Receiving files from business partners that don’t match the agreed requirements/formats causes all sorts of problems in daily business. I found it particularly disturbing during month-end closing when time is really tight: You have a strict rule in which order each process has to run and there are many dependencies between them. So when then one import doesn’t work, many other processes will come to a halt as well. Fortunately, today there is a simple remedy for it: Automatically validate E-mail attachments with Flow and Power BI
Process Automation with Flow and Power BI
You can create a Flow that “listens” for incoming emails in a mailbox that match certain criteria and contain attachments. Flow can then extract these attachments and save them to an online-folder. After that, Flow triggers a refresh of a Power BI dataset, that imports these attachments and checks for the data quality-criteria that you have defined. Then you create measures for the data quality that trigger data driven alerts from Power BI service. Flow then listens for these alerts and sends an email back to the sender, requesting for a corrected file.
This not just saves crucial time, but also your nerves (and those of your team-mates).
As per the time of writing, the native QuickBooks connector in Power BI has some shortcomings for the Time Activity-data: It will not return employee details (so you will not know who did the hours) and it will not return hours (if they haven’t been entered by start- and end-date).
But fortunately the connector has 2 functions, who can return the full data that the QBO-API has to offer. At the end of the list in the navigation pane there are the functions “Entity” and “Report”:
In this blogpost I show you my M-Python-function that I use to export data from Power BI to csv files (Export Python).
I prefer it to R mostly because I don’t have to create the csv-file(names) in advance before I import data to it. This is particularly important for scenarios where I want to append data to an existing file. The key for this task is NOT to use the append-option that Python offers, because M-scripts will be executed multiple times and this would create a total mess in my file. Instead I create a new file with the context to append and use the Import-from-folder method instead to stitch all csvs back together. Therefore I have to dynamically create new filenames for each import. So when the M-Python-scripts are executed repetitively here, the newly created file will just be overwritten – which doesn’t do any harm.
!! This is a clickbait post to get your vote for some missing features in Power BI !!
Although this might not be what the inventors of Power BI had in mind, large lots of folks are trying to create classical financial statements in it. And putting aside the afford that might go into getting the numbers right, there is still a major drawback to swallow:
In this blogpost I’ll show you how to create a list of account numbers from the totalling syntax that you find in Dynamics NAV account schedules or chart of accounts for example:
This string shall be transformed into a “real” list of account numbers in the query editor that can be used to select all accounts within those ranges. Read more
Recently I came across an interesting request where someone wanted to un-cumulate their quarterly YTD-figures (green) into their single quarters values (red) like so (“Unravel cumulative totals”):
Retrieve every Quarters Amount from the Quarter To Date values (“YAmount”)
To retrieve this value, one would have to start with the first value in the year. This is also the value of the first quarter, but for the 2nd quarter, one would have to deduct the value of the first quarter from the cumulative value of the 2nd quarter. So basically retrieving the previous cumulative row and deduct it from the current cumulative row. Do this for every row, unless it’s the start of the year or belongs to a different account code in this example: