Inside Data by Mikkel Dengsøe
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Hands-on with an MCP for data quality
How an MCP combined with the right metadata and context can supercharge data quality workflows
Aug 26, 2025
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Mikkel Dengsøe
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Hundreds of actionable data quality guidelines
Building a collection of bite-sized guidelines for data teams – from testing to ownership and incident management best practices
Aug 18, 2025
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Mikkel Dengsøe
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Using Omni’s AI Assistant on the Semantic Layer
Can modern data tools’ AI assistant replace analysts for self-serve or is there still some way to go?
Jul 18, 2025
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Mikkel Dengsøe
Using AI to build a robust testing framework
Adding tests and monitors to dbt using Cursor, Claude, and dbt’s MCP server
Jul 11, 2025
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Mikkel Dengsøe
6
Using AI for Data Modeling in dbt
From raw data to a semantic layer with Cursor and dbt’s Fusion engine
Jul 4, 2025
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Mikkel Dengsøe
7
Benchmark Your Data Team
What data from hundreds of top data teams tells us about team size, role distribution, data-to-engineer ratios, and salaries.
Feb 13, 2025
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Mikkel Dengsøe
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A Guide for Building High-Quality Data Products
68 pages of best practices on defining data products, testing strategies, managing ownership, and measuring data quality
Jan 16, 2025
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Mikkel Dengsøe
3
The State of Data Testing in 2024: Why We Still Have Broken Windows
Two years ago, I shared an article called ‘Data tests and the broken windows theory’.
Nov 18, 2024
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Mikkel Dengsøe
7
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Inside Data by Mikkel Dengsøe
A regular column with ideas, observations, inspiration and frustrations in and around the data industry. Especially relevant for data practitioners 📊.
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Inside Data by Mikkel Dengsøe
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