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Certified Data Analyst | SQL β€’ PowerBi β€’ Excel Bsc. Food Science & Technology πŸ“§: [email protected]

Joined December 2025
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first internship doneeeee!
i got my first internship certificate!!!!🀭
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Happy birthday to me!🌸
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Power BI vs Excel vs Tableau, which do you use most?
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certificates say you learned. projects say you can.
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You don't need to know everything to get started.
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Your first analysis won't be perfect. Neither will your Fifth!! Stop trying to be perfect and just put it out here!
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Unpopular opinions in Data Analytics Some of these might annoy you. Check threadπŸ‘‡πŸ½
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Guess what?πŸ˜‚ Watching Tutorials can become a hiding place!!! Watching one more video feels productive, but at some point you have to open a dataset and get stuck on your own.
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7. Your first dashboard will be bad, and that’s normal Mine was. Everyone’s is. Build it anyway, post it, then make the next one better.
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5. Use whatever gets the job done well, not whatever is trending. 6. Learning the tool is the easy part. You can learn Power BI in a few weeks. Knowing what question to ask and what the answer actually means takes much longer.
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1. You don’t need 10 certificates to land your first job 2. More charts doesn’t mean more insight. 3. The tool matters less than the questions you ask. 4. Cleaning data is most of the job
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6 questions to ask before you start any analysis Most bad analysis comes from starting without the right questions. Check threadπŸ‘‡πŸ½
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Quick recap before you start: What decision will this help make? Who is this for? What does β€œsuccess” mean? What data do we actually have? What do we already believe? What’s the scope and timeframe?
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6. What’s the scope and timeframe? Which region, which period, which customers? If you don’t set the boundaries early, the analysis keeps growing and nothing gets finished.
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5. What do we already believe? Most people start with a guess about what the data will show. Ask what it is, so you can test it honestly instead of just confirming it.
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4. What data do we actually have? Check what’s available, how clean it is, and what’s missing before you promise anything. It’s better to flag a gap on day one than on deadline day.
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3. What does β€œsuccess” actually mean? β€œImprove sales” can mean revenue, number of orders, or new customers. Agree on the exact metric first, so you’re not arguing about it after the work is done.
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2. Who is this for? A manager who wants a quick yes or no needs something different from a team that wants to dig into details. Know who’s reading before you build anything.
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1. What decision will this help make? If nobody can say what they’ll do with the answer, pause. An analysis with no decision behind it usually ends up as a report nobody reads.
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6 storytelling mistakes killing your data presentations Good data doesn't guarantee a good story. Here's what quietly kills the narrative. Check threadπŸ‘‡πŸ½
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3. Too much data, not enough story Showing every chart you built feels thorough, but it drowns the one insight that actually matters. Cut ruthlessly, keep only what supports the point.
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2. No narrative arc A story has a beginning (what we expected), a middle (what actually happened), and an end (what we should do about it).
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