Blog
Data Stability with Python: How to Catch Even the Smallest Changes
As a data engineer, it is nearly always the safest option to run data pipelines every X minutes. This allows you to sleep well at night…
Clear signals: Enhancing communication within a data team
Demystifying Device Flow
Implementing OAuth 2.0 Device Authorization Grant with AWS Cognito and FastAPI
Short feedback cycles on AWS Lambda
A Makefile that enables to iterate quickly
Prompt Engineering for a Better SQL Code Generation With LLMs Copy
Picture yourself as a marketing executive tasked with optimising advertising strategies to target different customer segments effectively…
Age of DataFrames 2: Polars Edition
In this publication, I showcase some Polars tricks and features.
Quack, Quack, Ka-Ching: Cut Costs by Querying Snowflake from DuckDB
How to leverage Snowflake’s support for interoperable open lakehouse technology — Iceberg — to save money.
The building blocks of successful Data Teams
Based on my experience I will elaborate on key criteria for building successful data teams
Querying Hierarchical Data with Postgres
Hierarchical data is prevalent and simple to store, but querying it can be challenging. This post will guide you through the process of…
How to organize a data team to get the most value out of data
To state the obvious: a data team is there to bring value to the company. But is it this obvious? Haven’t companies too often created a ...
Becoming Clout* certified
Hot takes about my experience with cloud certifications
You can use a supercomputer to send an email but should you?
Discover the next evolution in data processing with DuckDB and Polars
Two Lifecycle Policies Every S3 Bucket Should Have
Abandoned multipart uploads and expired delete markers: what are they, and why you must care about them thanks to bad AWS defaults.
How we used GenAI to make sense of the government
We built a RAG chatbot with AWS Bedrock and GPT4 to answer questions about the Flemish government.
How we reduced our docker build times by 40%
This post describes two ways to speed up building your Docker images: caching build info remotely, using the link option when copying files
Cross-DAG Dependencies in Apache Airflow: A Comprehensive Guide
Exploring four methods to effectively manage and scale your data workflow dependencies with Apache Airflow.
Upserting Data using Spark and Iceberg
Use Spark and Iceberg’s MERGE INTO syntax to efficiently store daily, incremental snapshots of a mutable source table.