Power BI Sales Forecasting Using DAX | Cumulative Sales & Actual vs Forecast Dashboard

📊 Learn Power BI Sales Forecasting Using DAX – Step-by-Step Tutorial In this video, I demonstrate how to create a sales forecasting solution in Power BI using DAX measures. You will learn how to calculate cumulative sales, identify the last actual sales month, calculate average monthly sales, and forecast future sales based on historical performance. This tutorial is useful for Power BI developers, data analysts, business intelligence professionals, and anyone learning advanced DAX calculations. 🎯 What You Will Learn ✅ Calculate cumulative sales using `CALCULATE`, `SUM`, `FILTER`, and `ALLSELECTED`. ✅ Identify the last actual sales date using `MAX` and `REMOVEFILTERS`. ✅ Calculate the last actual sales month. ✅ Forecast future sales using average monthly sales. ✅ Build an Actual vs Forecast sales measure. ✅ Use `DATEDIFF` and `DIVIDE` in DAX calculations. ✅ Visualize actual and forecast sales trends in a Power BI line chart. 📌 Important Note: These are two different forecasting approaches. The first extends cumulative sales using a month-based calculation, while the second forecasts future sales using the average of actual monthly sales. Validate the results against your dataset and business requirements before using them for business decisions. About Me I am a Power BI & Microsoft Fabric Developer | Founder, interested in building interactive dashboards, business intelligence reports, data models, and analytical solutions. I am currently looking for: Power BI Developer opportunities Data Analyst and Business Intelligence roles Freelance Power BI projects Remote job opportunities International clients and collaborations 📩 Email: vrmatheen@gmail.com 📱 Phone / WhatsApp: +91-7975327349 If you need help with Power BI dashboards, DAX measures, Excel-to-Power BI reporting, or sales analytics, feel free to contact me. 🌍 Target audience: USA, UK, Canada, Australia, India, Bengaluru, Dubai, and Saudi Arabia. 👍 Like the video, share it with fellow data professionals, and subscribe for more Power BI, DAX, SQL, Python, and data analytics tutorials. #Microsoft #Accenture #Deloitte #TCS #Infosys #Wipro #HCLTech #Capgemini #Cognizant #LTIMindtree #TechMahindra #IBM #NTTData #Kyndryl #CGI #Sigmoid #KPIPartners #DataSemantics #LatentViewAnalytics #TigerAnalytics #Tredence #FractalAnalytics #MuSigma #Quantiphi #ZSAssociates #EXL #Course5Intelligence #Evalueserve #NeoStatsAnalytics #Snowflake #Databricks #Oracle #SAP #Salesforce #ServiceNow #Adobe #Amazon #Google #Atlassian #Cisco #DellTechnologies #HP #Broadcom #NVIDIA #Intel #Teradata #Cloudera #SAS #Qlik #ThoughtSpot #Palantir #Elastic #Confluent #MongoDB #NetApp #Rubrik #HashiCorp #JPMorganChase #GoldmanSachs #MorganStanley #Citi #WellsFargo #AmericanExpress #Visa #Mastercard #PayPal #Paytm #PhonePe #Razorpay #CRED #Groww #Zerodha #WalmartGlobalTech #Target #Tesco #Flipkart #Myntra #Swiggy #Zomato #Uber #Airbnb #Bookingcom #Siemens #Bosch #SchneiderElectric #Philips #GEHealthCare #DataAnalytics #DAX #PowerQuery #SQL #DataVisualization #BengaluruJobs #RemoteJobs #IndiaJobs #Hiring #OpenToWork