About

👋 I’m Fari Lindo — founder and creator of Data Inside Data™.

I’m a systems-focused technologist working across IT infrastructure, cybersecurity, cloud engineering, data science and engineering, analytics, and automation. I believe learning is a lifelong practice — and that the most effective way to grow is by building real systems, solving real problems, and reflecting on the process openly.

My work centers on one core principle:

Build real systems. Document the thinking. Share the process.

Data Inside Data™ is where I design, build, and ship technical systems — from early experiments to production-ready workflows. It’s a living workspace where ideas move from concept to execution, and where complexity is broken down into structured, practical steps.

Whether you’re just starting out or already deep in the tech stack, my goal is simple:
make advanced systems understandable, repeatable, and usable in real-world environments.

🏗 Systems Philosophy My work centers on building real systems and documenting the thinking behind them. DataInsideData™ reflects a documentation-first engineering approach where projects, experiments, and infrastructure builds are structured so others can understand, reproduce, and extend them.

What I Share Here

• Real projects that reflect my experience and ongoing pursuits
• Deep‑dive breakdowns of each project’s development process
• Beginner‑friendly tutorials for those entering tech
• Advanced content for experienced builders
• Tools, diagrams, and workflows that mirror real‑world engineering environments

This site serves as both a teaching space and a living archive — documenting what I build, what I learn, and how systems evolve from concept to production.

💡 Documentation Approach Projects on this site are designed to mirror real engineering environments. Whenever possible, the documentation connects directly to the underlying GitHub repositories, code structure, and system architecture used to build the project.

This site is intentionally hands-on, architecture-aware, and grounded in real-world problem solving, not theory alone.

My Work Operates at the Intersection of

• Data science, analytics engineering, & databases
• Full-stack & systems development (web, tooling, automation)
• Cloud, DevOps/DevSecOps
• IT & infrastructure (hardware, OS, networking)
• Documentation-driven engineering
• Impact-oriented systems (education, nonprofit, etc.)

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⚙️ Technical Path The diagram below traces the evolution of my work across infrastructure, software development, cloud systems, data analytics, and AI engineering.

It highlights the environments, training, and projects that shaped my approach to building, analyzing, and documenting technical systems.

flowchart TB

  %% ----------------------------------
  %% Track 1 — Infrastructure & Cloud -
  %% ----------------------------------
  subgraph T1["Infrastructure & Cloud"]
    A["2020 | Windows Server 2012R2"]
    B["2023 | BMCC A+ Training"]
    C["2024 | AWS CCP Training"]
    A --> B --> C
  end

  %% --------------------------------
  %% Track 2 — Software Development -
  %% --------------------------------
  subgraph T2["Software Development"]
    D["2024 | Revature Java + SQL"]
  end

  %% -----------------------------
  %% Track 3 — AI & Data Systems -
  %% -----------------------------
  subgraph T3["AI & Data Systems"]
    X["2023 | Fullstack Academy<br/>Data Analytics Cohort"]
    E["2024 | Udacity AI/ML Nanodegree"]
    F["2024 | AWS Racing League"]
    G["2025 | The Knowledge House<br/>Data Science Fellowship"]
    X --> E --> F --> G
  end

  %% -------------------------
  %% Track 4 — Platform Launch
  %% -------------------------
  subgraph T4["DataInsideData™ Platform"]
    I["2026 | DataInsideData.com Launch"]
  end

  %% -------------------------
  %% Cross-track progression
  %% -------------------------
  C --> D
  D --> X
  G --> I

📌 This diagram evolves as new milestones are added. It reflects a systems map of my technical path rather than a fixed timeline.

🏅 Certifications & Credentials

These credentials reflect both formal training and hands-on application across data, cloud, and infrastructure systems.

☁️ AWS Certified Cloud Practitioner

Issued: March 2025

• Core AWS services
• Cloud security & shared responsibility
• Cost-aware infrastructure design

📄 View Certificate (PDF)

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🛠 CompTIA A+ Certification

Issued: March 2025

• Hardware & operating systems
• Networking fundamentals
• Troubleshooting & system reliability

📄 View Certificate (PDF)

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🎓 The Knowledge House Fellowship — Data Science Track

New York City

2025 Cohort

An intensive fellowship focused on:

• Applied Python & SQL
• Machine learning foundations to expert
• Real client-facing analytics projects
• Communicating insights to non-technical stakeholders

📄 View Certificate (PDF)

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📊 Google Data Analytics Certificate

Coursera Professional Certificate

Focus areas:

• Data wrangling & analysis
• SQL & dashboards
• Business-focused insights

🔗 Program details

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🧭 How to explore this site

• Projects → Architecture, systems, and case studies
• Posts → Tutorials, breakdowns, and lessons learned
• Start Here → Guided entry points based on your goals

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🤝 Let’s connect

If you’re interested in collaboration, consulting, or just exchanging ideas:

📩 visit the Contact page.

Data Inside Data™ is not just a blog — it’s a workspace.

Thanks for being here.