Category
Data & Analytics
Data engineering and analytics tools: ETL and reverse ETL, dbt, BI platforms like Metabase and Superset, product analytics, and Python data libraries.
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Apr 23, 2026
openpyxl vs pandas for excel automation: Which Python Library Should You Use?
openpyxl vs pandas for Excel automation: cell-level formatting and formulas against fast data processing. When to use each, or both together.
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Apr 23, 2026
What is a Semantic Layer in BI? Solving the ‘Metric Chaos’ Problem
What is a semantic layer in BI? How it stops metric drift between dashboards, how it works, steps to build one and pitfalls to watch…
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Apr 23, 2026
How to Automate Google Sheets with Python Pandas: A Step-by-Step Guide
Automate Google Sheets with Python and Pandas: set up a service account, read a sheet into a DataFrame, transform the data and write it back.
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Apr 23, 2026
The Pragmatic Business Intelligence Implementation Roadmap: From Raw Data to Actionable Insights
A practical BI implementation roadmap: requirements mapping, the data foundation, dashboard design and governance, deployment and scaling.
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Apr 23, 2026
How to Scale Metabase on AWS: A Production-Ready Guide
Run Metabase on AWS in production: an external application database, ECS Fargate, a load balancer and auto-scaling to stop memory crashes.
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Apr 23, 2026
Setting Up a dbt Cloud Pipeline Tutorial: From Raw Data to Production-Ready Models
Set up a dbt Cloud pipeline: connect the warehouse and Git, configure a production environment, schedule jobs and add CI checks on pull requests.