We Run Our SDLC Out of Git
We put our entire SDLC in git. Requirements, decisions, task assignments, everything. Then we cancelled standup. Nobody complained. OK, I complained, which is apparently how you get assigned the blog post about it.
Data Pipeline Patterns: A Practical Reference
A practical reference for data pipeline patterns: loading strategies, slowly changing dimensions, change data capture, Lambda, Kappa, and Medallion architecture, reliability fundamentals like idempotency and atomic swap, and orchestration patterns.
Open Source vs. Proprietary Data Platforms: What Oklahoma Companies Actually Need
The hyperscale data platform pitch is compelling, but it was designed for a different customer. Here is an honest look at where open source tools like PostgreSQL, DuckDB, Airflow, and dbt outperform proprietary platforms for most Oklahoma organizations, and when the proprietary option is actually the right call.
Let Your Data Trigger Your DAGs: Airflow Dataset Scheduling
Stop coupling DAGs by time or ExternalTaskSensor. Airflow's dataset scheduling lets you wire pipelines together through the data they produce and consume, so the right DAGs run at the right time without the fragility.
Why Oklahoma Energy Companies Can't Afford to Ignore Data Engineering
Oklahoma energy companies are sitting on enormous amounts of data spread across systems that were never designed to talk to each other. PPDM gives you a standard. Data engineering makes it actually work.
5 Signs Your Oklahoma Business Needs a Data Engineer (Not Just an IT Guy)
We've seen a trend of small-to-mid size Oklahoma businesses outgrowing their data setup. Here's how to tell if it's time to bring in a real data engineer.
Stop Letting Your Airflow Config Live in Someone's Head
If your Airflow Variables, Connections, and secrets only exist in the UI or someone's memory, you don't have a config strategy, you have a time-bomb. Here's how to actually fix that.
Keep Your Pipelines Portable: The Case for Decoupled Airflow
Learn how to build portable, testable data pipelines by containerizing your ETL logic and using Airflow purely as a scheduler, keeping your code independent from any specific orchestration tool.
Streamlining Data Pipelines: Leveraging Distributed Airflow Workers Across Customer Networks
Stop fighting for inbound VPN access. Put your Airflow workers where the data lives and let them call home.
Mastering Meltano
How to Run a Meltano Pipeline with a REST API and PostgreSQL
This guide takes an existing Meltano proof-of-concept and elevates it by using a true data source and target database. We will be working with public REST API endpoints as an extractor, and we will use PostgreSQL as a loader.
Mastering Meltano
How to Build a Docker Image to Run Containerized Meltano Pipelines
Containerize a Meltano EL pipeline with Docker to get a reproducible, self-contained workflow that produces a JSONL artifact.