How to Differentiate Yourself as a Data Analyst

You are never JUST a Data Analyst. When I worked at Amazon, my job title said Analyst. But my actual job included - Building databases + data tools (BI Engineer) - Developing models to find drivers (Data Scientist) - Turning user needs to a roadmap (Product Manager) - Planning and coordinating projects (Project Manager) And I liked it that way. I got promoted bc I did MORE than my job asked for. So if you’re a Data Analyst or Business Analyst, 3 skills that you can build NOW to level up your career: 𝟭/ 𝗟𝗲𝗮𝗿𝗻 𝘁𝗼 𝗯𝘂𝗶𝗹𝗱 𝘀𝗶𝗺𝗽𝗹𝗲 𝗽𝗿𝗲𝗱𝗶𝗰𝘁𝗶𝘃𝗲 𝗺𝗼𝗱𝗲𝗹𝘀 You don’t need a PhD to build models. Start with basic ML models (logistic & linear regression). Start by learning basic Statistics. 𝘚𝘵𝘢𝘯𝘧𝘰𝘳𝘥’𝘴 𝘐𝘯𝘵𝘳𝘰 𝘵𝘰 𝘚𝘵𝘢𝘵𝘴 𝘤𝘰𝘶𝘳𝘴𝘦 𝘪𝘴 𝘧𝘳𝘦𝘦: 𝘩𝘵𝘵𝘱𝘴://𝘸𝘸𝘸.𝘤𝘰𝘶𝘳𝘴𝘦𝘳𝘢.𝘰𝘳𝘨/𝘭𝘦𝘢𝘳𝘯/𝘴𝘵𝘢𝘯𝘧𝘰𝘳𝘥-𝘴𝘵𝘢𝘵𝘪𝘴𝘵𝘪𝘤𝘴 Then build incorporate simple models into your job. 𝟮/ 𝗟𝗲𝗮𝗿𝗻 𝗱𝗮𝘁𝗮 𝗺𝗼𝗱𝗲𝗹𝗶𝗻𝗴 + 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲𝘀 Building a database is complex and scary, right? Nope. It doesn’t have to be. I think about a database as 3 simple components: ↳ Design the data model ↳ Set up the database (I like Postgres) ↳ Load data into it with simple pipelines If you want a guided course, check out DataCamp’s Intro to Data Engineering: https://lnkd.in/eZV6gjYM If you’re looking for a free course, check out this 3-hour YouTube video: https://lnkd.in/eiHraCKj 𝟯/ 𝗟𝗲𝗮𝗿𝗻 𝗽𝗿𝗼𝗱𝘂𝗰𝘁 𝗺𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 Find a small project at work & manage it as a Product. What does this mean? ↳ Understand stakeholder requirements ↳ Translate those into a Product roadmap ↳ Enlist the right people to work on the project ↳ Communicate progress and blockers frequently I personally like this book about the Product Management career: https://amzn.to/4jPHxC8 ——— Btw, I’m writing about my time as an Analyst at Amazon (+ how I got promoted). Sign up to get my newsletter in your inbox tomorrow! www.askdatadawn.com ♻️ Repost this if you found this useful!

Best way to stand out early in your data career? Think like a business owner 💡 👉 Talk to stakeholders to understand their motivations 👉 Build domain knowledge to learn the nuances of the business 👉 Clearly articulate how your analysis ties to specific goals or KPIs 👉 Draft a measurement plan before you even touch the data Early in my career all I wanted to do was build fancy reports and dashboards, but as soon as I started thinking this way everything changed. Not only did I start earning respect and recognition from management, but I began to actually see (and measure) the impact of my work. This was probably the single biggest catalyst in my career growth and development as an analyst. So to all the seasoned pros out there, what other advice would you give to help an analyst accelerate their career?

Trying to land your first data job but feel stuck in “learning mode”? You’re not alone. Most new analysts spend months on courses without knowing what hiring managers actually care about.  After years helping professionals break into data, here’s what I’ve learned:  Skills don’t speak for themselves, 𝘰𝘶𝘵𝘱𝘶𝘵𝘴 do. If you’re just starting out, here’s the fastest way to build trust with recruiters (even without experience): 𝗦𝘁𝗼𝗽 𝗳𝗼𝗰𝘂𝘀𝗶𝗻𝗴 𝗼𝗻 “𝘄𝗵𝗮𝘁 𝘆𝗼𝘂’𝗿𝗲 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴.” 𝗦𝘁𝗮𝗿𝘁 𝘀𝗵𝗼𝘄𝗶𝗻𝗴 𝘄𝗵𝗮𝘁 𝘆𝗼𝘂 𝗰𝗮𝗻 𝗱𝗼 𝘄𝗶𝘁𝗵 𝗶𝘁. That means: – Create one-page projects that answer real business questions  – Use tools you’re learning (SQL, Excel, Power BI, Python) to clean messy data  – Share insights in plain English don’t hide behind dashboards  – Post consistently and narrate your process like a consultant would You don’t need 10 certificates. You need 3 solid case studies that show how you think. 📌 If you’re targeting analyst roles, aim to solve:  ➝ How can we increase customer retention? ➝ Where are we losing money? ➝ What product is underperforming? These aren’t just data questions. They’re business problems solved with data thinking. You won’t master everything at once. But you can show you're learning like a pro. 𝗧𝗵𝗲 𝗱𝗮𝘁𝗮 𝗳𝗶𝗲𝗹𝗱 𝗿𝗲𝘄𝗮𝗿𝗱𝘀 𝗮𝗰𝘁𝗶𝗼𝗻, 𝗻𝗼𝘁 𝗽𝗲𝗿𝗳𝗲𝗰𝘁𝗶𝗼𝗻. 𝗠𝗮𝗸𝗲 𝘆𝗼𝘂𝗿 𝘀𝗸𝗶𝗹𝗹𝘀 𝘃𝗶𝘀𝗶𝗯𝗹𝗲. 𝗧𝗵𝗮𝘁’𝘀 𝗵𝗼𝘄 𝘆𝗼𝘂 𝗯𝘂𝗶𝗹𝗱 𝘁𝗿𝘂𝘀𝘁.

The most challenging transition from "breaking into" a data career to "growing" your data career is your relationship with technical skills. Getting into data requires much investment in growing your technical skills and showing proficiency. The harsh truth is that these technical skills are just the bare minimum. While it's essential to upskill and improve your technical understanding, this alone won't get you promoted. What gets you promoted is applying your technical skills to business problems and getting buy-in to implement them. The key phrase here is "buy-in to implement," and this is where you NEED to become proficient in soft skills and selling internally to your peers and leadership. It's why I spend so much time talking to stakeholders across the business to understand the pains they experience and how data can support their respective business goals. It's why I spend so much time scoping problems and their impact. It's why I spend so much time bringing my stakeholder along the building process so they feel it's their project as well. Stop focusing on data itself, and instead focus on what data can do for your stakeholders and watch your career trajectory accelerate. #data #ai