Excel Analysis: How I'd Learn It Starting From Scratch

Excel analysis is still the first language most data teams speak — and that's not changing anytime soon. Despite years of hype around Python, R, and cloud tools, Excel runs on over 750 million computers worldwide. That's roughly one in ten people on Earth using a single piece of software to make sense of numbers every day.

I find that number surprising every time I look it up. Not because Excel is bad — it's remarkably good at what it does — but because the data world keeps announcing its death and it keeps not dying. Companies running billion-dollar operations use it for budgeting, forecasting, and reporting. Job listings for data analyst roles almost always list it. And for quick, ad-hoc analysis? Nothing matches the speed of opening a spreadsheet and just starting.

The problem is that most people learn Excel the wrong way. They pick up tips from colleagues, Google one function at a time, and end up with a patchwork skill set that gets them 70% of the way there. They can sort a table and run a SUM. But pivot tables still feel like dark magic. Nested IF formulas make them nervous. Dashboards look like something other people build.

This guide is a curated path through that 30% gap. Whether you're just getting started or trying to move beyond basic formulas, here are the Excel analysis courses, free resources, YouTube channels, and books that actually deliver.

Key Takeaways

• Excel analysis remains one of the most in-demand data skills for entry-level and mid-level roles — learning it has direct career value.
• Pivot tables are the highest-leverage Excel skill for beginners: they show you what Excel can do before you get lost in formula syntax.
• You can build a solid Excel analysis foundation completely free using Microsoft's own documentation, IBM's Coursera course, and Alison's self-paced programs.
• The YouTube channels ExcelIsFun, Leila Gharani, and Chandoo collectively cover virtually every Excel analysis technique from beginner to advanced.
• Pairing Excel analysis with Power Query and Power BI dramatically expands what you can do with your data.

In This Article

• Before You Start Learning Excel Analysis
• Excel Analysis Courses That Are Worth Paying For
• Start Learning Excel Analysis Without Spending a Dime
• The Excel Analysis YouTube Channels I Keep Coming Back To
• Excel Analysis GitHub Repos Worth a Star
• For When You Want to Go Deep With Excel Analysis
• Where Excel Analysis Learners Actually Get Help
• Related Excel Analysis Skills Worth Exploring
• Frequently Asked Questions About Excel Analysis

Before You Start Learning Excel Analysis

Here's a take that most tutorials won't give you: don't start with VLOOKUP.

Every beginner Excel guide starts with VLOOKUP. But VLOOKUP is a formula — and formulas reward you slowly. You type something, something happens, repeat 50 times. Meanwhile, pivot tables let you drag a column name into a box and watch three months of sales data summarize itself in about two seconds.

Start with pivot tables. They show you why Excel analysis matters before you get lost in syntax.

Once you've seen what pivot tables can do, formulas become more motivating to learn. You'll see that VLOOKUP (or its more capable replacement, XLOOKUP) answers specific questions from pivot-organized data. Things click faster in that order.

You don't need any programming background. You need a working copy of Excel — Microsoft 365 is recommended because it includes the newest functions like XLOOKUP, LET, and dynamic arrays. If you're on a budget, LibreOffice Calc covers most fundamentals, though it won't have Power Query.

One more thing worth noting: the data science skills you build in Excel translate directly to other tools. Learning to think in tables, filters, and aggregations is the same mental model you'll use in SQL, Python, and Power BI later on.

Excel Analysis Courses That Are Worth Paying For

There are dozens of paid Excel courses out there. Most teach the software. A few teach you to actually think analytically. Here's the difference in practice:

1. Microsoft Excel Data Analysis: Formulas & Pivot Tables [Editors' Choice]

This is the course I'd hand to someone who wants to get genuinely useful at Excel analysis without sitting through hours of filler. With a 4.69 rating from over 10,700 students, it earns that score. The instructor covers formula logic, data cleaning techniques, and pivot table construction with real business datasets — not toy examples. What makes it stand out is the sequencing: formulas come after you understand what you're trying to solve, not before. That's the right order.

2. Excel Data Analysis With Pivot Tables & Pivot Charts [Editors' Choice]

Over 39,000 students enrolled. That number typically means one of two things: either the course is genuinely good, or it had a great discount period early on. In this case, it's actually good. The course focuses specifically on pivot tables and pivot charts, which means it goes deep instead of broad. You'll come out able to build interactive dashboards with slicers, group by time periods, use calculated fields, and create pivot charts that don't look like they came from a 1997 PowerPoint template. For anyone whose main gap is pivot tables specifically, this is the right pick.

3. Master Excel Analysis With BCG Consultant Secrets

Taught by Lucas Lin, this course takes an interesting angle: it frames Excel analysis through the lens of management consulting. That means you'll learn speed techniques, keyboard shortcuts, and the kind of analysis structure consultants use when building reports for executive audiences. Rated 4.56. If your job involves presenting data to decision-makers, this course's focus on professional-grade efficiency is worth the investment. You might also find Excel Shortcuts for Management Consultants a useful companion — 4,700+ students and rated 4.53.

4. Microsoft Excel - Data Analysis & Visualization

Where most Excel courses stop at pivot tables, this one keeps going into visualization — how to choose the right chart type, how to format charts for clarity rather than decoration, and how to build dashboards that actually communicate something. Rated 4.43 with 2,200+ students. The data visualization skills you build here translate beyond Excel too, shaping how you think about presenting any kind of data.

5. Revealed: Excel Power Query One Hour Bootcamp

Power Query is the part of Excel that most beginners skip — and then desperately wish they'd learned sooner. It handles data cleaning and transformation steps that would otherwise eat hours of your time every week. This beginner-level course by Doug Burke gets you up and running in a single session. Rated 4.30. It's a solid addition to your toolkit once you've got formulas and pivot tables down. For specialized fields, there's also Measurement System Analysis Using Microsoft Excel — niche, but excellent for manufacturing and quality control professionals.

Pick Your Path: Which Excel Analysis Course First?

Start Learning Excel Analysis Without Spending a Dime

Here's what surprises most people: some of the best Excel analysis resources are completely free.

Essential Excel Functions and Formulas for Beginners [Editors' Choice]

This is the free course I'd recommend first. It covers IF, COUNTIFS, SUMIFS, text functions, date functions, and the FILTER function — essentially the formula toolkit every analyst needs. Rated 4.53 with nearly 1,800 students. Completely free on Udemy (Udemy regularly offers courses free or at steep discounts — worth checking).

Excel Basics for Data Analysis — IBM on Coursera

IBM's contribution to Coursera's data specialization is genuinely well-made. It covers data quality checks, filtering, sorting, lookup functions, and pivot tables — framed specifically for data analysis work rather than general Excel use. You can audit it free, which means full video access without a certificate.

Data Analysis in Excel — Excel-Easy.com

Don't let the plain website design fool you. Excel-Easy has been quietly building one of the most useful free Excel references on the internet for over a decade. The data analysis section covers sorting, filtering, conditional formatting, subtotals, and pivot tables with clear screenshots and short explanations. Great for quick lookups when you forget how something works.

Mastering Data Analysis Using Microsoft Excel — Alison

Alison is a legitimate free learning platform — not a trial, not freemium. The Excel analysis course covers formulas, pivot tables, and data visualization. You can complete it at your own pace and earn a certificate (for a fee, though the learning itself is always free). If you want structure without paying for a Udemy course, this is a strong option.

Microsoft's Official Excel Documentation

Microsoft's own support docs are underrated. The "Analyze Data" button in Excel 365 uses AI to surface patterns, trends, and insights from your data automatically. The documentation explains how it works and how to use it well. Worth reading even if you never touch the feature constantly — it gives you a clearer picture of what modern Excel can actually do.

Introduction to Data Analysis Using Excel — Rice University on Coursera

Rice University's Coursera intro course walks through reading data into Excel, organizing it, manipulating it, and applying basic analysis. Free to audit. Good for a structured, academic-style approach without the academic price tag.

The Excel Analysis YouTube Channels I Keep Coming Back To

YouTube might be the single best free resource for Excel analysis. These are the channels worth subscribing to:

ExcelIsFun (YouTube) [Editors' Choice]

Mike Girvin — a former Excel MVP and community college instructor — has built a library of over 3,700 videos. That's not a typo. The channel covers everything from absolute basics to Power Query, Power Pivot, and DAX formulas. His teaching style is unusually thorough; he shows why things work, not just how. The downside is that with 3,700 videos, finding the right one takes navigation. Use the search bar within his channel. His "Excel Basics" and "Excel Magic Trick" playlists are the right starting points.

Leila Gharani (YouTube)

Leila's videos are shorter and more focused than Mike's — most run under ten minutes. She's excellent for picking up specific Excel analysis techniques quickly: XLOOKUP vs VLOOKUP, dynamic arrays, Power Query basics, and how to build clean dashboards. Her production quality is high without feeling overproduced. If you learn better in focused bursts than in long sessions, this channel is the one.

Chandoo (YouTube)

Chandoo specializes in Excel dashboards and business analytics — how to turn raw data into something a CEO would actually look at. He's particularly good at the "last mile" of Excel analysis: not just crunching numbers, but communicating them clearly. If your job involves presenting Excel analysis to non-technical audiences, this channel belongs in your regular rotation.

MyOnlineTrainingHub (YouTube)

Mynda Treacy's channel focuses heavily on Power Query, Power Pivot, and PivotTables. If you want to go beyond basic Excel analysis into the modern Excel data model, this is where to learn it. The Power BI analysis skills you develop from Power Pivot transfer almost directly to Power BI too — so you're building two skill sets at once.

Excel Campus — Jon Acampora (YouTube)

Jon Acampora has delivered over 270 tutorials to more than 38 million viewers. His content skews practical: real-world scenarios, Excel hacks that save time, and clear walkthroughs of features that most people never discover. Good for intermediate learners who want to fill in gaps.

Excel Analysis GitHub Repos Worth a Star

GitHub isn't the first place most people look for Excel resources. It should be.

Awesome Excel — NajiElKotob (GitHub, 85 stars)

A curated list covering Excel tutorials, YouTube creators, Power Query resources, VBA references, visualization guides, and official Microsoft documentation links. The Power Suite section alone — covering Power Query, Power Pivot, Power Map, and Power View — is worth bookmarking. If you want a single reference that covers the entire Excel analysis ecosystem, this is it.

Excel Fundamentals — D-Lab Berkeley (GitHub)

UC Berkeley's D-Lab published their six-hour Excel intro curriculum with full materials: exercises, datasets, and step-by-step instructions. It covers functions, text, date, and logic calculations, charts, and pivot tables. Everything's free, and the datasets are real enough to actually practice on. It's a structured curriculum without a price tag.

Both repos work well as companions to course study. Use the D-Lab materials for structured practice sessions and the Awesome Excel list as an ongoing reference as your skills grow.

For When You Want to Go Deep With Excel Analysis

If you've finished courses and channels and want something more lasting on your shelf:

Modern Data Analytics in Excel (O'Reilly)

This book is specifically about the modern Excel stack — Power Query for data cleaning, Power Pivot for data modeling, dynamic array functions, and Python integration in Excel 365. It's aimed at analysts who've outgrown basic pivot tables and want to understand what Excel can actually do right now. Available on O'Reilly Learning with a subscription, or for direct purchase.

Microsoft Excel Data Analysis and Business Modeling, 7th Edition (Wayne Winston)

This is the Excel analysis book that business analysts and finance professionals cite most often. It covers regression, optimization with Solver, simulation, and statistical analysis — areas that most courses skim or skip entirely. Not for beginners, but if you want to understand the full analytical depth Excel is capable of, Wayne Winston's book is the definitive reference. Available at Microsoft Press.

Excel 365 Bible (Wiley)

For a comprehensive reference that covers everything from beginner basics to advanced features, the Excel 365 Bible is what most power users keep at their desk. It's long — over 1,000 pages — but organized so you can find what you need without reading it cover to cover. Good for anyone who wants a single authoritative reference rather than piecing things together from tutorials.

Where Excel Analysis Learners Actually Get Help

Learning Excel analysis on your own is manageable until you hit a formula that won't work and can't figure out why. These are the places where real answers come quickly:

r/excel on Reddit has over 800,000 members. The community is genuinely helpful for questions at every skill level. Post your formula, explain what you're trying to do, and you'll usually get a working answer within an hour. It's also a good place to browse for tips you didn't know to search for.

MrExcel Message Board is the older, still-active alternative. Founded by Excel author Bill Jelen, it covers formulas, VBA, pivot tables, and Power Query. The search archive alone is worth bookmarking — most problems have already been asked and answered in detail.

ExcelForum fills a similar role, with a strong community around formula help and data analysis questions. Useful when you want more than one perspective on a tricky problem.

For staying current on new Excel features — Microsoft releases meaningful updates to Excel 365 regularly — the Excel blog on Microsoft Tech Community is the most reliable source.

If business analytics is your longer-term goal, these Excel communities pair well with SQL and data analytics forums, since most business analysts use Excel alongside other platforms. And if you want to understand where Excel analysis fits within a broader data science methods workflow, r/datascience has useful discussions on when Excel is the right tool vs. when to move to something else.

Related Excel Analysis Skills Worth Exploring

Excel analysis rarely exists in isolation. These skills pair naturally with it:

• Data Visualization — Excel builds charts, but data visualization as a discipline teaches you which chart to use and why. Over 1,500 courses available to explore.
• Power BI Analysis — Microsoft's BI tool shares Power Query and the data model with Excel. If you know Excel analysis, Power BI is the natural next step for sharing interactive dashboards with teams. 428 courses available.
• Python Analysis — When datasets get too large for Excel or you need to automate repetitive analysis, Python (especially Pandas) is the upgrade path. 390 courses available.
• Business Analytics — Excel is a core tool in business analytics. This category covers how to apply data to real business decision-making. 327 courses available.
• Data Science Skills — A broader look at the complete skill set data scientists use, from Excel to machine learning and beyond.
• Data Engineering — Understanding how data gets structured and stored makes you more effective when working with it in Excel and other tools.
• Big Data — Once you hit the limits of what Excel can handle, big data tools pick up where it leaves off.

Frequently Asked Questions About Excel Analysis

How long does it take to learn Excel analysis?

Most learners get comfortable with the core skills — formulas, pivot tables, and basic charts — in 4-6 weeks of consistent practice (roughly an hour a day). Getting genuinely fast and confident, including Power Query and complex formulas, typically takes 3-6 months of regular use on real data. You can browse Excel analysis courses to find one that matches your current level and available time.

Do I need math skills to learn Excel analysis?

No advanced math required. Most Excel analysis involves arithmetic, percentages, and basic statistics — averages, sums, counts. The analytical thinking matters more than mathematical ability. If you can read a budget or a sales report, you already have the foundation you need.

Is Excel analysis enough to get a data analyst job?

Excel analysis is a solid starting point for entry-level data analyst roles — many job listings require it as a baseline. But most roles also expect SQL knowledge, and increasingly, some Python familiarity. Think of Excel analysis as the first skill on a learning path that moves through SQL and into Python analysis or Power BI analysis over time.

What's the difference between Excel analysis and Power BI?

Excel analysis happens inside a spreadsheet — it's flexible, quick, and great for individual or small-team work. Power BI is built for sharing visual dashboards with larger audiences and handles much bigger datasets. The two tools share Power Query and the data modeling layer (Power Pivot / DAX), so skills transfer between them. If you're analyzing data for yourself, Excel is often faster. If you're building dashboards for an entire department, Power BI is the better fit.

Is Excel Analysis a substitute for Python in data science?

No — and this is one of the most common misconceptions beginners have. Excel analysis is excellent for exploration, quick reporting, and communicating with non-technical stakeholders. Python handles complex statistical modeling, automation at scale, and datasets that would crash Excel entirely. The two tools complement each other in most data science workflows rather than competing. Many analysts use Excel for initial exploration, then Python for deeper work.

Excel analysis is one of those skills that quietly compounds over time. Every formula you learn, every pivot table you build, every dashboard you deliver makes the next one faster. Start with one good course, practice on real data you care about, and watch the pieces connect.

Your next move: pick one course from the list above and open a dataset you actually work with. The Excel analysis courses on TutorialSearch are a good place to find what fits your level and your goals.