AI command center · data mission control

M.S. Analytics

AI Product & Business Analyst

Product, data, and AI systems work for decision intelligence: SQL-backed analytics, product strategy, business analysis, and applied AI use cases.

Explore BudgetDB View systems

Ask about BudgetDB, churn, spend, dashboards, SQL QA, or agent workflows

Where is operational spend concentrated?Which teams are driving software cost?What changed in churn this month?Show SQL QA failures before the exec review.Summarize dashboard risks for leadership.

Decision pipeline

Raw data to operating intelligence

Raw business data

CSV exports, budget workbooks, vendor spend, product usage, support data.

Postgres analytics warehouse

Cleaned tables, composable views, spend allocation, QA checks, metric definitions.

Dashboards and reporting

Executive KPI surfaces, product analytics, operating reviews, decision-ready readouts.

AI insight layer

Natural-language questions, structured summaries, guardrails, workflow automation.

Product systems signal

Product thinking, business impact, technical analysis, and AI system design.

31+

SQL views and checks

BudgetDB-style warehouse logic, executive views, and QA validation.

98%

QA pass target

Reconciliation-first thinking for trusted business reporting.

30%

manual reporting reduction

Automation mindset across reporting, dashboards, and recurring analysis.

10K+

engagement lift analyzed

Product analytics, retention, churn, funnels, and stakeholder reporting.

Flagship system

BudgetDB is the center of the portfolio.

The site is structured around a real systems-builder story: operational data, Postgres modeling, QA, dashboards, and AI-assisted decision support.

Flagship system

BudgetDB Operations Analytics Warehouse

Flagship

A Postgres-backed operations analytics system that turns budget, vendor, software spend, and headcount data into trusted executive views.

Business question

Where is operational spend concentrated, and how should leadership prioritize the next planning cycle?

Creates a reusable decision layer: cleaned tables, composable views, spend allocation, QA checks, and executive-ready outputs.

PostgreSQLBudget AnalysisOperations AnalyticsExecutive Reporting

Software cost SQL G&A Budget Workbook Financial Model

Open system profile

BudgetDB Operations Analytics Warehouse preview

Mission control

A portfolio that behaves like a system surface.

Each section is built around the decision layer: data model, dashboard, AI workflow, and business question.

Dashboards

Executive KPI Dashboards

Live

Dashboard views for contact center performance, revenue mix, product trends, and executive operating reviews.

Business question

What does leadership need to see quickly to understand performance, variance, and where to investigate?

Makes KPI patterns easier to scan and turns analysis into a review-ready operating surface.

TableauKPIsRevenueSupport Operations

Contact center dashboard Revenue dashboard

Open system profile

Analytics engineering

Cost Model QA Checks

Live

SQL validation checks comparing source totals to modeled fact totals by cost category, with variance and pass/fail status.

Business question

How can messy operational data become reliable product and business reporting we can trust?

Adds confidence gates before dashboards and executive summaries are used for decisions.

SQLPostgreSQLData QAReconciliation

SQL demo file

Open system profile

Python modeling

Customer Churn Predictive Analysis

Live

A reproducible Python workflow for churn analysis: loading, target conversion, missing-value handling, encoding, baseline modeling, and reporting.

Business question

Which customers are most likely to churn, and how can we monitor the pattern repeatedly?

Frames predictive analysis as a repeatable business workflow instead of a one-off notebook.

PythonPandasScikit-learnPredictive Modeling

Python script

Open system profile

Customer Churn Predictive Analysis preview

Systems capabilities

Product analytics, AI systems, agents, and business execution.

The positioning is intentionally broader than a resume: it shows how product analytics, business analysis, and AI architecture come together.

BudgetDB analytics warehouse

Postgres models, budget tables, spend allocation, QA checks, and executive-ready views for operations analytics.

PostgresCTEsData QA

Executive dashboards

Leadership reporting surfaces for product, revenue, support, budget, and operational health.

TableauKPIsStorytelling

AI-assisted workflows

Natural-language-to-SQL concepts, prompt systems, insight layers, and grounded analysis workflows.

NL to SQLRAGAutomation

Agent architecture

Design patterns for internal ops assistants, tool routing, validation loops, and multi-step task decomposition.

AgentsGuardrailsTools

Real code

Proof is shown as code and system logic, not screenshot decoration.

BudgetDB is supported by SQL models, QA checks, and notes that explain how the data system becomes decision infrastructure.

Code proof

View SQL file View code

1CREATE VIEW analytics.v_software_cost_per_employee_company_2025 AS2WITH employee_count AS (3  SELECT COUNT(*)::int AS total_employees_20254  FROM analytics.dim_employee5  WHERE (start_date IS NULL OR start_date <= '2025-12-31'::date)6    AND (end_date IS NULL OR end_date >= '2025-01-01'::date)7),8company_spend AS (9  SELECT SUM(COALESCE(total_spend_2025, 0))::numeric AS total_software_spend_202510  FROM analytics.vendors_2025_clean11)12SELECT13  c.total_software_spend_2025,14  e.total_employees_2025,15  ROUND(c.total_software_spend_2025 / NULLIF(e.total_employees_2025, 0), 2)16    AS software_cost_per_employee_202517FROM company_spend c18CROSS JOIN employee_count e;

Product and business credibility

Product, business, and operations analysis with AI systems thinking.

Built analytics systems across product, operations, budget, and executive reporting workflows.

Designed product and operational metrics frameworks for performance, efficiency, and user impact.

Used SQL, Python, dashboards, and LLMs to reduce manual reporting and accelerate insight generation.

Partnered across product, operations, finance, support, and leadership to translate data into decisions.

Internal Ops Assistant

A chat-style assistant concept that lets leadership ask questions against trusted budget, vendor, payroll, and employee cost data.

SQL QA Agent

Agent pattern for checking source totals, modeled facts, variance thresholds, and dashboard readiness before reporting.

Chorus Product Prototype

In-development iPhone and web product for learning AI agent fundamentals, comparing platforms, and saving reusable skills.

Future platform foundation

Chorus, agents, models, and experiments have a place to grow.

Dedicated coming-soon pages are already planned so the portfolio can expand into products, tools, templates, and AI systems over time.

Agents Models Experiments

Need analytics systems, AI workflows, or decision infrastructure?

I am building toward roles and collaborations across product analytics, business analysis, operations analytics, AI systems, and agent-enabled workflows.

Start a conversation