Pivotalstats
Pivotalstats
  • Видео 108
  • Просмотров 827 550
Top 5 Usages of EARLIER dax function | Power BI
In this video we will see how to apply Countif, Sumif, Rolling or Cummulative Sum and more using EARLIER dax function in Power BI
Data Used :
pivotalstats.com/top-5-usages-of-earlier-dax-function-in-power-bi/
Visit my blog for more content :
www.pivotalstats.com/
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Просмотров: 376

Видео

Calculation Groups - Reduce Measure Overload Instantly | Power BI
Просмотров 615Месяц назад
In this video, we explore the Calculation Groups feature in Power BI and how it drastically reduces the number of measures you need in your reports. Say goodbye to measure overload and cluttered data models! I'll guide you through creating reusable time intelligence calculations Data & Logic www.pivotalstats.com/post/how-to-reduce-measure-clutter-using-calculation-group-in-power-bi Visit my blo...
What is Visual Calculations in Power BI: A Step-by-Step Guide!
Просмотров 8752 месяца назад
Power BI’s new Visual Calculations feature is a game-changer! In this video, we dive deep into everything you need to know about this exciting update. From enabling the feature to exploring its interface, and understanding best practices, we’ll guide you through how to use Visual Calculations to simplify your data analysis and make your reports more dynamic. 🔍 What You’ll Learn: How to enable a...
Power BI End to End Churn Analysis Portfolio Project | Power BI + SQL + Machine Learning | 2024
Просмотров 34 тыс.4 месяца назад
#powerbi #dataanalytics #powerbitutorial #machinelearning #randomforest #sqlserver #sqlservermanagementstudio #python In this complete CHURN ANALYSIS project using SQL Server, Power BI & Python, we will cover a wide range of topics which includes 1. ETL process in SQL Server 2. Data Cleaning in SQL Server 3. Power BI Transformations 4. Power BI Visualization & Enhancing Visuals 5. Build Machine...
Mastering Top 5 Uses of DAX Query View | Power BI
Просмотров 6 тыс.6 месяцев назад
Unlock the full potential of Power BI with this deep dive into the Top 5 usages of DAX Query View. Whether you're a business analyst, data enthusiast, or just getting started with Power BI, this video will guide you through powerful ways to use DAX queries to enhance your data analysis and reporting capabilities. Data Used: pivotalstats.com/top-5-usages-of-dax-query-view-in-power-bi/ Visit my b...
Best Power Query Tool to Check & Enhance Data Quality !
Просмотров 1,1 тыс.7 месяцев назад
Unlock the full potential of your data with Power Query Data Profiler. In this comprehensive tutorial, learn how to seamlessly navigate through Power Query to identify errors, manage blanks, and glean essential descriptive statistics from your datasets. Dataset used: pivotalstats.com/wp-content/uploads/2024/11/Electric_Vehicle_Population_Data.zip Visit my blog for more content : www.pivotalstat...
SQL Bootcamp - Learn SQL in 2 Hours | Beginners | GCP | BigQuery | [Full Course]
Просмотров 4,2 тыс.7 месяцев назад
SQL Bootcamp - Learn SQL in 2 Hours | Beginners | GCP | BigQuery | [Full Course]
Query Folding in Power BI | Complete Guide
Просмотров 4,5 тыс.8 месяцев назад
Query Folding in Power BI | Complete Guide
Understanding Row Context and Filter Context in Power BI
Просмотров 6 тыс.8 месяцев назад
Understanding Row Context and Filter Context in Power BI
Solving DATE CONVERSION ERROR in Power BI / Power Query | Comprehensive Guide
Просмотров 10 тыс.11 месяцев назад
Solving DATE CONVERSION ERROR in Power BI / Power Query | Comprehensive Guide
Power BI DAX Tutorial - Beginner to Advanced [Full Course]
Просмотров 120 тыс.Год назад
Power BI DAX Tutorial - Beginner to Advanced [Full Course]
Power BI Project End to End Dashboard Development | Beginners | Power BI Tutorial 2024
Просмотров 361 тыс.Год назад
Power BI Project End to End Dashboard Development | Beginners | Power BI Tutorial 2024
Comprehensive Guide on MATPLOTLIB, SEABORN & PLOTLY | Python Data Analysis
Просмотров 2,3 тыс.Год назад
Comprehensive Guide on MATPLOTLIB, SEABORN & PLOTLY | Python Data Analysis
How to Pivot & Unpivot Dataframe in Pandas | Python Data Analysis
Просмотров 1,4 тыс.Год назад
How to Pivot & Unpivot Dataframe in Pandas | Python Data Analysis
Pandas Merge Vs. Join: Which One Should You Use? | Python Data Analysis
Просмотров 981Год назад
Pandas Merge Vs. Join: Which One Should You Use? | Python Data Analysis
Mastering Pandas Series: Top 25 Essential Methods for Data Analysis | Python Data Analysis
Просмотров 546Год назад
Mastering Pandas Series: Top 25 Essential Methods for Data Analysis | Python Data Analysis
Complete PANDAS guide for Beginners | Python Data Analysis
Просмотров 943Год назад
Complete PANDAS guide for Beginners | Python Data Analysis
Complete NUMPY for Beginners in just 10 minutes | Python Data Analysis
Просмотров 2,6 тыс.Год назад
Complete NUMPY for Beginners in just 10 minutes | Python Data Analysis
Two Most Important Python Libraries for Data Analysis | Python Data Analysis
Просмотров 777Год назад
Two Most Important Python Libraries for Data Analysis | Python Data Analysis
Part 6 - FOR LOOP & WHILE LOOP in Python | Python Data Analysis
Просмотров 197Год назад
Part 6 - FOR LOOP & WHILE LOOP in Python | Python Data Analysis
Part 5 - COLLECTION DATA TYPES in Python | Python Data Analysis
Просмотров 250Год назад
Part 5 - COLLECTION DATA TYPES in Python | Python Data Analysis
Part 4 - Creating Custom Functions & Adding Parameters in Python | Python Data Analysis
Просмотров 191Год назад
Part 4 - Creating Custom Functions & Adding Parameters in Python | Python Data Analysis
Part 3 - Conditional Statements, Indexing & Comments in Python | Python for Data Analysis
Просмотров 181Год назад
Part 3 - Conditional Statements, Indexing & Comments in Python | Python for Data Analysis
Part 2 - OPERATORS in Python | Python Data Analysis
Просмотров 220Год назад
Part 2 - OPERATORS in Python | Python Data Analysis
Part 1 - Python basics for DATA ANALYSIS | Python Data Analysis
Просмотров 880Год назад
Part 1 - Python basics for DATA ANALYSIS | Python Data Analysis
Introduction to Data Analysis & its 6 Steps | Python Data Analysis
Просмотров 263Год назад
Introduction to Data Analysis & its 6 Steps | Python Data Analysis
How to SCHEDULE QUERIES & create STORED PROCEDURES in SQL | BigQuery
Просмотров 7 тыс.Год назад
How to SCHEDULE QUERIES & create STORED PROCEDURES in SQL | BigQuery
Important TEXT manipulation function to merge & split text | BigQuery
Просмотров 1,1 тыс.Год назад
Important TEXT manipulation function to merge & split text | BigQuery
STANDARD vs. MATERIALIZED views in SQL | BigQuery
Просмотров 5 тыс.Год назад
STANDARD vs. MATERIALIZED views in SQL | BigQuery
How to work with DATE & EXTRACT function in SQL | BigQuery
Просмотров 2 тыс.Год назад
How to work with DATE & EXTRACT function in SQL | BigQuery

Комментарии

  • @nahidehsan41
    @nahidehsan41 18 часов назад

    i am not finding the data.its not in the descreption.could you please provide the data

    • @pivotalstats
      @pivotalstats 15 часов назад

      Yes the link is in the description. I'm pasting it here for your reference. You will find a download button there.. pivotalstats.com/end-end-power-bi-dashboard-development/

  • @bankimdas9517
    @bankimdas9517 22 часа назад

    Thanks for making this video. Now all my doubts are clear regarding to Row Context and Filter Context. Please make more videos on DAX.

  • @sreejamaddela6548
    @sreejamaddela6548 2 дня назад

    Thank you so much ❤ this is exactly what I'm looking for and I followed all the steps and created dashboard I'm proud to say that i have found excellent power bi dashboard on youtube. Your voice and the way you explained it's so clear and easy to understand for beginners. Thank you for doing these videos. 😍 btw this is my first comment on youtube ever till now . Hope to get response 😁

    • @pivotalstats
      @pivotalstats День назад

      Thank you so much for such a nice comment. Really glad that this helped! :)

  • @bhuvanadevi8133
    @bhuvanadevi8133 2 дня назад

    Thank you so much for this concise video. I made a great dashboard much like yours by following your instructions. Also, I noted that we need to perform more clean up as Age profile is duplicated. Two (0-15)Age_profile exists in the dataset. Could someone also tell me what Time_Band and Total in the dataset mean? It is a little difficult for me to interpret the main ideas if I do not comprehend these two characteristics. Thanks in advance.

    • @pivotalstats
      @pivotalstats День назад

      Glad it helped! Yes you are correct, Age profile also need some cleaning. The data contains Patient Waiting List for a group of hospitals in Ireland. Total is the total number of patients and Time band is the time they have been in the wait list for getting a certain treatment. Hope this helps!

    • @bhuvanadevi8133
      @bhuvanadevi8133 День назад

      @@pivotalstats Thank you

  • @musicals_lovers
    @musicals_lovers 2 дня назад

    Can explain about how to add it on our resume

    • @pivotalstats
      @pivotalstats День назад

      You can create a guthub page and add your project file there. Add the github link at the top of your resume and in the projects section, write about how you prepared the dashboard using advanced visualization techniques. Also mention about the insights you generated on patient wait list. Use chat gpt for generating a apt 2 line statement.

  • @JyotiLifestyle
    @JyotiLifestyle 3 дня назад

    wonderful tutorial, can you please upload second data set.

    • @pivotalstats
      @pivotalstats 18 часов назад

      Hi, glad you like the content. The zip file contains both pizza and student data.

  • @MRMICKY-xy8zm
    @MRMICKY-xy8zm 5 дней назад

    Thank you so much SIR!!!

  • @yacinechaker2687
    @yacinechaker2687 5 дней назад

    Best PowerBI project on youtube. You dive deep into the functionnalities but you manage to explain every step of the way. Thanks a lot

    • @pivotalstats
      @pivotalstats 5 дней назад

      Thanks, glad you liked the content 🙂

  • @Fatimah_safaa27
    @Fatimah_safaa27 6 дней назад

    Thanks a lot

  • @mohammedhussain8520
    @mohammedhussain8520 7 дней назад

    Great video

  • @cwnmaster
    @cwnmaster 7 дней назад

    Remove the background noise.

    • @pivotalstats
      @pivotalstats 7 дней назад

      Sure, I trying to do a better job at editing now. You won't such issues in my latest videos. Thanks for watching!

  • @noueruz-zaman7894
    @noueruz-zaman7894 8 дней назад

    This is the best video and explanation I have seen on power bi. I have using power bi for couple of years but just using it as status quo instead of understanding why it works like that.

    • @pivotalstats
      @pivotalstats 8 дней назад

      Glad you liked the content. Thanks for watching!

  • @lesliewilliams5510
    @lesliewilliams5510 8 дней назад

    i use the 80/20 Pareto Rule too ...

  • @calvinkart
    @calvinkart 10 дней назад

    What about dinamic SQL? It coud be usefull if we can create it in PBi

    • @pivotalstats
      @pivotalstats 10 дней назад

      True, but in a way parameters in pbi is somewhat similar. Although its not that flexible.

  • @ajjbs7580
    @ajjbs7580 10 дней назад

    Sorry, but I must say this: Why didn't you do something with bread? Every time you pizza I want to turn off the video. Honestly, this is one of the better tutorials and I am fighting to get throu. I want to learn this stuff and you structure each topic so great but the pronunciation of the English words is nerv wracking to me. Maybe it is just me....

    • @pivotalstats
      @pivotalstats 10 дней назад

      Thanks for the feedback, I'll try to do it using bread data next time. Cheers :)

  • @BlessedBeni
    @BlessedBeni 11 дней назад

    Hi Sir, instead of using the Date column from either Fact tables, cant we pull the Date column from the DIM_DATES? Wont that yield the right results, and avoid the cross-join? Please clarify.

    • @pivotalstats
      @pivotalstats 11 дней назад

      Hi, yes you are absolutely correct, that will get you the correct results. The reason i used fact table was to show the impact of cross filtering and how to resolve it. I should have mentioned this point in the video. Thanks for highlighting, cheers!

    • @BlessedBeni
      @BlessedBeni 11 дней назад

      @pivotalstats ok, thanks Sir

  • @jjportlouisa
    @jjportlouisa 13 дней назад

    Merci!

    • @pivotalstats
      @pivotalstats 13 дней назад

      Thanks for the support, cheers!

  • @atienograce2520
    @atienograce2520 14 дней назад

    Thank you so much for this project.I am happy to announce that I have learnt a lot with this one project. I did have a little snag though,trying to format the tooltip was a bit cumbersome for me.The one in PowerPoint wasn’t aligning well with the one in power bi.Here is what I did…I selected only the tooltip coverage,pasted to ppt and when returning to powerbi bit doesn’t really align well. I wish you had shown us how you did it briefly but anyway,please let me know on how to solve it.Thank you so much!

    • @pivotalstats
      @pivotalstats 13 дней назад

      Glad the content was helpful. I think I covered tooltip briefly in churn analysis project (link below). I will try to cover this in detail in a future video. ruclips.net/video/QFDslca5AX8/видео.htmlsi=lg9j1v9x8cc3bLvg

  • @saikiranrevankar9899
    @saikiranrevankar9899 15 дней назад

    How did you calculated the average ranking based on ranking year along with this if you can share us the steps performed to extract the URL for each country column

    • @pivotalstats
      @pivotalstats 15 дней назад

      Sorry about that. I should have added the updated data instead of the original file. You can download the updated data from below link: pivotalstats.com/wp-content/uploads/2024/11/Happiness-Data.zip To answer your question, RankAverage is just an Average of all Rank columns. And since wikipedia follows a standard format, below is the formula to get the url ="en.wikipedia.org/wiki/" & B2

  • @shaileshthorat3928
    @shaileshthorat3928 16 дней назад

    Who is the target audience for this dataset ? And what are those all fields about in the data ?... Archive date and all ?

    • @pivotalstats
      @pivotalstats 15 дней назад

      The data contains Patient Waiting List for a group of hospitals in Ireland and target audience is hospital administration who wants to reduce the waiting period for patients. Archive date is just giving us the waiting list status on a particular date. Total is the total number of patients and Time band is the time they have been in the wait list for getting a certain treatment. Hope this helps!

    • @shaileshthorat3928
      @shaileshthorat3928 13 дней назад

      @pivotalstats thanks Buddy, can you frame 5 questions that all this dashboard is answering...

  • @KhaDoanhLuu
    @KhaDoanhLuu 16 дней назад

    I really appreciate your work! This tutorial was super helpful, thank you!

    • @pivotalstats
      @pivotalstats 15 дней назад

      Happy to hear that! Thanks for watching:)

  • @luudiep3412
    @luudiep3412 17 дней назад

    Could you please upload the dataset again ? I cannot it. Thank you very much

    • @pivotalstats
      @pivotalstats 17 дней назад

      Updated, thanks! pivotalstats.com/automate-data-collection-with-folder-connector-power-bi/

  • @JohnFrost-m6p
    @JohnFrost-m6p 18 дней назад

    good learning through this project, from sql to python to powerbi, very rich in learning content!

  • @PRERNAPATTANAIK-b8d
    @PRERNAPATTANAIK-b8d 20 дней назад

    I am not able to access the dataset. The link isn't valid, can you please update it:)

    • @pivotalstats
      @pivotalstats 20 дней назад

      Thanks for letting me know. Just updated it now. Below is the link for your reference pivotalstats.com/end-end-power-bi-dashboard-development/

  • @sayuuuue
    @sayuuuue 21 день назад

    very simplified and helpful, really do not know how to thank you!

  • @VivekRana-kg4ni
    @VivekRana-kg4ni 21 день назад

    Amazing tutorial buddy... but i have a question for you, I am working on a data where I have two date columns 1 is allocated date 2nd is paid date...so while working on power pivot i just want a single filter so that i can just filter a specific date and get a resolved% ...that is paid till that date and allocation till that day...how can i achieve this....can it be possible to have 1 columne filter for both the conditions... I'm stuck...pls if anyone can help, it would be great for me! And the tutorial is really amazing loved ur way of explaining things. Thanks 🙏

    • @pivotalstats
      @pivotalstats 18 дней назад

      Hi, Glad you liked the content! To answer your question, the only way I think you can acheive this is by creating another duplicate data table and then create a dimension date table. This date table will have all possible dates which are there in your Data (no duplicates). Now connect the Dimension table with Allocation Date in your Table1 and Paid Date in your Table2. Finally when you are creating your slicer, use the Date column from the dimension table. This will filter both dates using 1 slicer. Only issue here is that now in your visuals, you need to add both Table1 & Table2. Let me know if this works!

  • @bhavishyabajaj5143
    @bhavishyabajaj5143 22 дня назад

    Just wanna say Thank you...

  • @ahmedadel2487
    @ahmedadel2487 22 дня назад

    NICE VIDEO

  • @charrynsasitube
    @charrynsasitube 23 дня назад

    Thanks for the project, it's very interresting

  • @ynguyen2112
    @ynguyen2112 24 дня назад

    Thanks!

    • @pivotalstats
      @pivotalstats 23 дня назад

      Welcome! Thanks for watching :)

  • @DileepSingh-DS
    @DileepSingh-DS 24 дня назад

    Communication is very nice, Anyone can understand word to word. I saw many videos on your channel, You explained each topic well. 👍

  • @scottdavies329
    @scottdavies329 26 дней назад

    That was very helpful thank you!

  • @vinuthav7567
    @vinuthav7567 26 дней назад

    Thank you !

  • @atulshinde5343
    @atulshinde5343 26 дней назад

    Hi Sir the power bi dashboard is fabulous.....having from scratch scenario in this video...

  • @johndavis1257
    @johndavis1257 27 дней назад

    This is one of the most useful code snippets I have ever found. Thank You So Much!!!

  • @heiaheiaheiahei
    @heiaheiaheiahei 27 дней назад

    this is exactly what I needed, I am glad that finally found your video!!

  • @heiaheiaheiahei
    @heiaheiaheiahei 27 дней назад

    Thanks!

    • @pivotalstats
      @pivotalstats 27 дней назад

      Glad you liked the content. Thanks :)

  • @atienograce2520
    @atienograce2520 27 дней назад

    Just finished this project.I’m in awe of how well you took us through it!I’ve learnt so much and will definitely add it to my resume.I understood everything,you are incredible!! Keep up the good work👏🏽

    • @pivotalstats
      @pivotalstats 27 дней назад

      Wonderful! Sure, will do :)

    • @santhukontheti4950
      @santhukontheti4950 16 дней назад

      I got 77k customers suddenly instead of 6318 ..after completing the steps of churn by services..What can be the reason ?

  • @lavenya1999
    @lavenya1999 29 дней назад

    Hi sir , thank you i just completed this project and i am adding it to my portfolio. You are a great teacher . Looking forward to more videos from you .

  • @anshuvb8051
    @anshuvb8051 29 дней назад

    Thank you for the detailed video. Keep up the good work.

  • @HAMSAOUD1998
    @HAMSAOUD1998 Месяц назад

    Thank you so much for the videos, they have been incredibly helpful. I'm wondering about the potential for freelancing after learning Power BI. Do you think these skills alone are enough to secure freelance projects? If so, what advice would you give for getting started in this field? Thank you in advance for your guidance!

    • @pivotalstats
      @pivotalstats 29 дней назад

      Hi, Really glad that my content is helping. To be honest I have seen many freelance work where they just need a dashboard prepared using a static data source. But if you truly want to outshine in the freelancing world then you should think about combining this with knowledge in cloud technologies (azure & fabric). So that you are capable of designing the data pipeline and distribution structure as well. All the best !

  • @chandranks
    @chandranks Месяц назад

    Very clear explanation

  • @drojanprojectchannel
    @drojanprojectchannel Месяц назад

    ❤ new subscriber brother. Thank you for this free online tutorial. Will watching your other videos in the following days.

  • @floyedmoras1882
    @floyedmoras1882 Месяц назад

    Amazing explanation. The best explanation in You tube. can you please make a complete project on power BI with real time scenarios or atleast based on the interview questions.

    • @pivotalstats
      @pivotalstats Месяц назад

      Glad you liked the content. There are 2 full projects uploaded on the channel. Check them out at below link ruclips.net/video/G8ikAJele_s/видео.htmlsi=p3X06GuH5xnHdxF5 ruclips.net/video/QFDslca5AX8/видео.htmlsi=hHcVF6DB-PBIAvKv

  • @lavenya1999
    @lavenya1999 Месяц назад

    Please add few more tutorials . it was very helpful

    • @pivotalstats
      @pivotalstats Месяц назад

      Sure, meanwhile you can check out the churn analysis project ruclips.net/video/QFDslca5AX8/видео.html

  • @ElMatador-w7q
    @ElMatador-w7q Месяц назад

    Isn't removing duplicates from single column (as we did in mapping) will affect the analysis outcome since their corresponding values in other columns are there in the data?

    • @pivotalstats
      @pivotalstats Месяц назад

      Hi, no that will not impact because we are working on a separate table. When the relationship is created between mapping and main table, it will assign relevant age group to each row.

  • @PallaviSatpute-i6s
    @PallaviSatpute-i6s Месяц назад

    Superb Explanation .

  • @sweetyrai9811
    @sweetyrai9811 Месяц назад

    Thanks man this was a savior...I have a project today and since last two days I watched multiple videos unable to understand sh*tz...but I understood everything that u explained. Excellent stuff for beginners like me.

  • @atienograce2520
    @atienograce2520 Месяц назад

    Masterpiece!Thank you so much for this detailed project.. Quick question ,under relationship's view we have two speciality_name columns under all data table but when we move onto building visuals,I see only one just below specialty HIPE...please let me know on what transformation you undertook...did you merge or discard the other and if so on what basis? Your response will be highly appreciated!

    • @pivotalstats
      @pivotalstats Месяц назад

      Really glad that you like the content! There should only be 1 specialty_name column in the final data. I think you might have skipped a transformation step in the Outpatient data where we are renaming "Specialty" to "Specialty_Name". If you skip this step or make a spelling error, power bi will treat Specialty name column from both Inpatient & Outpatients as 2 different columns. Hope this helps!

    • @BlessedBeni
      @BlessedBeni 16 дней назад

      @@pivotalstats thank you so much!! even i was stuck at this point for an hour... then saw your comment. I had not skipped this step, but the column was renamed w/an extra "i".