📊 𝗗𝗮𝘆 1/𝟯𝟬 𝗪𝗵𝗮𝘁 𝗰𝗮𝗻 𝗮 𝗿𝗲𝗮𝗹 𝗲𝘀𝘁𝗮𝘁𝗲 𝗱𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝘁𝗲𝗹𝗹 𝘆𝗼𝘂? 🏠📊 While working on my 𝗔𝘂𝘀𝘁𝗶𝗻 𝗥𝗲𝗮𝗹𝘁𝘆 project, I started with a simple question: 𝗪𝗵𝗮𝘁 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗱𝗿𝗶𝘃𝗲𝘀 𝗽𝗿𝗼𝗽𝗲𝗿𝘁𝘆 𝗽𝗿𝗶𝗰𝗲𝘀? After analyzing 𝟭𝟱,𝟭𝟳𝟭 𝗽𝗿𝗼𝗽𝗲𝗿𝘁𝗶𝗲𝘀, a few things caught my attention: 🏠 𝟭𝟱,𝟭𝟳𝟭 properties analyzed 💰 $𝟰𝟬𝟱𝗞 typical property value 🏢 𝟮+ story properties showed higher values 🚿 Bathrooms & garage capacity also played a role 📍 Location & school ratings showed interesting patterns The best part? Using 𝗣𝗼𝘄𝗲𝗿 𝗕𝗜 𝗞𝗲𝘆 𝗜𝗻𝗳𝗹𝘂𝗲𝗻𝗰𝗲𝗿𝘀 to dig a little deeper instead of just looking at numbers. That’s what I enjoy about data 𝗧𝗵𝗲𝗿𝗲’𝘀 𝘂𝘀𝘂𝗮𝗹𝗹𝘆 𝗮 𝘀𝘁𝗼𝗿𝘆 𝗵𝗶𝗱𝗶𝗻𝗴 𝗯𝗲𝗵𝗶𝗻𝗱 𝘁𝗵𝗲 𝗻𝘂𝗺𝗯𝗲𝗿𝘀. 👀 What’s your favorite Power BI feature?

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𝗧𝘂𝗿𝗻𝗶𝗻𝗴 𝗖𝗼𝗳𝗳𝗲𝗲 ☕ 𝗶𝗻𝘁𝗼 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀 📊 | 𝗚𝗿𝗮𝗻𝗻𝘆 𝗖𝗮𝗳𝗲 𝗗𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱 𝗥𝗲𝘃𝗲𝗮𝗹 🔥 Hey Contra Fam 👋 Super excited to share my latest project the 𝗚𝗿𝗮𝗻𝗻𝘆 𝗖𝗮𝗳𝗲 𝗘𝘅𝗲𝗰𝘂𝘁𝗶𝘃𝗲 𝗣𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 𝗗𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱, built using 𝗣𝗼𝘄𝗲𝗿 𝗕𝗜 💻✨ This wasn’t just about creating visuals… It was about turning raw data into 𝗿𝗲𝗮𝗹 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗶𝗻𝘀𝗶𝗴𝗵𝘁𝘀 that actually matter 📈 🔥 𝗞𝗲𝘆 𝗛𝗶𝗴𝗵𝗹𝗶𝗴𝗵𝘁𝘀: 💰 $𝟰.𝟯𝟮𝗠 𝗥𝗲𝘃𝗲𝗻𝘂𝗲 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗲𝗱 → Strong month-over-month growth 🚀 🌍 𝗡𝗼𝗿𝘁𝗵𝗲𝗮𝘀𝘁 = 𝗥𝗲𝘃𝗲𝗻𝘂𝗲 𝗞𝗶𝗻𝗴 👑 → $𝟭.𝟳𝟭𝗠 (~𝟰𝟬%)** contribution 💎 𝟲𝟲% 𝗥𝗲𝘃𝗲𝗻𝘂𝗲 𝗳𝗿𝗼𝗺 𝗟𝗼𝘆𝗮𝗹𝘁𝘆 𝗠𝗲𝗺𝗯𝗲𝗿𝘀 → Retention is driving the business 💯 📦 Top Subscription Plan → “2 Meal Kits/3” is the most popular 🔥 📊 𝗣𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 𝘃𝘀 𝗧𝗮𝗿𝗴𝗲𝘁 → +𝟭𝟬.𝟲𝟮% 𝗥𝗲𝘃𝗲𝗻𝘂𝗲 𝗚𝗿𝗼𝘄𝘁𝗵 → +𝟯𝟭.𝟱% 𝗦𝗵𝗶𝗽𝗺𝗲𝗻𝘁𝘀 𝗜𝗻𝗰𝗿𝗲𝗮𝘀𝗲 🛠️ What skills I used: ⚡ 𝗗𝗔𝗫 𝗠𝗮𝗴𝗶c – PM comparisons, targets vs actuals, ARPC 🔗 𝗗𝗮𝘁𝗮 𝗠𝗼𝗱𝗲𝗹𝗶𝗻𝗴 – connecting multiple datasets like a puzzle 🎨 𝗨𝗜/𝗨𝗫 𝗗𝗲𝘀𝗶𝗴𝗻 – clean dark theme for premium feel 💡 Why this project matters? For me, data analytics isn’t just about charts… It’s about answering: 👉 𝗪𝗵𝘆 𝗶𝘀 𝘁𝗵𝗶𝘀 𝗵𝗮𝗽𝗽𝗲𝗻𝗶𝗻𝗴? 👉 𝗪𝗵𝗲𝗿𝗲 𝗶𝘀 𝘁𝗵𝗲 𝗼𝗽𝗽𝗼𝗿𝘁𝘂𝗻𝗶𝘁𝘆? 👉 𝗪𝗵𝗮𝘁 𝘀𝗵𝗼𝘂𝗹𝗱 𝘁𝗵𝗲 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗱𝗼 𝗻𝗲𝘅𝘁? And this dashboard does exactly that 💯

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Austin Realty Insights I built this interactive Power BI dashboard to explore Austin’s real estate market using a dataset of 15,171 properties. I cleaned and transformed the data using Power Query, created DAX measures and KPIs, and built interactive visuals with cross-filtering and Key Influencers. The main challenge was turning a large dataset with many attributes into a dashboard that stayed simple, useful, and easy to navigate. Through this project, I strengthened my skills in Power BI, DAX, Power Query, data modeling, and business-focused data visualization. Key result: Median property price of $405K, with insights into the factors associated with property values.

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Cover image for Built an interactive Power BI

Built an interactive Power BI retail dashboard to analyze sales, profit, products, stores, and customer performance through clear and actionable insights.

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Omer Khan

Data Analyst | Power BI, SQL & Excel | Turning Data into Ins