Steps to Become a Data Analyst

If I had to go from zero to landing my first data analyst job in 90 days, here’s the roadmap I’d follow. No fluff. No endless tutorials. Just a clear path to building real-world, portfolio-worthy skills. You don’t "learn data." You practice decision-making with data. 0. 𝐅𝐨𝐮𝐧𝐝𝐚𝐭𝐢𝐨𝐧𝐬 & 𝐓𝐡𝐢𝐧𝐤𝐢𝐧𝐠 𝐢𝐧 𝐃𝐚𝐭𝐚 (𝐖𝐞𝐞𝐤𝐬 1–2) Before you touch Python or Power BI, understand what makes data valuable. • Alex The Analyst – What does A Data Analyst do? https://lnkd.in/dN8xUHZy • Google – Foundations: Data, Data Everywhere https://lnkd.in/d_vwRE5q 1. 𝐄𝐱𝐜𝐞𝐥 & 𝐒𝐐𝐋 (𝐖𝐞𝐞𝐤𝐬 3–5) Still 70% of the job. And still underrated. • Luke Barousse– Excel for Data Analytics https://lnkd.in/dwR2rJsj • Alex the Analyst – Learn SQL in 4 hours https://lnkd.in/dUZGt9Jw • Luke Barousse - SQL for Data Analytics https://lnkd.in/dadiekDw 2. 𝐏𝐲𝐭𝐡𝐨𝐧 + 𝐄𝐃𝐀 (𝐖𝐞𝐞𝐤𝐬 6–8) Python isn’t required everywhere, but it gives you range. • Efficient Python for Data Scientists – Book https://lnkd.in/dfe-ZpFP • Kaggle – EDA Notebooks https://lnkd.in/d9Sv_QWF • FreeCodeCamp - Data Analysis with Python https://lnkd.in/d4x9c3uA • 𝐏𝐫𝐨𝐣𝐞𝐜𝐭 idea: Clean and explore a messy dataset (Netflix, Airbnb, etc.) 3. 𝐃𝐚𝐬𝐡𝐛𝐨𝐚𝐫𝐝𝐬 & 𝐕𝐢𝐬𝐮𝐚𝐥𝐬 (𝐖𝐞𝐞𝐤𝐬 9–10) This is what stakeholders see. Learn to tell a story. • Tableau Public – Practice Visualization https://public.tableau.com • Alex the Analyst - Learn Tableau https://lnkd.in/dPr8BQFa • Luke - Power BI for Beginners https://lnkd.in/d5ApkuC2 • 𝐏𝐫𝐨𝐣𝐞𝐜𝐭: Visualize COVID, sales, churn, or hiring trends 4. 𝐏𝐫𝐨𝐣𝐞𝐜𝐭𝐬 & 𝐏𝐨𝐫𝐭𝐟𝐨𝐥𝐢𝐨 (𝐖𝐞𝐞𝐤𝐬 11–12) This gets you hired. Show, don’t just tell. • Luke Barousse – Data Analyst Portfolio Guide https://lnkd.in/dA_gydAC • Data Analyst Portfolio Projects by Alex https://lnkd.in/d-mVCk7X • Data Analysis Project - Codebasics https://lnkd.in/duk93hQv • What Makes a JOB_READY Data Portfolio Project https://lnkd.in/dvpQqS9i • GitHub + Medium/LinkedIn: Share your project story & decisions 5. 𝐉𝐨𝐛 𝐏𝐫𝐞𝐩 & 𝐈𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰 𝐑𝐞𝐚𝐝𝐢𝐧𝐞𝐬𝐬 (𝐖𝐞𝐞𝐤𝐬 13–14) Polish your resume. Practice your story. Sharpen your SQL. • Resume Worded – Resume & LinkedIn Checker https://lnkd.in/dK73PQ8U • Pramp – Mock Interviews https://www.pramp.com • DataLemur (Nick) – SQL & Case Prep https://www.datalemur.com • Datainterview by Daniel Lee https://lnkd.in/dSdshHG8 • Dataford - SQL & Python Practice https://lnkd.in/enbEEgYd • 10-Day Data Analyst Interview Prep Series https://lnkd.in/dCUPGStB This is the roadmap I wish I had when I started. No guesswork. Just what actually gets you hired. ♻️ If this helped, repost it. Someone out there needs clarity today. PS: I drop weekly guides on data careers here → https://lnkd.in/e9wsdgc8

I was a Business Analyst at Amazon in 2017 to 2019. But if I were to start my Analytics career in 2025, here's are the 5 steps I would take 👇 1️⃣ 𝗟𝗲𝗮𝗿𝗻 𝘁𝗵𝗲 𝘁𝗼𝗽 𝟯 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝘁𝗼𝗼𝗹𝘀 1. SQL 2. Tableau (or another data viz tool) 3. Excel Pro-tip #1: Learn one skill at a time • 𝘔𝘢𝘴𝘵𝘦𝘳 𝘚𝘘𝘓 𝘣𝘦𝘧𝘰𝘳𝘦 𝘮𝘰𝘷𝘪𝘯𝘨 𝘵𝘰 𝘛𝘢𝘣𝘭𝘦𝘢𝘶 • 𝘔𝘢𝘴𝘵𝘦𝘳 𝘛𝘢𝘣𝘭𝘦𝘢𝘶 𝘣𝘦𝘧𝘰𝘳𝘦 𝘮𝘰𝘷𝘪𝘯𝘨 𝘵𝘰 𝘌𝘹𝘤𝘦𝘭 Pro-tip #2: Get lots of hands-on practice • Find practice problems on InterviewMaster.AI • Find datasets & competitions on Kaggle 2️⃣ 𝗕𝘂𝗶𝗹𝗱 𝘆𝗼𝘂𝗿 𝗻𝗲𝘁𝘄𝗼𝗿𝗸 Yes, start building your network early. Building a strong network takes months (or even years). Tips for networking ↳ Start with your 𝘦𝘹𝘪𝘴𝘵𝘪𝘯𝘨 connections, like family/ friends ↳ Stay in touch (regularly) with your new connections ↳ Ask everyone you chat with for more introductions 3️⃣ 𝗕𝘂𝗶𝗹𝗱 𝗮 𝗽𝗼𝗿𝘁𝗳𝗼𝗹𝗶𝗼 A portfolio allows you to showcase your skills to recruiters and hiring managers. What projects should a Data Analyst portfolio have? 1. 𝘚𝘘𝘓 𝘱𝘳𝘰𝘫𝘦𝘤𝘵 𝘦𝘹𝘵𝘳𝘢𝘤𝘵𝘪𝘯𝘨 𝘪𝘯𝘴𝘪𝘨𝘩𝘵𝘴 𝘧𝘳𝘰𝘮 𝘭𝘢𝘳𝘨𝘦 𝘥𝘢𝘵𝘢𝘴𝘦𝘵𝘴 2. 𝘋𝘢𝘵𝘢 𝘝𝘪𝘴𝘶𝘢𝘭𝘪𝘻𝘢𝘵𝘪𝘰𝘯 𝘱𝘳𝘰𝘫𝘦𝘤𝘵 𝘵𝘦𝘭𝘭𝘪𝘯𝘨 𝘤𝘭𝘦𝘢𝘳 𝘴𝘵𝘰𝘳𝘪𝘦𝘴 𝘸𝘪𝘵𝘩 𝘤𝘩𝘢𝘳𝘵𝘴 3. 𝘌𝘹𝘤𝘦𝘭 𝘱𝘳𝘰𝘫𝘦𝘤𝘵 𝘸𝘪𝘵𝘩 𝘢𝘥𝘷𝘢𝘯𝘤𝘦𝘥 𝘵𝘦𝘤𝘩𝘯𝘪𝘲𝘶𝘦𝘴, 𝘭𝘪𝘬𝘦 𝘱𝘰𝘸𝘦𝘳 𝘲𝘶𝘦𝘳𝘺 4️⃣ 𝗟𝗲𝗮𝗿𝗻 𝗵𝗼𝘄 𝗱𝗮𝘁𝗮 𝗶𝘀 𝘂𝘀𝗲𝗱 𝗶𝗻 𝘁𝗵𝗲 𝗿𝗲𝗮𝗹 𝘄𝗼𝗿𝗹𝗱 Want to stand out from other job applicants? Learn how to use data in the real-world, by • Reading case studies and books • Practicing with real-world questions→ 𝘐𝘯𝘵𝘦𝘳𝘷𝘪𝘦𝘸𝘔𝘢𝘴𝘵𝘦𝘳.𝘈𝘐 • Joining competitions to solve real business problems 5️⃣ 𝗔𝗽𝗽𝗹𝘆 𝗳𝗼𝗿 𝗲𝗻𝘁𝗿𝘆-𝗹𝗲𝘃𝗲𝗹 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘀𝘁 𝗿𝗼𝗹𝗲𝘀 Now you're ready to apply for jobs + land your first job! But before you start applying, review this checklist: ✓ Do you have a resume tailored to Data Analyst jobs? ✓ Can you use referrals to increase your chances? ✓ Do you have a polished, public portfolio page? ✓ Have you started practicing for interviews? Btw, I wrote about this in 𝘦𝘹𝘵𝘳𝘦𝘮𝘦 detail. Link to the full article in the comments. ♻️ Repost this, if you found this useful please!

The Roadmap for an Aspiring Data Analyst isn't always a straight line. It's not meant to be easy, but being organized and efficient is key. Below is a roadmap for anyone aspiring to be a data analyst. I broke it up into 5 stages: Stage 1: Learn - You've decided to make data analytics your new career. - Choosing your learning platforms can be difficult due to the amount of content out there. I'd choose 1-3 platforms and stick to it, don't want information overload. - Along with learning technical skills, always focus on learning industry knowledge and terminology. Stage 2: Network - In 2024, it's more difficult than ever to land an analytics job. With more interest and less roles comes intense competition. - Utilizing sites like LinkedIn can help you easily meet other aspiring analysts but also meeting data professionals. You can learn an immense amount of information from people with experience. - Attending data conferences virtually and in-person can give you an opportunity to meet others and learn some industry perspectives. Stage 3: Portfolio - Now that you have a solid network and technical knowledge, it's time to showcase your skills. - As a reminder, it's more than just your technical abilities. You have to provide value to a business so make sure to discuss your business impact with your project. - This portfolio will go on your resume so recruiters and hiring managers can easily see your work. Stage 4: Job Hunt - This stage is where the road ends for most people. Not trying to sound negative, but this is where people found adversity for the first time and don't know how to overcome it. - Make sure your resume is polished and have a few varieties of it. A solid resume is a difference maker from my experiences. - Using different methods like cold applying, networking, content creation, finding LinkedIn job posts, and more to land a role. There isn't one way better than the other, whatever it takes to land a role. - Don't stop applying even if you land interviews. Never put all your eggs in one basket. Stage 5: Celebrate - You receive an offer, sign your name, and land your first data analyst job! - Take the time to reflect and celebrate. Your new career awaits you. - The first 90 days of your role are crucial. Connect with people in your company and be the best analyst/coworker you can be. - If you can, try to help others who also want to break into the industry. Anything you'd like to add to this list?