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Systems analysis
Map the people, process, data, constraints, and decision points before choosing a technical answer.
Technical Consultant · Systems Analyst · Business Systems Analyst
I turn ambiguous workflows into clear, testable systems.
I connect business context to requirements, data rules, SQL-backed analysis, and practical documentation so the next decision is easier to understand and support.
Capabilities
From operating problem to reviewable evidence
I work across the boundaries between business analysis, implementation detail, and technical validation.
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Requirements and acceptance
Turn ambiguity into explicit rules, scenarios, acceptance criteria, and implementation-ready definitions.
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Data quality and SQL
Preserve source meaning, route exceptions honestly, query controlled data, and reconcile reported results.
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Traceable communication
Connect decisions to source values, rules, tests, and documentation that technical and business readers can use.
Selected work
Workflow Intake Analysis Demo
A practical Python and SQL workflow for turning inconsistent synthetic intake into validated, traceable results.
Featured case study · Synthetic data
Preserve uncertainty instead of manufacturing certainty
I built a workflow that defines the business rules, protects unknown values, separates records that are ready for use from those that need review, and traces each result back to its source.
Evidence snapshot
- Synthetic records
- 30
- Validated
- 21
- Needs review
- 9
- Traceability rows
- 420
Every record stays visible; only records that meet the defined contract enter the validated result.
How I work
Structured enough to trust. Practical enough to use.
I treat analysis as a chain: the business question shapes the rule, the rule shapes the implementation, and the evidence shows whether the result holds.
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Understand the operating context
Identify the people, process, systems, source authority, constraints, and decision boundary.
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Define the contract
Translate ambiguity into requirements, data rules, mappings, assumptions, and acceptance criteria.
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Test the important edges
Preserve exceptions, reconcile outputs, and distinguish supported facts from values that still need judgment.
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Make the result usable
Document the reasoning and evidence so another person can review, implement, or support the work.
Professional background
Business context, translated into technical work
My professional background spans regulated business operations, client-facing problem solving, process discipline, documentation, and technical systems training.
That experience shapes how I work: clarify what a rule means, account for exceptions, document the decision, and leave the next person with something they can use.
Tools and methods
Tools connected to working proof
The case study connects analysis artifacts to a working Python pipeline, SQLite, SQL, schemas, a bounded API contract, and automated checks.
- Python
- SQLite
- SQL
- JSON Schema
- OpenAPI
- Postman
- Git & GitHub
- Requirements
- Acceptance criteria
- Data dictionaries
- Traceability
- Automated testing
Background
Education & Technical Training
My education combines a business foundation with hands-on technical training that supports my work across systems, workflows, data quality, and technical problem solving.
Business foundation
Front Range Community College
Associate of Arts with Business Designation, 2015
Technical training
University of Denver
Cybersecurity Boot Camp, 240-hour completed program, 2022
Coursework
Additional coursework
Additional coursework at Colorado State University and the University of Northern Colorado