Factual, actionable answers to high-value data questions. No fluff, just results.
Query optimization, joins, window functions, and database best practices.
Pandas, NumPy, data manipulation, and efficient Python coding patterns.
Formulas, pivot tables, data cleaning, and productivity shortcuts.
Statistical methods, exploratory analysis, and analytical thinking.
Overfitting, train-test splits, feature engineering, and AI fundamentals.
Chart selection, design principles, and effective visual communication.
User-ranked tools for data work. Vote for the tools you use and trust. 400+ tools across 6 categories.
Tableau, Power BI, D3.js, and 80+ charting tools
Python, R, Excel, and 90+ analytics platforms
OpenRefine, Trifacta, and 75+ prep tools
TensorFlow, PyTorch, and 85+ ML platforms
GitHub Copilot, ChatGPT, and 60+ AI assistants
PostgreSQL, Snowflake, and 90+ data infrastructure
Up-and-coming agent plugins, MCP servers, and workflow tools for data practitioners. Curated for the agentic era.
Reusable SKILL.md packages for SQL, dbt, and notebook workflows
Model Context Protocol servers for warehouses and BI tools
LangGraph, Pydantic-AI, and frameworks for data-pipeline agents
n8n AI nodes, Windmill — agentic glue for analytics ops
Cursor rules and Continue.dev configs for SQL and Python
Vanna, Wren AI — text-to-SQL and analytics chatbots
Every tip on this site is designed to be read in 35 seconds or less. We focus on high-value questions that data professionals actually search for, with factual, to-the-point answers you can apply immediately.
Whether you're a data analyst, data scientist, business analyst, or just starting your data journey, you'll find practical tips that save you time and improve your work. Learn more about the author.