Lopez Data Works

Data systems built from real operational problems.

I build production-style data pipelines, automation workflows, dashboards, APIs, and analytics tools that make messy business data usable, reliable, and decision-ready.

Operational architecture

From source to decision

Live-ready

Controlled data pipeline

Five connected stages turn fragmented operational inputs into governed, decision-ready outputs.

01

Ingest

APIsFilesEvents
02

Standardize

CleanMapNormalize
03

Model

ETL / SQLBusiness logic
04

Control

QAAuditExceptions
05

Deliver

DashboardsAPIsApps

Control plane

Reliability and traceability across every stage.

Schema checksState trackingAudit evidenceException handling

Decision layer

The system ends with outputs people can act on.

DashboardsReportsData filesAPIsOperational apps

Operational result

Repeatable execution, visible controls, and outputs designed for the next decision.

ReliableTraceableActionable

Flagship systems

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Selected builds that show the full pattern: messy inputs, automation, validation, reporting, and a usable business outcome.

OrderTime Cloud ETL & Inventory Intelligence Platform visual
Flagship

Cloud ETL Platform

Cloud-ready ETL and analytics platform that transforms fragmented OrderTime operational data into governed, analytics-ready datasets for inventory, procurement, and reporting decisions.

PythonAzure SQLETLDocker
Power BI Inventory Intelligence Dashboard & Semantic Model visual
Flagship

Power BI Inventory Dashboard

Power BI semantic model and inventory dashboard suite that turns stock health, replenishment, procurement, velocity, and deadstock analytics into one connected decision layer.

Power BIDAXPower QuerySemantic Modeling
Procurement Intelligence & Replenishment Automation visual
Flagship

Procurement Intelligence

Procurement intelligence engine that turns fragmented inventory, sales, vendor, pricing, and receipt signals into action-ready replenishment recommendations.

PythonPandasSQLCSV
CCC Stateful Insights & Incremental Reporting Pipeline visual
Flagship

CCC Stateful Insights

Stateful reporting pipeline that detects new and changed CCC quote runs, tracks processing history in JSON state, and refreshes downstream analytics only when operationally necessary.

PythonJSON StatePowerShellExcel
Pegasus AI Analytics Copilot & SQL-Safe Query Assistant visual
Flagship

AI Analytics Copilot

AI-guided analytics workspace that helps users ask operational questions, routes requests through controlled tools, and returns structured answers through a SQL-safe decision layer.

FastAPIReactOpenAI APIAzure SQL
Pegasus Ops Analytics API & Executive Dashboard visual
Flagship

Ops Analytics API

Operational analytics layer that turns KPIs, trends, alerts, and export-ready outputs into a reusable FastAPI backend and an executive-friendly dashboard experience.

FastAPIAzure SQLT-SQLTailwind
PartsTrader Monthly Reporting Pipeline & Changed-Only Orchestrator visual
Flagship

PartsTrader Monthly Pipeline

Monthly reporting orchestrator that uses a stage registry, dependency graph, manifests, dry-run planning, and JSON state to run only the work that needs to be refreshed.

PythonCLIJSON StateExcel
Pegasus Scanner — Inventory Scanning & Cycle Count App visual
Flagship

Pegasus Scanner

Inventory scanning and cycle-count application that turns scanner input, BIN-based counts, receiver checks, and export-ready audit records into a controlled warehouse workflow.

FastAPIHTML/JSAzure SQLBarcodeDetector

How I build systems

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Every build follows the same discipline: understand the operational problem, engineer the workflow, validate the output, and deliver something people can actually use.

01

Understand the work

Diagnose

Start with the business problem, the workflow friction, the data sources, and the decision that needs to improve.

02

Build the system

Engineer

Design the pipeline, SQL model, workbook engine, dashboard, API, scanner flow, or automation layer around the real process.

03

Make it reliable

Validate

Add checks, audit trails, state tracking, exception handling, and quality logic so the output can be trusted.

04

Make it usable

Deliver

Turn the system into decision-ready outputs: dashboards, files, alerts, reports, apps, or stakeholder delivery workflows.

Capability map

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A practical skill map across Python, SQL, Power BI, APIs, automation, analytics engineering, and the operational domains where those tools create value.

Analytics & BI

Deadstock analytics, markdown logic, and trend comparison workbooks

Deadstock Classification Markdown Recommendation Logic Two-Run Trend Workbooks

Automation

Customer sales analytics and Excel reporting automation

Weighted profitability modeling Excel workbook generation Period-over-period analysis

Analytics & BI

Power BI semantic modeling and operational dashboard design

Multi-page BI design DAX measure engineering Semantic model structure

Analytics & BI

Market analytics, forecasting models, and decision-support dashboards

Financial Data Extraction Forecasting & Signals Interactive Analytics UI

Automation

Webhook API design and event logging

Webhook Receivers Payload Validation Event Persistence

Analytics & BI

Weekly file generation, audit workbooks, and partner-ready exports

Inventory Export Automation Audit-Ready Workbooks Stakeholder Delivery

Build record

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Browse the complete 30+ build record by domain, system type, and technology stack — from ETL pipelines and dashboards to pricing engines, scanners, and AI-assisted tools.