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No.
Date
Title
Written by
Topics
01
Fri Mar 20 2026
From PySpark Notebook to Production-Ready Code
Alexandr Koryachko
  • Data Engineer
  • Data Science
  • Machine Learning Engineering
02
Mon Mar 9 2026
Introducing  counterfactual analysis and why it matters for your AI systems
Martijn Di Bucchianico
  • Data & AI Solutions
  • Data & AI Strategies
03
Tue Dec 2 2025
Databricks, Fabric, or Snowflake: How Your Engineering Experience Changes
Kasper Uleman
  • Analytics Engineering
  • Data Engineer
  • Data Platforms
  • Machine Learning Engineering
04
Fri Oct 17 2025
Slash Your Cloud Data Costs: 11 Proven SQL Optimization Techniques
Ally Mashaura
  • Analytics Engineering
  • Data Platforms
05
Fri Oct 10 2025
Power BI best practice: CI/CD Pipelines
Jessica Eggen
  • Analytics Engineering
  • Data Engineer
06
Thu Aug 28 2025
Databricks, Fabric, or Snowflake: The Big Three Explained
Richard Kooijman
  • Analytics Engineering
  • Data Engineer
  • Data Platforms
  • Machine Learning Engineering
07
Thu Jul 3 2025
Navigating the European Cloud Landscape: Open Telekom Cloud, STACKIT, and OVHcloud in Focus
Richard Kooijman
  • Data Platforms
  • EU-Cloud
08
Tue Jun 17 2025
Is self-hosted analytics database Databend the EU-based alternative to Snowflake?
Richard Kooijman
  • Data Platforms
  • EU-Cloud
09
Tue Jun 10 2025
How to transform any website into a chatbot using LLMs?
  • Data Science
  • Generative AI
10
Thu Jun 5 2025
Recent developments on AI protocols: MCP and future possibilities
Sinan Polatoglu
  • Agentic AI
  • Data Science
  • Generative AI

From PySpark Notebook to Production-Ready Code

The gap between a working notebook and maintainable production code is significant, especially in teams where people specialize in different parts of the project lifecycle. Situations where data scientists throw a proof-of-concept notebook over the...

Written by

  • Alexandr Koryachko

Topics

  • Data Engineer
  • Data Science
  • Machine Learning Engineering
See more

Introducing  counterfactual analysis and why it matters for your AI systems

Written by

  • Martijn Di Bucchianico

Topics

  • Data & AI Solutions
  • Data & AI Strategies

Databricks, Fabric, or Snowflake: How Your Engineering Experience Changes

Written by

  • Kasper Uleman

Topics

  • Analytics Engineering
  • Data Engineer
  • Data Platforms
  • Machine Learning Engineering

Slash Your Cloud Data Costs: 11 Proven SQL Optimization Techniques

Written by

  • Ally Mashaura

Topics

  • Analytics Engineering
  • Data Platforms

Power BI best practice: CI/CD Pipelines

Written by

  • Jessica Eggen

Topics

  • Analytics Engineering
  • Data Engineer

Databricks, Fabric, or Snowflake: The Big Three Explained

If you work in data engineering or cloud analytics, you’ve probably heard debates about Databricks, Microsoft Fabric, and Snowflake. Once upon a time, each platform solved a distinctly different problem: Databricks was the go-to for managed, code-fi...

Written by

  • Richard Kooijman

Topics

  • Analytics Engineering
  • Data Engineer
  • Data Platforms
  • Machine Learning Engineering
See more

Navigating the European Cloud Landscape: Open Telekom Cloud, STACKIT, and OVHcloud in Focus

Written by

  • Richard Kooijman

Topics

  • Data Platforms
  • EU-Cloud

Is self-hosted analytics database Databend the EU-based alternative to Snowflake?

Written by

  • Richard Kooijman

Topics

  • Data Platforms
  • EU-Cloud

How to transform any website into a chatbot using LLMs?

Topics

  • Data Science
  • Generative AI

Recent developments on AI protocols: MCP and future possibilities

Written by

  • Sinan Polatoglu

Topics

  • Agentic AI
  • Data Science
  • Generative AI
See more
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