Salam Sir, When we shall be starting SQL, whether it will be MSSQL, PostGre, MySQl or else? I have already installed MSSQL 2022 and SSMS 22.😅

Please join the facebook group. End of this month, you would not be able to access the skool community. https://www.facebook.com/share/g/1HdVZQtETS/?mibextid=wwXIfr

We have people in this community from many different backgrounds such as Finance, Healthcare, Retail, Marketing, Logistics, IT and many more. I was thinking, why should all the learning sessions come from me? Everyone here has knowledge and experience that others can learn from. What if we start community led sessions where members can volunteer to share something from their own field? For example, someone from Finance could explain important financial KPIs and how they are analyzed. Someone from Logistics could explain logistics operations and KPIs. Someone from Healthcare could introduce healthcare data and analytics. It does not need to be a formal lecture. Even a 20 to 30 minute session sharing your experience, business processes, important KPIs, data or a real world analytics example could be very valuable for everyone. This way, we can learn not only Power BI, SQL and VBA, but also understand how data and analytics are actually used across different industries. My goal is to build a community where we learn from each other, share our experience and grow together rather than depending on one person for all the learning. What do you think about this idea? Would you be interested in sharing something from your field with the community?

About the dataset: A synthetic heart-disease dataset built for 2026: HbA1c, full lipid panel, wearable step counts, sleep and stress - the risk factors the classic 300-row heart datasets never recorded. Ideas to get you started: - Build a heart-disease classifier and check which factors carry it. - Do wearable owners actually show a lower risk profile? Test it properly - and watch for confounding by age. - Which matters more: the lipid panel or the lifestyle columns? Compare model families. - Is the sleep-risk relationship really U-shaped? Bin sleep_hours and plot it. - Build a simple interpretable risk score and compare it to a gradient-boosted model. - Explore HDL vs LDL - does the ratio beat either one alone?

I wanted to share a Power BI project I recently completed using the IBM HR Analytics Employee Attrition & Performance dataset. My goal was not just to create charts, but to practice taking a real business question → transforming the data → building an interactive dashboard → generating actionable insights. 🎯 Business Question Why are employees leaving, and what patterns can HR leadership identify to improve employee retention? 📊 Dashboard Includes - KPI cards for Total Employees, Attrition Rate, Average Monthly Income & Average Years at Company - Attrition by Department - Attrition by Gender - Age vs. Monthly Income - Attrition by Education Level - Attrition by Work-Life Balance - Job Satisfaction × Job Role × Attrition analysis - Interactive slicers for Marital Status, Age, Department & Gender - Key Insights section 🔎 Some Interesting Findings 1️⃣ Overall Attrition Rate: 16.12% This provides the baseline for understanding employee turnover. 2️⃣ Younger employees show higher turnover The analysis shows a noticeable concentration of attrition among employees around the 20–30 age range, which could indicate opportunities around career development, compensation and employee engagement. 3️⃣ Work-life balance matters The analysis shows interesting differences in attrition across work-life balance categories, highlighting an area HR could investigate further. 4️⃣ R&D has the highest number of attrition cases However, this is an important lesson: attrition count ≠ attrition rate. Because R&D has a larger workforce, the absolute number of departures needs to be considered alongside the department's total employee population. 5️⃣ Education, job role and satisfaction reveal additional patterns Combining these dimensions can help HR identify employee segments that may benefit from targeted retention strategies. 🧠 What I'm Practicing ✅ Power BI ✅ Power Query ✅ DAX ✅ Data Modeling ✅ KPI Development ✅ Data Visualization ✅ Interactive Dashboard Design ✅ Conditional Formatting