All vs Allselected vs Allexcept DAX | Power BI Interview

[@VinodRS01]

Crystal clear ♥️ Thanks man for the wonderful explanation.

[@learnwidgiggs]

Glad it was helpful!

[@softwine91]

Very nice explanation. Thank you very much. So basically, AllExcepts is the opposite of All

[@smileymoviereview2589]

Really superb. Clear explanation with a simple example. Thanks Shashank for sharing this video with us.😊

[@learnwidgiggs]

Glad you liked it.

[@beingrishi6450]

Shashank you should share datasets and pbix file along with your video in description box for practical purposes it will be helpful for us for practices.

[@vishalachary6814]

Nice video ,my doubts are cleared only by your videos .thanks a lot .

[@learnwidgiggs]

Glad to hear that.

[@OleksandraS.-dj3yz]

It's not really clear the difference between the table as an argument in ALL and a column. Also, why ALL(productColor) didn't change the measure but All(product name) did? Isn't it removing ALL the filters regardless of the column?

[@aditjain6580]

Thank you for sharing this Important Interview Question with us Sir. You are looking very nice in Black Shirt.👌

[@learnwidgiggs]

Dhanyawad 🙏

[@chinunayak6494]

What an explanation sir❤❤ ,just wow

[@PrakruthiHarvi]

Hi Bro. Your video's are helped me a lot. I have a question which asked me in an interview. How to cache the data / pre-calculating data to optimize speed ?

[@raahinakeethadath9725]

File-options-setting-global- clear cache

[@b.prabakaran9979]

In Power BI, you can optimize performance and speed by caching data through various methods. Here are some strategies you can use to cache or pre-calculate data in Power BI: DirectQuery vs. Import Mode: Power BI offers two main data storage modes: Import and DirectQuery. Import mode loads data into Power BI's internal data model, allowing for faster performance as data is cached in memory. DirectQuery mode queries data directly from the data source, which can be slower but ensures real-time data access. You can choose the appropriate mode based on your data size, refresh frequency, and performance requirements. Data Refresh Scheduling: Schedule regular data refreshes to ensure that your dataset stays up-to-date while also caching the data for faster access. Power BI allows you to set up automatic refresh schedules for datasets, ensuring that the data is refreshed at specified intervals. Incremental Data Refresh: Implement incremental data refresh to update only the new or changed data since the last refresh. This helps reduce data refresh time and optimizes performance, especially for large datasets. Data Aggregation: Pre-aggregate or summarize data where possible to reduce the volume of data loaded into memory. Aggregating data at a higher level of granularity can improve query performance and reduce memory usage. Optimize DAX Measures: Write efficient DAX measures that minimize the computational load on the data model. Avoid using complex or nested calculations that can slow down query performance. Use Calculated Columns Sparingly: Limit the use of calculated columns, especially if they involve heavy calculations or string manipulations. Calculated columns can increase the size of the data model and impact performance. Partitioning: Partition large tables into smaller segments based on date ranges or other criteria. Partitioning helps improve query performance by allowing Power BI to query only relevant segments of data. Optimize Data Model Relationships: Create optimized relationships between tables in your data model to improve query performance. Use appropriate cardinality and cross-filter direction settings based on your data relationships. Use Aggregations: Set up aggregations to store pre-calculated summary data at different levels of granularity. Aggregations help accelerate query performance, especially for large datasets. Data Compression: Ensure that your data is stored in a compressed format to reduce storage requirements and improve query performance. Power BI automatically compresses data where possible. By implementing these strategies, you can effectively cache data and optimize performance in Power BI, resulting in faster report rendering and improved user experience.

[@Tanha_Akela]

Good Content always 🙂

[@learnwidgiggs]

Thank you 😊

[@ShrutikaUgalmugale]

Many Thanks for all videos!! Good work,keep it up🙏🙂👌

[@learnwidgiggs]

Most welcome 😊

[@rabbabalakrishna6715]

Thank you for making this video based on my request

[@learnwidgiggs]

Welcome😊

[@khushboosharma661]

Hi, I don't know why but I am getting confused alot in all these 3 all filters

[@BasavaKumar]

Very clearly explained. Thanks a lot.

[@udayallada]

Hi there! Is it true that we need to sign in to access all the features provided in power BI?

[@nithyanandbandari]

make videos about data modeling and give the examples also.

[@learnwidgiggs]

Okay..noted

[@monishpilla4137]

I have a question that is, I have a table visual with 5 fields and I have same in the slicer now where ever the client select any two fields it have to give the difference how can we get any idea that u can share

[@learnwidgiggs]

Didn't get your question

[@monishpilla4137]

@@learnwidgiggs I have 5 feilds in my slice if my client select any two of them it have to give the difference of them

[@amitabhverma7897]

can you please share the .pbix file (or the link) ?

[@kanavvasudeva1799]

Bro on wednesday my interview is their plz suggest me the important questions from python and power bi

[@Engineering4675]

@bangalore?

[@kanavvasudeva1799]

@@Engineering4675 hyderabad

[@learnwidgiggs]

From Power BI side, just revise all the videos from this channel...you are good to go.

[@v.kandammalaliassundari3172]

Is it necessary to take pl 300 exam to become data analyst

[@learnwidgiggs]

No

[@krishnakantapanda6835]

Nicely explained 👌

[@learnwidgiggs]

Glad to hear this!

[@Piyushgaikwad7719]

Hello Shashank i want to know the answer of one question which was asked in one of my recent interview, where should i share my question with you ?

[@learnwidgiggs]

You can share on my mail id. (mail id present in the about section of the channel)

[@balavenugopal3269]

Nice explanation

[@TheMiNEChANNeL775]

Live class they provide

[@monishpilla4137]

Thanks for the videos

[@learnwidgiggs]

Welcome 😊

[@gayatri7536]

Helpful information

[@learnwidgiggs]

Glad you found it useful

[@dattupeddagolla928]

Table a Column1 12 15 35 65 Approved Pending 67 98 Pending Approved This is the data how to do sum here?

[@ananyabhattacharyya2362]

First convert the non numeric values to null using conditional statement. Then sum the latest column which is recently made.

[@sandhyah6089]

@@ananyabhattacharyya2362 not working

[@saranyamohanbaba2366]

in modelling create a calculated column ValueType = IF( ISNUMBER(TableName[Values]), "Numeric", "Text" ) then sum the numeric

[@meghalohar2367]

helpful video

[@nitingupta20031]

Hi Shashank, yesterday i make a comment here, however it's deleted. I think you don't want to reply me.

[@learnwidgiggs]

Sorry I didn't see any message of yours. Maybe KZbin would have deleted it on its own if founded it as spam.

[@abhishekvrm2777]

😂

[@abinashkumar1533]

paid promotion na , kitna diya aapko ???????

[@Travelwithus304]

Asked in EY Product Name Category AbcBike Bike Bike123 Bike DEF Accessories LFG Accessories Bike Bike Need to create this in Power Bi category calculated column My solution Category = Switch ( TRUE(), CONTAINSSTRING(‘Table[Product Name],”Bike”),”Bike”, CONTAINSTRING(‘Table[Product name ],”Accessories “),”Acceesories”, “Accessories “ )