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Modern Data Stack Engineering

Comprehensive coverage of building, optimizing, and scaling modern data architectures using cloud-native tools like Databricks, Snowflake, and dbt.

The articles and projects here focus on practical implementation—medallion architecture patterns, cost optimization, pipeline design, and choosing between platforms like Databricks and Snowflake. If you're building or evolving a data platform, this is where to start.

Articles

Beyond the Spin: Building a Creative Loading Bar in Streamlit for Better UX

case study ·
When Databricks queries take 5–20 seconds, a static orange banner feels like an error. Swap in a branded Automower animation with the same Streamlit context-manager API.

LINHAC 2026 — Conference Report

field note ·
LINHAC 2026 confirmed a clear shift: hockey analytics is becoming core infrastructure, not a side project. This report summarizes the strongest research signals, practical club examples, and what organizations should prioritize next.

22 Articles in 26 Days: Session Data, Keywords, and What the Automation Actually Produces

case study · · Updated
Four weeks of build in public: 22 n8n tutorials published, 951 sessions, 38 ranked keywords, and 2 top-10 rankings — without a single external backlink. Here are the numbers, without spin.

n8n Split in Batches Node: Processing Large Datasets Without Hitting Rate Limits

tutorial · · Updated
When you need to process thousands of records in n8n, feeding them all at once into an API or database crashes the workflow or triggers rate limits. The Split in Batches node is how you process large datasets reliably — here is how it actually works.

Agentic Data Organisation: How I Set Up an AI-Driven Data Organisation with Claude

case study · · Updated
A practical walkthrough of my agentic data organisation: roles, ownership, agent coordination, and how Claude drives decision flow across analytics, platform, and governance.

n8n Merge Node Modes Explained: Combine, Multiplex, and Pass-Through Under Partial Input

tutorial · · Updated
The n8n Merge node has four modes with subtle behavior differences that only surface with partial input, mismatched item counts, or timing gaps between branches. Here is what each mode actually does.

n8n Error Trigger: Workflow-Level Error Catching and When It Actually Fires

tutorial · · Updated
The n8n Error Trigger node is a workflow that runs when another workflow fails — but the when and why are full of edge cases. Here is how it actually works, what it misses, and how to build reliable error handling in production n8n.

From Raw Data to Revenue Decisions: Building an End-to-End Analytics Platform

case study ·
How I designed and shipped a full-stack data intelligence system for a global manufacturing company — from Databricks pipelines to AI-powered dashboards.

From BI Reporting to Data-Driven Automation: A 10-Year Evolution of Data Strategy

analysis ·
How data strategy evolved from static BI reports to AI-powered automation. Learn from 10 years of data engineering experience: from centralized reporting to data mesh, and why making AI investments pay for themselves requires collapsing legacy and modern stacks.

Beyond Dashboards: How to Build Living Data Experiences with Conversational Analytics

analysis ·
Dashboards fail because they require users to go somewhere else. Data prototyping expertise: learn how proactive insights and conversational analytics replace traditional dashboards with living data experiences.

Integrating APIs with n8n: A Simplified Approach to Workflow Automation

tutorial ·
As an agentic engineer, I've worked on numerous projects that involve integrating multiple APIs to create seamless workflows. ...

Projects

Enterprise ML & Data Platform — 100 Jobs, 631 Tables, NLP at Scale

production
End-to-end data and ML platform for a global manufacturing company. 100 Databricks jobs, 631 Unity Catalog tables, support intelligence across 1.46M cases, production churn models, demand forecasting, and a 17-page Streamlit dashboard — built and operated solo over three years.

End-to-End Analytics Platform — Databricks, Streamlit & GPT-4o

production
Full-stack data intelligence system for a global manufacturer. Medallion architecture on Databricks, AI-powered natural language querying, z-score anomaly detection, and 10 production dashboards covering 14 markets — shipped in 12 weeks.

Conversational Analytics Prototype - Beyond Dashboards

prototype
Interactive prototype demonstrating the future of data analytics: natural language queries, proactive insights, and zero-training data exploration. Built to show what comes after traditional dashboards.

MCP-Connected Development Workflow for Data-Informed Prototyping

prototype
Connected Claude to analytics, research, strategy, and design context through MCP to build React prototypes inside the development environment.

From SLA Reporting to Proactive IT Operations

historical
A Power BI and SQL analytics layer for finding patterns in ServiceNow data and turning SLA reporting into operational improvement.

Food-Waste Marketplace MVP with Django

historical
An early full-stack marketplace connecting consumers with surplus food from local restaurants and grocery stores, built as a focused Django and Bootstrap MVP.

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