Programs & Events

  • Orientations and presentations (totals and attendance)
  • Workshops count and attendance
  • Event totals and employer participation

Employer Development

  • Approved employers and new employer contacts (last 12 months)
  • Employer orientations vs goals
  • Employers at events and totals

Platforms & Adoption

  • Unique logins (last 12 months)
  • Student profile completions (last 12 months)

Outcomes & Opportunities

  • Workability-IV enrollments and placements
  • Handshake postings, openings, and job types
  • Aztec Mentor Program counts, matches, and industry breakdown
  • Career fair check-ins and totals

Note: Code artifacts are intentionally not public due to institutional data sensitivity. This case study focuses on workflow design, KPI logic, and decision-ready reporting structure.