IST 782 Portfolio

Applied data science as operational control.

My work informs my degree, and my degree informs my work. This portfolio shows how graduate coursework and enterprise practice reinforce each other through analytics, database thinking, workflow design, governance, and communication.

Portfolio thesis: Data science becomes valuable when it stabilizes decisions. The strongest work is not just analysis; it is a repeatable system that helps people see the state of a process, act with confidence, and preserve evidence for later review.

Three system stories

Financial Control System

A fragmented reconciliation process became a structured control workflow. The work combined data cleaning, variance detection, trend logic, audit preparation, and human review.

reconciliation forecast logic audit support

Chemical Compliance System

A high-consequence reporting process became a more reliable review and sign-off system. The focus was traceability, role clarity, compliance evidence, and defensible documentation.

compliance governance review states

Inventory Control System

Expiration-sensitive inventory became a prioritization surface for operational action. The system emphasized FEFO logic, exception review, snapshot evidence, and practical adoption.

FEFO inventory risk decision support

What this portfolio demonstrates

  • Turning messy operational problems into structured data workflows.
  • Designing systems that support human decision-making instead of replacing it.
  • Using evidence, documentation, and traceability as part of the analytic product.
  • Connecting coursework to real implementation patterns.

Public-safety boundary

The portfolio intentionally avoids proprietary code, internal data, production screenshots, exact financial values, internal system names, customer/vendor details, and protected operational identifiers.

The evidence shown here is generalized, sanitized, or synthetic by design.