Luke Barousse

@DataWithHawl 🙌

Learning Excel for Data Analytics through @LukeBarousse’s course. I’ll be consistent every day and post my progress. 3 months focused on mastering Excel for data analytics.

⚠️ Fundamental DE concepts are more important than focusing on tools first. I break down how I rank these tools based on the core concepts here👉 youtu.be/_-DzZeixu0w

Data Nerds! I ranked every data engineering tool by how often it shows up in 4M+ job postings. 📊 But here's the catch 😳. Some critical skills show up way less than they should because they're often assumed to be foundational skills for jobs. (e.g., Skills like Bash/Terminal for running pipelines) Anyway, here's the breakdown of the tiers 👇 (Note: % = how often each tool appears in DE job postings) 🔴 S TIER — Non-Negotiable The core skills needed for any DE job. Don't apply without these: 📊 SQL (~68%) — every warehouse runs on it. Query, transform, and model data. 🐍 Python (~67%) — the pipeline language. Ingestion, automation, APIs, glue between systems. ⌨️ Terminal/Bash (~11%) — every tool you'll use runs from here. This is highly undervalued in postings. 📁 Git (~11%) — version control. Every team uses it. Same posting-% caveat as Bash. ☁️ One cloud platform + warehouse (~26-46%) — AWS + Redshift, GCP + BigQuery, or Azure + Synapse. Combined cloud presence is in nearly every posting. Start with SQL, then Python. Everything else you absorb alongside them. 🟠 A TIER — Job-Ready Foundation The tool that closes the gap from "learning DE" to "hireable for modern stacks": 🪛 dbt (~10%) — only 10% of all DE postings, but 36% in Analytics Engineer (AE) roles. That's not a niche, it's a leading indicator. AE is the new hybrid role modern data teams are hiring for: part analyst, part engineer. ✅ Land the job with S + A. Pass the interview with conceptual knowledge of B Tier 👇 🟡 B TIER — Interview-Aware Know what they solve. Don't expect to code from scratch: ⚙️ Airflow (~17%) — orchestration. Built on DAGs (directed acyclic graphs). ⚡ Spark (~38%) — distributed computing for processing large datasets. 🌊 Kafka (~19%) — real-time event streaming between systems. All these depend on a foundational knowledge of Python & SQL; don't jump the gun learning these. 🟢 C TIER — Data Platform Awareness Pick the one your company uses. Understand both conceptually: ❄️ Snowflake (~26%) — pure SQL warehouse. Optimized for analytics. Modern-stack favorite. 🧱 Databricks (~24%) — lakehouse on Spark. Handles structured + unstructured. ML/AI heavy teams. 🔵 D TIER — Versatility Multipliers Lower headline demand, but high value per hour: 📊 Power BI (~15%) / Tableau (~10%) — but the kicker: in AE roles these jump to 28% / 33%. Modern data teams want pipeline builders who can also visualize. For analysts pivoting to DE, lead with this in interviews. 🟣 E TIER — Path-Dependent High demand on paper, but concentrated in legacy enterprise stacks. Skip until your job requires it: ☕ Java (~25%) — legacy enterprise data infrastructure ⚖️ Scala (~22%) — Spark's native language. Spark-heavy shops. 🎥 How did I derive this ranking? In my latest video, I walk through the concepts first (the DE lifecycle, what each tool actually solves) and then derive the tiers. (Link in comments 👇)

@OboniiX Thanks for the shoutout!

Luke Barousse @LukeBarousse" target="_blank" rel="nofollow noopener">youtube.com/@LukeBarousse Great for SQL, Python, job prep, and real-world analytics advice. @LukeBarousse

You do NOT need to pay thousands to learn Data Analytics. Most of the resources you need are already free. Here are some of the best platforms, websites, and YouTube channels to learn Data Analytics 👇🏾

@kwame_abaasah Congrats on finishing up the course!!

I just completed @LukeBarousse 10-Day Data Engineering Crash Course! Over the past 10 days we went over the fundamentals: 📍 Day 1: What Data Engineers actually do 🔄 Day 2: The Data Engineering Lifecycle 🛠️ Day 3: Essential DE tools 🗄️ Day 4: How data gets stored

@FuturePresido19 Keep up the studies!

Sight @LukeBarousse at the bottom right corner

I asked AI: If someone were to start learning Data Analysis today, with AI already blowing up the tech world, what’s the best way to do it? The advice it gave was incredibly strategic. Here are the 4 steps to surviving and thriving in data right now: 🧵👇

@Laymanke No prereqs required.

@LukeBarousse Prerequisites?

Data Nerds! I just launched a FREE 10-Day Crash Course on Becoming a Data Engineer! 🛠️ This course is for the analyst whose boss heard 'I know SQL' and somehow translated that to 'build our entire data infrastructure.' 😵 Over the course of 10 days, I'll deliver it straight to your inbox, one email at a time: 🧑‍💻 Day 1: What Data Engineers actually do 🔄 Day 2: The Data Engineering Lifecycle — the framework everything clicks around 🛠️ Day 3: Essential DE tools — backed by real job posting data 🏗️ Day 4: Data warehouses, lakes, and lakehouses 📐 Day 5: Data modeling — the skill that separates analysts from engineers 📥 Day 6: Batch vs. streaming ingestion 🔧 Day 7: ETL, ELT, and transformations 📊 Day 8: Serving data to the business ⚙️ Day 9: Orchestration and production pipelines 🗺️ Day 10: Your DE learning roadmap 🎁 Bonus: How to land your data job It's the crash course I wish I had back when I was nodding along to words like 'orchestration' and 'ingestion' and praying nobody asked me to define them. 😅 No fluff. No tool-of-the-week hype. Just the concepts that make the rest of it click. 📩 Link in the first comment 👇

@Tech_p001 💯 AGREE! I was lucky enough to get a signed copy from Joe and Matt

@LukeBarousse This book is a goldmine

The Course 👉 lukebarousse.com/data-engineer-…

@Bitly @BitlyCSChannel Just sent DM, thank you!

@LukeBarousse Hello there - Thanks for reaching out. Please direct message @BitlyCSChannel and our Global Support Team will be happy to assist with your issue. Much appreciated. - DW

@kailodee I use SerpAPI to pull them from Google Jobs... which pulls them from major job platforms

@LukeBarousse @LukeBarousse wow, this is truly insane. Where is it pulling the job posts from?

Data Nerds! I just rebuilt datanerd.tech, my free job market intelligence app. 📲 But first, why the heck is this app even needed? Ask any AI what the top skills for data analysts are, and you'll get a confident answer — pulled from the same biased sources that have always polluted this topic. Colleges list outdated technologies to justify their aged programs. Course providers list their own courses as "top skills." Influencers (including me) are falling for it, too. As someone who wasted months learning outdated tools because I thought it was “relevant” (...thanks, Microsoft Access 🤦🏼‍♂️) I built an app that cuts through the noise. 🙅🏼‍♂️ No opinions. No agendas. 📊 Just an analysis of real-time job postings telling you exactly what employers are actually demanding. Since launching 3 years ago, datanerd.tech has aggregated over 4 million job postings so data nerds like you can focus on the skills that actually matter and stop wasting time on the ones that don't. And here's what the rebuild actually brought: 🌍 A faster, cleaner pipeline pulling real-time job postings from around the world 🔍 A brand new job search feature where you enter YOUR current skills and find recently posted jobs that match you No more "what should I learn next?" Just data telling you where you stand and what's in demand right now. Tomorrow I'm dropping a full walkthrough video on everything the app can do. Stay tuned. 🙌

@Meet_Fvad @EhdyeeJ appreciate the shoutout!🙌

@EhdyeeJ Check out @LukeBarousse YouTube page ,the fella is so clear

Currently battling the Excel IF function. It feels like a literal wall, but I’m determined to break through. If you’ve figured out the logic, please send some brain cells my way! 😅 #LearningExcel

@EstherDataQueen Too Sweet! Thanks for the shoutout, @EstherDataQueen 🙌

@LukeBarousse taught me Excel, Power BI, and even Python. I didn’t just learn the basics. I followed along with the practical examples he demonstrated in his videos, which really helped me understand how to apply the skills.

How I learned data analytics in 3 pics Quote with yours ☺️

@Dharmikananii Heck yeah! Great job on the dashboard! 🙌

📊 Data Jobs Analysis 2.0 – Insights for Job Seekers • Master SQL, Python & visualization tools🎯 • Higher salaries = advanced skills (ML/Cloud)💰 • Data Scientist have 86% mastery in Python and 57% in SQL Inspired by @LukeBarousse #DataAnalytics #SQL #Python #DataScientist

@Dharmikananii Great job on the dashboard!

🚀 Data Jobs Dashboard 2024 💼 Most roles are full-time 📈 Senior Data Scientist & ML Engineer are among the highest-paying roles 🔎 Drill-through pages for deeper job insights and decision-making Lot's of thanks :- @LukeBarousse #PowerBI #DataAnalytics #DataJobs #DataScientist

@Versatileblezyn @Rita_tyna 🙌

@LukeBarousse @Rita_tyna Thank you sire..it’s a great pleasure learning from you and thank you for the evergreen course…you nailed it 🫡

Day 24/120 of the versatileblezyn becoming a data analyst Project 2 (Salary Analysis) I worked on the second project about salary analysis. Guided by @LukeBarousse #120DaysOfDataWithTina #DataAnalyticsLockedIn @Rita_tyna

@Praisee__ @Rita_tyna Great job on the project @Praisee__

Guided by @LukeBarousse #120DaysOfDataWithTina #DataAnalyticsLockedIn @Rita_tyna

Day 24/120: Project 2 (Salary Analysis) Today was long and stressful because of work, but I still showed up. I worked on the second project about salary analysis. The project answered these questions: