We help you climb the data maturity ladder
Scaling for success with data and AI
Give your data team magical powers
Granting your data team supernatural capabilities for unrivaled insights and innovation
Data Strategy
A solid data strategy, architecture and infrastructure allow organizations to focus efforts on where it matters most i.e. value creation.
Gen AI
GenAI offers a transformative pathway for businesses, empowering them with unparalleled efficiency, insights, and competitive advantage.
Data Platforms
A data strategy translates the corporate and digital strategy for your data organization, while a data architecture study clarifies how to implement it.
93
Clients
138
data initiatives delivered
400+
people trained
365+
Conveyor projects
Learning/Knowledge base
Take a deeper dive
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
The building blocks of successful Data Teams
During my 7 years of experience in the field of data, I have worked in multiple data teams of which some were successful but others…
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…
Learning/Knowledge base
Take a deeper dive
Simplifying Data Management: Introducing the Data Product Portal
Join us for an exclusive webinar hosted by Kris Peeters and Wannes Rosiers as they unveil the Data Product Portal.
Webinar: "Initial Reactions: Market Insights on the Data Product Portal"
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
The impact of product thinking for data
Data governance has been changing throughout the years, and the adoption of product thinking to data once again introduces change to data...
Short feedback cycles on AWS Lambda
A Makefile that enables to iterate quickly
Sustainable GenAI: Technology, Data and Governance
Join us for an event focused on the crucial aspects of GenAI development and its implementation.
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…
Data Engineering Summer School 2024
Learn data engineering from the pros!
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
GenAI: Hands-On LLM Hackathon
An interactive, hands-on hackathon on building and deploying an entire LLM-based application from start to finish.
Conveyor x Luminus Event: "Fast lane to data value. Embracing platform and product thinking"
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.
Decentralized vs Centralized: How to organize your data teams?
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.
State of Data 2024
Future-Proofing Your Data Engineering Career. Essential Skills for 2024 and Beyond
Embark on a journey with our top-tier Data Engineers as they unveil the key skills that will shape the future of data engineering.
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.
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
The building blocks of successful Data Teams
During my 7 years of experience in the field of data, I have worked in multiple data teams of which some were successful but others…
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…
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The best companies drive digital process adoption with Dataminded
ML scalability
Introducing cloud for doing ML training at scale
Cloud data platform
Scaling advanced analytics to continuously improve customer experience of media products
SAAS product
Setting up a SaaS product on AWS. Leveraging cloud scalability to meet client demand.
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“Success to resolve my issue quickly and efficiently, and their friendly and helpful made the experience even better.”
Dave Debryne
Creative Director @Placeholder
“Success to resolve my issue quickly and efficiently, and their friendly and helpful made the experience even better.”
Ryan Call
Creative Director @Placeholder
“Their team was able to identify the most effective keywords and create ads that spoke directly to our target audience.”
Jenny Wilson
CEO Founder
“Success to resolve my issue quickly and efficiently, and their friendly and helpful made the experience even better.”
Dave Debryne
Creative Director @Placeholder
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ML scalability
Introducing cloud for doing ML training at scale
Cloud data platform
Scaling advanced analytics to continuously improve customer experience of media products
SAAS product
Setting up a SaaS product on AWS. Leveraging cloud scalability to meet client demand.