SQL for BI Analysis: Thinking in Metrics, Grain, and Question

📰 Medium · Data Science

Learn to use SQL for BI analysis by focusing on metrics, grain, and question to answer business questions correctly

intermediate Published 7 May 2026
Action Steps
  1. Identify key business questions to answer using SQL
  2. Define the grain of the data to ensure accurate analysis
  3. Determine the relevant metrics to measure and track
  4. Write SQL queries to extract and analyze the data
  5. Test and refine the queries to ensure correct results
Who Needs to Know This

Data analysts and business intelligence professionals can benefit from this approach to improve their SQL skills and provide more accurate insights to stakeholders

Key Insight

💡 SQL is a tool to answer business questions, not the goal itself

Share This
Boost your BI analysis skills with SQL by focusing on metrics, grain, and question #BI #SQL

Key Takeaways

Learn to use SQL for BI analysis by focusing on metrics, grain, and question to answer business questions correctly

Full Article

In BI work, SQL isn’t the goal, but it’s just the tool. The real goal is answering business questions correctly and confidently. Continue reading on Medium »
Read full article → ← Back to Reads

Related Videos

How to Prompt Your LLM Directly from SQL
How to Prompt Your LLM Directly from SQL
Ian Wootten
People Skills for Analytical Thinkers (Ep. 1005 with Gilbert Eijkelenboom)
People Skills for Analytical Thinkers (Ep. 1005 with Gilbert Eijkelenboom)
Super Data Science: ML & AI Podcast with Jon Krohn
What is Data Mesh Explained with Examples
What is Data Mesh Explained with Examples
VLR Software Training
This could be the most perfect data frontend
This could be the most perfect data frontend
Matt Williams
How to Scrape Facebook Ad Library Data + Analyse on n8n 🔥
How to Scrape Facebook Ad Library Data + Analyse on n8n 🔥
DroidCrunch
6-Phase SQL Roadmap 2026 | Data Analytics & Engineering | #shorts
6-Phase SQL Roadmap 2026 | Data Analytics & Engineering | #shorts
SCALER