Need help with Dax Measure
Hi, I have facing performance issue with a measure in my power bi report where I have creating the below measure Transaction Count = COUNTROWS ( FILTER ( SUMMARIZE ( 'Compiled Sales', 'Compiled Sales'[Store Code], 'Compiled Sales'[BillNo], "Total", SUM ( 'Compiled Sales'[Sold Quantity] ) ), [Total] > 0 ) ) can this measure be created in another way currently this dax is taking 20 sec and my main fact table has 20 million records. please let me know if any other information is requried.
Return SUM for newest value by unique ID
Hi all, I'm pretty new to PowerBi but I have got good familarity. I want to return a SUM value (so I can put in a card visual) of a SUM of values only by unique IDs and their latest date of values. This means I can put a date slider which filters the latest SUM values (by unique IDs) in a date range. Example data: ID Amount DateTime 1 10 01/01/2023 1 5 02/05/2023 1 2 01/08/2023 2 15 01/01/2023 2 10 02/05/2023 2 5 01/08/2023 I want to then add a filter slider and if I select January and it only shows the SUM value of 25. But if I change the slider for May it will show me the SUM value of 15. If I set the date slider for the whole of 2023 I want it to only show the latest data which is a SUM of 7. I can create DAX to SUM latest values only but if I change the slider to January there is no data. So I need to be able to create a SUM based on unique IDs only and their latest date based on a filter slider. Many thanks, Liam
Previous datetime for streaming dataset
Hi, I have streaming dataset. Requirement is to show live data. To perfrom some calculations I connect this dataset to powerbi Desktop and adding measures as per need. Now I am trying to create a measure which will give me perivous value of datetime. I want time diffrence of two entity. Please check below image. In this case I want new column with perivous datetime. I want to calculate time diffrence of non Blank ESN value to next stopper_down_time_Stamp. I tried one measure- CALCULATE(index(-2,ALLSELECTED('live-table'[HosurDateTime]),ORDERBY('live-table'[HosurDateTime],ASC)),KEEPFILTERS('live-table')) But this is giving me only one value for latest record. not complete column values. Please help me out. Thanks.
Calculate a date sequence on a row level per ID (in DAX)
Hi there, I have this data set where each patient goes through different treatments (each row is a new treatment). I would like to add a new column (using DAX) that creates a sequence of numbers from 1 to "N" for each Patient, being 1 assigned to the earliest date. This is what the new column should look like: Patient Created on (d/mm/yyyy) Treatment number (calculated column) Patient A 16/08/2023 3 Patient A 5/05/2023 2 Patient A 25/03/2023 1 Patient B 13/08/2023 2 Patient B 5/05/2023 1 Patient C 19/06/2023 1 Patient D 8/09/2023 2 Patient D 14/07/2023 1 Thanks!
Need help improving DAX calculations for accurate results in Power BI from single date column!
Hello Power BI community! I'm seeking your expertise to help me improve two DAX calculations that I'm currently using to calculate the receiving and sending (handling) dates for a ticket table. The data I'm dealing with is related to a list of tickets that are received and then treated by technicians on different dates, unfortunately, I'm only provided with one date column which aggregates all actions performed on a specific ticket (which is DateTime), and a ticket may appear repetitively but with different receiving and sending dates (which should be taken into account of course). Here's a snapshot from the raw data table: Feel free to download these tables from here: "https://smallpdf.com/file#s=c745e973-29a0-4dbd-85ab-2472d7379858" Below are the DAX calculations I'm using to produce the results (which are now inaccurate) ReceiverDate = CALCULATE( MIN(WEEKLY_IDs[DateTime]), FILTER( ALL('WEEKLY_IDs'), 'WEEKLY_IDs'[SenderID] = EARLIER('WEEKLY_IDs'[ReceiverID]) && 'WEEKLY_IDs'[ReceiverID] = EARLIER('WEEKLY_IDs'[SenderID]) && 'WEEKLY_IDs'[Ticket_ID] = EARLIER('WEEKLY_IDs'[Ticket_ID]) ) ) SenderDate = CALCULATE( MAX([DateTime]), FILTER( ALL('WEEKLY_IDs'), 'WEEKLY_IDs'[SenderID] = EARLIER('WEEKLY_IDs'[SenderID]) && 'WEEKLY_IDs'[ReceiverID] = EARLIER('WEEKLY_IDs'[ReceiverID]) && 'WEEKLY_IDs'[Ticket_ID] = EARLIER('WEEKLY_IDs'[Ticket_ID]) ) ) These are the end results I'm seeking to accomplish with these two DAX calculations:Calculate the total average days
Hello community! I am stumped. So I am trying to do a "conversion" rate based on a start date from one table and a start date from another table. These two tables do not have a direct relationship, however, they are both connected to a main table through an ID. The main table includes the slicer # and the main table ID #. I am using a DAX where I pull the minimum date value based on the start date of each table, then I am using a datediff between those two minimum values. What I need is for the sum of those conversion days for all of the main table #s and then I will divide that number by the count of main table IDs. Here's an example. Instead of it showing -254 I need it to total eveything in that table in order for me to divide it by the count. Hopefully this wasn't too confusing, Thanks!
