George Zervas’ Post

Before any dashboard, chart, or insight , there’s this: The messy, unfiltered, chaotic dataset that needs attention. In this project, I started with a raw Excel file filled with: • Inconsistent date formats • Names in different cases • Missing Manager IDs and Termination Dates • Wrong data types (numbers showing as text, and vice versa) I brought the dataset into Power BI Power Query, and that’s where the real magic began ✨ From trimming and cleaning names, capitalizing where necessary, replacing nulls with meaningful values, to carefully converting data types (text → number → date), every transformation step mattered. I even had to troubleshoot the DOB column that kept throwing errors,and learned how powerful “Using Locale” can be in fixing inconsistent date formats. Power Query truly reminded me that: 👉 Data cleaning isn’t just a step; it’s the foundation. Without it, every calculation, every dashboard, every insight would be unreliable. Sharing both the before (Excel) and after (Power BI) videos to show what transformation really looks like in action 🚀 #PowerBI #DataCleaning #DataTransformation #DataAnalytics #PowerQuery #DataPreparation #LearningJourney #AnalystMindset

Excited to share my latest Power BI project — Global Superstore Dashboard, designed to transform raw data into clear and actionable business insights. 📊Project Highlights: Developed an interactive dashboard to track key KPIs such as Sales, Profit, Quantity, and Profit Margin across multiple dimensions. Conducted Regional & Category Analysis to identify high-performing markets and product segments. Used DAX measures for dynamic calculations, including Year-over-Year Growth and Profit-to-Sales Ratio. Leveraged Power Query for data cleaning and transformation to ensure accuracy and consistency.  💡 Insights Gained: Identified top-performing regions and customers driving revenue growth. Highlighted underperforming categories with potential for optimization. Discovered seasonal sales patterns and profitability trends over time. #PowerBI #DataAnalytics #BusinessIntelligence #DataVisualization #PowerQuery #DAX #Excel #DashboardDesign #Analytics #PowerBIDashboard

🔍 What Is Drill Down and Drill Up in Power BI? In Power BI, Drill Down and Drill Up let you explore your data at different levels of detail within a hierarchy — such as going from Year → Quarter → Month in a date field. These features are used in visuals like bar charts, column charts, line charts, and matrix tables when a hierarchical structure is present. --- 📉 Drill Down Purpose: To see more detailed data. What Happens: When you drill down, Power BI shows a lower level of your data hierarchy. Example: a) You have sales data by Year. b) Click to drill down → Now you see sales by Quarter within that Year. c) Drill again → See Month, and so on. --- 📈 Drill Up Purpose: To return to a more summarized level. What Happens: You move back up the hierarchy. Example: 1) You're viewing data by Month. 2) Click to drill up → See Quarter. 3) Drill up again → See Year. 💡 Why Use Drill Down/Up? To explore data interactively. To let users answer their own questions without switching pages. To keep dashboards clean and show only necessary detail when needed. #PowerBI #MicrosoftPowerBI #PowerBIReports #PowerBIDashboard #DataVisualization #BusinessIntelligence #DataAnalytics #PowerQuery #DAX

Most dashboard problems aren’t design — they’re dirt. Here’s how I clean fast in Power BI, so leaders trust what they see: 🧱 Set the foundation Set data types first, flip on Column quality/profile/distribution, and mark a proper Date table. 🔍 Hunt the weird Surface outliers, dupes, and sudden spikes with Column distribution or a quick Group By. 🧩 Decide the blanks Drop or fill but make it a rule. Use Replace values / Fill down and log it in Applied Steps. 🌐 Speak one language Trim/Clean text, standardize units/time zones, and merge lookup tables so codes/IDs are consistent. ✅ Trust but verify Match row counts to the source, keep lookup→fact as 1: many, and use quick DAX (COUNTROWS / DISTINCTCOUNT) to confirm the numbers #BusinessAnalyst #DataAnalyst #PowerBI #PL300 #PowerQuery #DAX #SQL #DataCleaning #DataQuality #DataModeling #UAT #StakeholderManagement

🎯 Power BI DAX Cheat Sheet — My 7 Most Used Formulas (Save this!) If you’ve ever struggled remembering DAX functions… you’re not alone 😅 After 6+ years in Power BI, these are the 7 DAX formulas I use in almost every project 👇 🧠 1. CALCULATE() Your gateway to context manipulation. 👉 Turns simple measures into powerful insights. 📅 2. DATESYTD() For perfect Year-to-Date visuals without complex date logic. 📊 3. SUMX() Iterates over rows — super handy when SUM doesn’t cut it. ⚙️ 4. FILTER() The secret sauce behind dynamic, rule-based measures. 🧩 5. RELATED() Brings columns from another table like a pro. Goodbye LOOKUPs! 📆 6. DATEADD() Easy way to compare month-over-month or year-over-year data. 🏁 7. VAR Use variables to simplify complex measures — readable + faster. 💡 Pro Tip: Wrap your measures with variables and comments. You’ll thank yourself later when debugging at 11 PM 😅 💬 Want my “Power BI DAX Quick Reference Guide (PDF)” that includes 25+ real examples with syntax? Drop a “DAX” in the comments ⬇️ I’ll DM you the complete cheat sheet! Also wanted to learn DAX or preparing for Power BI interview don't forget the find most suitable DAX videos here : https://lnkd.in/gKDTjP5h 🔁 Reshare it with your connection so that others can take benefit from you. #PowerBI #DAX #DataAnalytics #BusinessIntelligence #PowerBIDeveloper #LinkedInTopVoice

💡 Creating Connection Between Slicers The Hidden Power of Data Visualization! Have you ever wondered why your slicers in Excel or Power BI don’t “talk” to each other? 👀 That’s because they’re not connected yet! When you create a connection between slicers, you’re basically telling your data “Hey, work together and give me ONE clear story.” 📊 ✨ Here’s what happens when slicers are connected: ✅ You can control multiple tables or charts with a single click. ✅ Your dashboards become more dynamic and interactive. ✅ You save time while making your reports look cleaner and smarter. How to do it (Step by step guide in the attached video): 1️⃣ Go to your slicer → Click ‘Report Connections’ (Excel) or ‘Sync Slicers’ (Power BI). 2️⃣ Select the visuals or tables you want linked. 3️⃣ Watch the magic happen when you filter once and all visuals respond! 💥 🔹 Connected slicers = connected insights. Because every great dashboard tells one story, not many fragments. Would you like me to create a story from your data? If Yes, send a message to transform your data into Business Growth. #WPS #exceltips #PowerBI #DataAnalysis #DataVisualizationinExcel #ProductivityHacks

🧠 Think Your Power BI Reports Are Slow? Maybe It’s Not Power BI’s Fault! 😬 𝗛𝗼𝗹𝗱 𝘂𝗽! 🤔 𝗧𝗵𝗲 𝗿𝗲𝗮𝗹 𝗰𝘂𝗹𝗽𝗿𝗶𝘁 𝗺𝗶𝗴𝗵𝘁 𝗯𝗲 𝘀𝗼𝗺𝗲𝘁𝗵𝗶𝗻𝗴 𝗰𝗮𝗹𝗹𝗲𝗱 𝗤𝘂𝗲𝗿𝘆 𝗙𝗼𝗹𝗱𝗶𝗻𝗴 (𝘆𝗮𝗮𝗻𝗶 𝘄𝗼𝗵 𝗰𝗵𝗲𝗲𝘇 𝗷𝗶𝘀𝗸𝗲 𝗯𝗶𝗻𝗮 𝗣𝗼𝘄𝗲𝗿 𝗕𝗜 𝘁𝗵𝗼𝗱𝗮 𝗴𝘂𝘀𝘀𝗮 𝗸𝗮𝗿 𝗹𝗲𝘁𝗮 𝗵𝗮𝗶 😅). Let’s decode it in simple words 👇 When Query Folding works properly, Power BI says to your data source (like SQL): “𝗛𝗲𝘆 𝗯𝘂𝗱𝗱𝘆, 𝘆𝗼𝘂 𝗱𝗼 𝘁𝗵𝗲 𝗳𝗶𝗹𝘁𝗲𝗿𝗶𝗻𝗴 𝗮𝗻𝗱 𝗰𝗹𝗲𝗮𝗻𝗶𝗻𝗴 — 𝗷𝘂𝘀𝘁 𝘀𝗲𝗻𝗱 𝗺𝗲 𝘁𝗵𝗲 𝗳𝗶𝗻𝗮𝗹, 𝗻𝗲𝗮𝘁 𝗱𝗮𝘁𝗮!” 😎 But when it breaks, Power BI downloads everything and tries to clean it by itself… and that’s when it becomes slow and heavy 🐢 💡 Why Query Folding Matters: ✅ 𝙏𝙝𝙚 𝙙𝙖𝙩𝙖 𝙨𝙤𝙪𝙧𝙘𝙚 𝙙𝙤𝙚𝙨 𝙖𝙡𝙡 𝙩𝙝𝙚 𝙝𝙚𝙖𝙫𝙮 𝙡𝙞𝙛𝙩𝙞𝙣𝙜 ✅ 𝙋𝙤𝙬𝙚𝙧 𝘽𝙄 𝙧𝙪𝙣𝙨 𝙨𝙢𝙤𝙤𝙩𝙝𝙚𝙧 𝙖𝙣𝙙 𝙛𝙖𝙨𝙩𝙚𝙧 ✅ 𝙍𝙚𝙥𝙤𝙧𝙩𝙨 𝙗𝙚𝙘𝙤𝙢𝙚 𝙚𝙛𝙛𝙞𝙘𝙞𝙚𝙣𝙩 𝙖𝙣𝙙 𝙥𝙧𝙤𝙛𝙚𝙨𝙨𝙞𝙤𝙣𝙖𝙡 ⚡ So next time your report feels sluggish — Don’t blame Power BI, check if your Query Folding is still your friend 😉 #PowerBI #DataAnalytics #DataAnalyst #BusinessIntelligence #DataVisualization #QueryFolding #PowerBIReports #DataPerformance #SQL

𝗠𝗮𝘀𝘁𝗲𝗿 𝗧𝗵𝗲𝘀𝗲 𝟭𝟬 𝗠𝘂𝘀𝘁-𝗞𝗻𝗼𝘄𝗻 𝗗𝗔𝗫 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝘀 𝘁𝗼 𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺 𝗬𝗼𝘂𝗿 𝗣𝗼𝘄𝗲𝗿 𝗕𝗜 𝗥𝗲𝗽𝗼𝗿𝘁𝘀! 🚀 DAX (Data Analysis Expressions) is the language that makes Power BI truly powerful. It lets you create custom measures and calculated columns that turn raw data into actionable insights. To truly level up your dashboards, you need to master these 10 core functions: CALCULATE(): The most vital function. It evaluates an expression within a modified filter context (e.g., Year-over-Year comparison). SUMX() / AVERAGEX(): Iterators that perform row-by-row calculations before aggregating the results (e.g., calculating total revenue from Price * Quantity). ALL() / ALLEXCEPT(): Essential for controlling filters, allowing you to calculate percentages of totals or ignore specific slices of data. RELATED(): Bridges tables in your data model, pulling a value from a related 'one-side' table into a calculated column or measure context. DIVIDE(): Always use this instead of /. It provides robust division and handles division-by-zero errors gracefully. IF() / SWITCH(): Defines conditional logic to categorize or flag data based on certain criteria. VALUES() / DISTINCT(): Used to identify or count unique values in a column, great for dynamic checks. DATEADD() / SAMEPERIODLASTYEAR(): Core time intelligence functions for comparing sales across different time periods. RANKX(): Calculates the dynamic rank of items (like products or customers) based on a measure. FILTER(): Returns a subset of a table. It's often used inside CALCULATE to define the exact rows for a specific calculation. Boost Your Data Skills! Master these functions, and you'll go from a basic user to a Power BI data ninja! #PowerBI #DAX #DataAnalysis #BusinessIntelligence #Excel #DataAnalytics #MicrosoftPowerBI #DataSkills

🚀 𝐌𝐚𝐬𝐭𝐞𝐫 𝐃𝐀𝐗 𝐅𝐮𝐧𝐜𝐭𝐢𝐨𝐧𝐬 𝐢𝐧 𝐏𝐨𝐰𝐞𝐫 𝐁𝐈! 💡 If you want to take your Power BI skills to the next level, understanding 𝐃𝐀𝐗 (𝐃𝐚𝐭𝐚 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬 𝐄𝐱𝐩𝐫𝐞𝐬𝐬𝐢𝐨𝐧𝐬) is a must! DAX helps you perform advanced calculations, create powerful measures, and build insightful dashboards 📊 Here are some of the 𝐦𝐨𝐬𝐭 𝐮𝐬𝐞𝐝 𝐃𝐀𝐗 𝐟𝐮𝐧𝐜𝐭𝐢𝐨𝐧 categories 👇 🗓️ 𝐂𝐚𝐥𝐞𝐧𝐝𝐚𝐫 🔢 𝐂𝐨𝐮𝐧𝐭𝐢𝐧𝐠 📈 𝐀𝐠𝐠𝐫𝐞𝐠𝐚𝐭𝐞 (𝐒𝐔𝐌, 𝐀𝐕𝐄𝐑𝐀𝐆𝐄, 𝐞𝐭𝐜.) 📉 𝐌𝐈𝐍 / 𝐌𝐀𝐗 📅 𝐃𝐚𝐭𝐞 🧮 𝐀𝐋𝐋 🔤 𝐓𝐞𝐱𝐭 🔗 𝐑𝐞𝐥𝐚𝐭𝐞𝐝 🎯 𝐅𝐢𝐥𝐭𝐞𝐫 ✨ Whether you’re analyzing 𝐝𝐚𝐭𝐚 𝐭𝐫𝐞𝐧𝐝𝐬, 𝐜𝐨𝐦𝐩𝐚𝐫𝐢𝐧𝐠 𝐩𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞, 𝐨𝐫 𝐛𝐮𝐢𝐥𝐝𝐢𝐧𝐠 𝐊𝐏𝐈𝐬 — DAX gives you the flexibility and control you need! 💬 Are you using DAX in your Power BI reports yet? 𝐒𝐡𝐚𝐫𝐞 𝐲𝐨𝐮𝐫 𝐟𝐚𝐯𝐨𝐫𝐢𝐭𝐞 𝐃𝐀𝐗 𝐟𝐮𝐧𝐜𝐭𝐢𝐨𝐧 𝐢𝐧 𝐭𝐡𝐞 𝐜𝐨𝐦𝐦𝐞𝐧𝐭𝐬 𝐛𝐞𝐥𝐨𝐰! 👇 #PowerBI #DAX #DataAnalytics #BusinessIntelligence #DataVisualization #PowerQuery #DataScience #Excel #Analytics #VocabValue

⚡ Top 3 Power BI Features for Beginners 3️⃣ Power Query – clean & transform your data 🧹 2️⃣ DAX Measures – create smart calculations 📈 1️⃣ Data Model – connect tables for fast, accurate reports 🌟 Master these and you’re already ahead! 👉 Learn more at createandlearn.net #powerbi #data #analytics #businessintelligence #excel #datacareer #createandlearn