Skip to main content

20 Power BI Dax Measures


UserPower bi 20 dax measures 20 DAX (Data Analysis Expressions) measures in Power BI with examples:
  1. Total Sales:

    scss
    Total Sales = SUM(Sales[Amount])
  2. Average Sales Price:

    scss
    Avg Sales Price = AVERAGE(Sales[Amount])
  3. Total Units Sold:

    mathematica
    Total Units Sold = SUM(Sales[Quantity])
  4. Total Customers:

    scss
    Total Customers = COUNTROWS(Customer)
  5. Total Products:

    mathematica
    Total Products = COUNTROWS(Product)
  6. Maximum Sales Amount:

    scss
    Max Sales Amount = MAX(Sales[Amount])
  7. Minimum Sales Amount:

    scss
    Min Sales Amount = MIN(Sales[Amount])
  8. Sales Growth Percentage:

    mathematica
    Sales Growth % = (Total Sales - [Total Sales Last Year]) / [Total Sales Last Year]
  9. Total Profit:

    scss
    Total Profit = SUM(Sales[Profit])
  10. Total Orders:

    scss
    Total Orders = COUNTROWS(Orders)
  11. Total Customers with Sales:

    css
    Total Customers with Sales = COUNTROWS(FILTER(Customer, [Total Sales] > 0))
  12. Total Sales by Region:

    mathematica
    Total Sales by Region = SUMX(VALUES(Region[RegionName]), [Total Sales])
  13. Total Sales by Year:

    scss
    Total Sales by Year = SUMX(VALUES(Calendar[Year]), [Total Sales])
  14. Running Total Sales:

    scss
    Running Total Sales = SUMX(FILTER(ALL(Calendar), Calendar[Date] <= MAX(Calendar[Date])), [Total Sales])
  15. Top N Products by Sales:

    mathematica
    Top N Products by Sales = TOPN(5, ALL(Product), [Total Sales])
  16. Rolling Average Sales (3 Months):

    scss
    Rolling Avg Sales 3M = AVERAGEX(DATESYTD(Calendar[Date]), [Total Sales])
  17. Total Sales to Date:

    mathematica
    Total Sales to Date = TOTALYTD([Total Sales], Calendar[Date])
  18. Sales Rank by Product:

    mathematica
    Sales Rank by Product = RANKX(ALL(Product), [Total Sales], , DESC, Dense)
  19. Customer Churn Rate:

    css
    Customer Churn Rate = DIVIDE([Lost Customers], [Total Customers])
  20. Year-to-Date Growth:

    mathematica
    YTD Growth = DIVIDE([Total Sales], [Total Sales Last Year]) - 1

These measures cover a range of common calculations in Power BI, including basic aggregations, comparisons, and time-based calculations. You can adapt and customize them to suit your specific data and reporting needs

Comments

Popular posts from this blog

Improve your Excel Productivity with these Shortcuts and formulas

I have given below 45 tips and tricks to improve your productivity while working in Excel. Useful Keyboard Shortcuts 1.  To format any selected object , press ctrl+1 2.  To insert current date , press ctrl+; 3.  To insert current time , press ctrl+shift+; 4.  To repeat last action , press F4 5.  To edit a cell comment , press shift + F2 6.  To autosum selected cells , press alt + = 7.  To see the suggest drop-down in a cell , press alt + down arrow 8.  To enter multiple lines in a cell , press alt+enter 9.  To insert a new sheet , press shift + F11 10.  To edit active cell , press F2 (places cursor in the end) 11.  To hide current row , press ctrl+9 12.  To hide current column , press ctrl+0 13.  To unhide rows in selected range , press ctrl+shift+9 14.  To unhide columns in selected range , press ctrl+shift+0 15.  To recalculate formulas , press F9 16.  To select data in current region , press ctrl+shift+8 ...

Data Analytics

Introduction to Data Analytics What is Data Analytics? Data Analytics is the process of exploring and analyzing large data sets to help data driven decision making.                         Analyze Data        Decision Making Definition Data when suitably filtered and analysed along with other related Data Sources and a suitable Analytics applied can provide valuable information to various organizations, industries, business, etc. in the form of prediction, recommendation, decision and the like. Applications of Data Analytics Finance & Accounting, Business analytics, Fraud , Healthcare, Information Technology, Insurance, Taxation , Internal Audit, Digital forensic, Transportation, Food, Delivery, FMCG, Planning of cities, Expenditure, Risk management, Risk detection, Security, Travelling, Managing Energy, Internet searching, Digital advertisement , etc. Real life examples of Data Analytics 1. ...

Basics of Microsoft Excel

A. Microsoft Excel Basics of Excel   There are 5 important areas in the screen. 1. Quick Access Toolbar: This is a place where all the important tools can be placed. When you start Excel for the very first time, it has only 3 icons (Save, Undo, Redo). But you can add any feature of Excel to to Quick Access Toolbar so that you can easily access it from anywhere (hence the name). 2. Ribbon: Ribbon is like an expanded menu. It depicts all the features of Excel in easy to understand form. Since Excel has 1000s of features, they are grouped in to several ribbons. The most important ribbons are – Home, Insert, Formulas, Page Layout & Data. 3. Formula Bar: This is where any calculations or formulas you write will appear. You will understand the relevance of it once you start building formulas. 4. Spreadsheet Grid: This is where all your numbers, data, charts & drawings will go. Each Excel file can contain several sheets. But the spreadsheet grid shows few rows & column...