DAX Summarization Tricks in Power BI

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  • čas přidán 8. 11. 2023
  • Check out our newly launched M Language course ↗️ - goodly.co.in/learn-m-powerquery/
    In this Power BI tutorial, we will dive into some nifty summarization tricks that will help you calculate average units sold per day, sales of the best-selling day in a given period, sales of the best-selling product, and much more.
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    #powerbi #DataSummarization #Mlanguage #powerquery #tutorial #DataModel #Granularity #tips
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Komentáře • 46

  • @GoodlyChandeep
    @GoodlyChandeep  Před 7 měsíci

    Check out the M Language course ↗ - goodly.co.in/learn-m-powerquery/
    Download the file ⬇ - goodly.co.in/powerbi-dax-summarization-tricks/

  • @juja2819
    @juja2819 Před 7 měsíci +2

    Awesome! Have learned a lot from this one, thank you! :)

  • @enocharthur4322
    @enocharthur4322 Před měsícem

    This is a very critical concept in Dax. Thank you for making it so simple to understand. You're a genius!

  • @sajidmuhammed1484
    @sajidmuhammed1484 Před 7 měsíci +2

    One of your best videos on DAX. Superb!

  • @MarkBrady
    @MarkBrady Před 4 měsíci

    Your videos work perfectly for my learning style. Thanks for all you do.

  • @FernandoDuarte-uj5pn
    @FernandoDuarte-uj5pn Před 7 měsíci +3

    I really like your way of explaining, summarizing, and thinking of granularity. Excellent! Thanks a lot.

    • @scotttokaryk3714
      @scotttokaryk3714 Před měsícem

      I came here to say exactly that. That is an excellent way of explaining things. I had a few "aha" moments watching this video!
      Definitely subscribing to Goodly now.

  • @mahathmasadineni2884
    @mahathmasadineni2884 Před 7 měsíci

    Awesome learning..

  • @mogarrett3045
    @mogarrett3045 Před 7 měsíci

    excellent Sir thank you

  • @IvanCortinas_ES
    @IvanCortinas_ES Před 4 měsíci

    Absolutely masterful explanation. Clear, precise and direct. Granularity must be treated appropriately. Thanks for the content Chandeep!

  • @AAAExcel
    @AAAExcel Před 3 měsíci

    Brilliant work

  • @HemanthKumar-lb4xt
    @HemanthKumar-lb4xt Před 7 měsíci

    As usual Awesome! 🙂

  • @raghavendrabatchu3933
    @raghavendrabatchu3933 Před 7 měsíci

    bro... your explanation is wonderful, simply superb keep it up, Thanks a lot for the content

  • @meriamhaq123
    @meriamhaq123 Před 24 dny

    First i had to google about 'Granularity' 😂. Superb video and explanation

  • @ivanzhelyazkov6625
    @ivanzhelyazkov6625 Před 7 měsíci +4

    I just took the first few sections of the M course and it has been a great journey so far. Thank you, sir!

    • @GoodlyChandeep
      @GoodlyChandeep  Před 7 měsíci

      A lot more to come. I am glad you're enjoying the journey.

    • @skumar05
      @skumar05 Před 7 měsíci

      ​@@GoodlyChandeepsir your video is super .by watching your video I enhanced my knowledge. Now I am preparing for interview. Thank you so much sir.

  • @giri41
    @giri41 Před 2 měsíci

    Great video .. my visual complain too much data to compute .. any suggestions please

  • @Feel-the-music333
    @Feel-the-music333 Před 7 měsíci

    hi Goodly, it is helpful. can you make video if you have only month and year instead of date in your sales table. how you filter the data using date table.

  • @Nalaka-Wanniarachchi
    @Nalaka-Wanniarachchi Před 7 měsíci

    Great.Better if you mention the context transition happening behind the scene little bit.

  • @Rice0987
    @Rice0987 Před 7 měsíci

    I'd love this video even if i wouldnt know the word excel.🤗

  • @niranjanrana1714
    @niranjanrana1714 Před měsícem

    perfect

  • @FrOsTyBeArKiD
    @FrOsTyBeArKiD Před 3 měsíci +1

    But all of these are using X functions like MAXX, SUMXX, etc. What if I want to get the sum of all the sales for each month then calculate percentiles off of those months?

  • @jerrydellasala7643
    @jerrydellasala7643 Před 7 měsíci

    Great lesson, but the file Data.xlsx is missing from the Zip file!
    1. Open a blank worksheet in Excel.
    2. In Power BI select a table (Sales) and right click on a header and select Copy Table. Switch to Excel and Paste - this will paste in the entire table.
    3. In Power BI go to the go to the Model view and click the Transform data button to bring up the Power Query editor.
    4. Select the table you copied and go to the Source step. This will show the name of the file (which doesn't matter), and then go to the Navigation step if there is one. This will show you what was extracted from the file in this case "Source{[Item="Sales",Kind="Table"]}[Data]" which means that the paste you did in step 2 is a Table named Sales.
    5. Return to Excel, turn the Pasted data into a Table and name the Table Sales.
    6. Back in the Power BI PQ Editor, look at the other table's Source and Navigation steps. In this case the Navigation indicates a Table named Products.
    7. Repeat the steps to copy the table in Power BI, paste it into Excel, turn it into a Table named Products.
    8. You can now save the file with any name you want. I chose "DAXSummarizationTricksData.xlsx". Paste the full path of the file replacing the path between the quotes in the Source step.
    (HINT: If you're comfortable with a command prompt, the command "dir DAXSummarizationTricksData*/s/b" will list matching files with the full path where it can be easily copied. You must be in a folder above the folder the file is saved in to get the full path.)
    9. Step through the queries and correct any problems you encounter. In this case the table you copy will be missing some columns which are deleted in the last PQ step. You'll need to remove the missing columns from the Change Type step, and then you can delete the last step which removes the missing columns.
    Hope this helps others as it's not uncommon for sample files to be missing the underlying data files. This is kind of unnecessary unless you're trying to follow along - I just hate broken files!

  • @megabuilds3007
    @megabuilds3007 Před 7 měsíci +1

    You are just incridible. Thanks.

  • @HappyAnalysing
    @HappyAnalysing Před 7 měsíci

    Hi Chandeep,
    Can you please help us to create an org chart on power BI for HR Data

  • @kartickshow
    @kartickshow Před 7 měsíci

    Thanks

  • @mahathmasadineni2884
    @mahathmasadineni2884 Před 7 měsíci

    Hi Chandeep,
    Identify the top 10 partners based on their total sales amount across all products. For each top-selling partner, determine the product that contributed the most to their sales.
    Can you help me how can we solve it?

  • @abhi007dhami
    @abhi007dhami Před 2 měsíci

    Query - How can we Group By 2 date columns by taking MAX of Datecolumn1 and MIN of Datecolumn2 and then take SUM or Average of the Summarized Table , Sample Table :-
    Number Approval Level Datecolumn1 Datecolumn1 2 Age (Days)
    1761894 Level 1 9/13/23 12:55 PM 9/13/23 1:27 PM 0.023
    1761894 Level 1.1 9/13/23 1:27 PM 9/18/23 12:05 PM 3.943
    1761894 Level 2 9/18/23 12:05 PM 9/19/23 10:35 AM 0.937
    1761894 Level 2 9/18/23 12:05 PM 9/19/23 9:03 AM 0.873
    1761894 Level 3 9/19/23 10:35 AM 9/19/23 10:47 AM 0.009
    1761894 Level 3 9/19/23 10:35 AM 9/19/23 11:06 AM 0.022
    1761894 Level 4 9/19/23 11:06 AM 9/19/23 5:07 PM 0.251
    1761894 Level 4 9/19/23 11:06 AM 9/20/23 7:16 AM 0.84

  • @luisangelgarciaquiroz
    @luisangelgarciaquiroz Před 7 měsíci

    Does the course contain Spanish subtitles?

  • @gennarocimmino
    @gennarocimmino Před 7 měsíci +1

    Hi Chandeep,
    At minute 0:39 of the video, you show the structure of the Data Model and select the Sales Table, which magically turns green.
    But how do you get it to colour?
    It's just an amazing thing. How do you do it?
    :) :)
    Thanks a lot

  • @ferdinandsantos6680
    @ferdinandsantos6680 Před 7 měsíci

    Where you showed the sales of the best selling channel per month, how do you write the measure to show the best selling channel itself, not just the sales?

  • @prywatny_sil1360
    @prywatny_sil1360 Před 7 měsíci

    Would code like below do the trick too?
    AVERAGEX ( VALUES( 'Calendar'[Date] ), Sales[Units] )

    • @GoodlyChandeep
      @GoodlyChandeep  Před 7 měsíci

      There isn't a need to write values for calendar dates.. they are already unique

  • @mathew9665
    @mathew9665 Před 7 měsíci +3

    On the first example - the method is interesting, but if your counting the days in the sales table, there might be times when there where no sales for a day - would it not be best practice to count the days from the calendar table?

    • @paulgallagher2987
      @paulgallagher2987 Před 7 měsíci +2

      I guess this would depend what your report users would expect it to mean when they read "Avg Daily Sales". If my Fish & Chip shop is only open on a Friday, Sat & Sun, I'd expect my average daily sales figure to be (Week Total Sales / 3) not (Week Total Sales/ 7).
      However if I have a Mon-Fri operating business that sells a few big ticket items a month and doesn't invoice anything on some days, I'd expect my Avg Daily Sales figure to be (Monthly Sales Total / No. of Working Days in the month)
      Or perhaps (Monthly Sales Total / No. of days in the month) which is the method you suggest.
      Like many things it depends on the context and use case of the measure and the report.

    • @mathew9665
      @mathew9665 Před 7 měsíci

      @@paulgallagher2987 - Interesting; but you can then filter down the calenda table further - The idea is that you would be operating from central date table - this then enables quick changes and developments, to take into consideration the elements you have highlighted, also to then adapt them to other date fields in the fact table

  • @gagansingh3481
    @gagansingh3481 Před 7 měsíci

    Is the course contains recorded videos or its a live course .

  • @optiontrading5951
    @optiontrading5951 Před 3 měsíci

    achha hoga par bhai fast bol rahe ho english m thoda slow bolo taki ham bi samj paye

  • @manishrai265
    @manishrai265 Před 7 měsíci

    Q How does the revenue generated from document registration vary
    across districts in Telangana? List down the top 5 districts that showed
    the highest document registration revenue growth between FY 2019
    and 2022.
    i am using this Dax code but my answer not up to mark
    Revenue Growth2 =
    VAR Revenue2019 = CALCULATE(SUM(fact_stamps[TOTal]), FILTER(fact_stamps,fact_stamps[Years] = "FY2019"))
    VAR Revenue2022 = CALCULATE(SUM(fact_stamps[TOTal]), FILTER(fact_stamps,fact_stamps[Years] = "FY2022"))
    RETURN
    IF(ISBLANK(Revenue2019) && ISBLANK(Revenue2022), BLANK(),
    DIVIDE(Revenue2022 - Revenue2019, Revenue2019,0)
    )
    please help me get correct answer