Senior Data Analyst with 10 years of experience working across analytics, data engineering, and BI. I work mainly with SQL, dbt, BigQuery, Snowflake, and modern BI tools, and have led projects involving data platforms, analytics systems, and machine learning in companies like Remote and Lamudi. Currently focused on building better data products and figuring out where AI fits into the modern data stack.
Previously at
Everything by Cedric Conol
5 of 5
SQL for Data Analysts
A hands-on SQL course that takes you from your first SELECT statement to writing window functions and CTEs, all practiced directly in an in-browser SQL sandbox. You'll learn to filter, sort, and reshape data, join tables, aggregate and group results, handle NULLs and dates, and use subqueries and set operations, then put it all together with window functions for running totals, rankings, and row comparisons. The course closes with 10 practice exams covering everything from basic SELECT queries to mixed challenges, so you finish able to write real analytical SQL, not just recognize syntax.
Free
12 modules
Python for Data Analysts
Learn pandas 3.0 by doing: filter, join, group, reshape and clean real-looking sales data, with a live Python playground in every lesson and nothing to install. Ten practice exams take you from your first DataFrame to rolling averages and multi-step analysis.
Free
13 modules
Git for Data Analysts
Learn to version your analysis work and publish it on GitHub. You'll go from your first commit to branches, pull requests, merge conflicts, undoing mistakes and rebasing, with checkpoints along the way that leave you with a polished portfolio repo.
Free
3 modules
Terminal for Data Analysts
Stop clicking through folders and start moving around your computer like a developer. You'll learn to navigate, create, copy, move, delete and inspect files from the command line (pwd, ls, cd, mkdir, cp, mv, rm, cat, head, tail, wc), practicing each command right after its lesson.
Free
3 modules
The Data Analyst Playbook 2nd Edition
Most aspiring data analysts don't fail because the material is too hard. They fail because the path is broken: endless tutorials, half-finished courses, and roadmaps that tell you to learn everything at once. The Data Analyst Playbook gives you a clear, sequenced path into data analytics, written by a Senior Data Analyst for beginners and career shifters. What's inside: The 6-step workflow behind real analysis work, from defining the problem to presenting insights The modern analyst tech stack: SQL, spreadsheets, BI tools, terminal, Git, dbt, and AI tools The Self-Taught Trap: tutorial hell, no feedback loop, the 3-day stuck problem, and imposter syndrome An 8-part curriculum (Thinking Like an Analyst, Spreadsheets, SQL, Data Modeling, BI Tools, Terminal, Git, AI Tools), each with clear objectives, hand-picked free resources, and "Where Learners Get Stuck" notes One connected project: analyze the same retail dataset in Excel, SQL, dbt, and Power BI, and check that your numbers match at every step How to use Claude, Cursor, and Copilot without letting AI think for you A capstone passion project to build, document on GitHub, and share publicly A BigQuery + Looker Studio path for Mac users Who it's for: career shifters, fresh graduates, and self-learners stuck in tutorial hell who need structure and practice that mirrors real work. Not for: experienced analysts looking for advanced statistics or Python/ML content. About the author: Cedric Conol is a Senior Data Analyst at Remote and former Lead Data Analyst at Lamudi Group. He specializes in SQL, dbt, and modern data stacks, holds a Master's in Data Science from the Asian Institute of Management, and runs DataReady. Format: 24-page PDF with clickable links to every resource.
Free