FROM
Manual steps
TO
Working systemData science · analytical tools · automation
Practical Data Science.
From simple analysis to advanced tools.
Data science built around your questions—from a focused analysis or Python tool to statistical models, machine learning, automated workflows, and interactive 3D visualization.
The capability stack
Data science, from question to working tool.
Start with the question. Prepare the data, explore the answer, and build a tool people can use.
Data science at work
Ask. Analyze. Build.
Chapter visuals pair working demos with illustrative workflows. All data is synthetic.
01 / BUILD
Turn questions into analytical tools.
From a focused Python script to a custom application, make analysis useful in everyday work.
02 / CONNECT + AUTOMATE
Make data reliable and analysis repeatable.
Prepare, validate, and connect data. Automate the steps that keep analytical work moving.
Inside the working dashboard
A metric you can trace.
- Generate the facts
Synthetic orders, costs, and dates.
- Check the data
Validate the schema and reconcile totals.
If a check fails → Stop. No metrics are displayed.
- Calculate the metrics
Revenue, direct cost, and direct profit from checked data.
- Explore the result
Charts and tables show the same underlying values.
Illustrated processing path · Synthetic data · Runs in your browser
Explore the dashboard03 / SEE + DECIDE
Analyze, model, and make informed decisions.
Explore patterns with statistics and visualization. Use machine learning and AI where they help answer the question.
Working demo · Synthetic data
Revenue & Profit Pulse
13 complete weeks · Fictional operating business
- Revenue
- $255,425
- Direct profit
- $120,749
Weekly revenue, direct cost, and direct profit from the interactive demo. Direct profit is revenue minus direct cost, not net income.
Separate AI workflow concept
Review before action
Sources and assumptions stay visible. A person makes the decision.
What we design toward
Make the change visible.
Transformation patterns, not unverified client claims.
FROM
Scattered sources
TO
Shared signalFROM
Complex question
TO
Evidence-based decisionFrom simple to complex
Data science in working tools.
Working demos and labelled workflow concepts. All example data is synthetic.
-
A view that fits
Choose KPI cards, date range, and layout in the working Business Dashboard. Synthetic data.
Explore the dashboard -
Assessment to report
Illustrative workflow: collect answers, calculate scores, review findings, and assemble a report.
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Data into insight
The dashboard’s actual processing path: generate data, validate it, calculate metrics, then show charts and tables. Failed checks withhold the output.
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Explore data in 3D
Actual VTK sampler output: 24 generated bins, with 10 flagged below the illustrative 35% level. Synthetic inventory, shown for review.
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Practical AI review
A concept workflow: sources support a draft, a person reviews it, then chooses to approve or revise.
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Code to result
A short Python analysis flags five days in synthetic operating data for human review.
How we work
Begin focused. Build for what comes next.
Start with one valuable problem. Deliver a working result. Expand when the value is proven.
- 01Understand
- 02Design
- 03Build
- 04Integrate
- 05Improve
Relevant experience
Built around operational reality.
- Industrial data-science leadership
- Python and R analytical tools
- Cloud and ERP modernization
- Oil-and-gas and geospatial analytics
- Spotfire experience
- Custom software and workflow automation
- Data integration and decision-support systems
People behind the work
Complex problems.
Practical solutions.
In their words.
Professionals who have worked with Alex Molinar across data science, energy, software, and operations describe the same focus: understanding the problem and building something useful.
Data science
“… one of the most naturally talented data scientists I've ever worked with.”
Workflow improvement
“His ability to quickly assess, improve, and revolutionize workflows and products brought immense value to our team.”
Business intelligence
“His impressive knowledge of the oil and gas industry combined with his determination to excel led him to create valuable BI analysis that helped grow the company and improve operations.”
Personal recommendations about Alex’s work across his career, shared on LinkedIn.
Read more recommendationsFree consultation · Flexible scheduling
What could your data help you do?
Start with one useful question—simple or complex. We’ll help find the practical next move.
Free Consultation hello@dallasdigitaldata.com Please do not include passwords, credentials, private exports, or other sensitive data in your first email.