I am facing an issue in power bi the columns in power query shows data exactly what it needs to be but when I close and apply the data of certain columns is just BLANK it does not show, moreover the data in lat long columns does not show decimals just whole numbers. Moreover, I have tried to refresh tables several times bu the problem persists. I have ann underlying BIG DATA solution, the data is correct there but dashboards seem to act weird any thoughts?
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I have a question about the function "Analyse in Excel" or "Analyse in Excel" in German when a PBI (Power BI) report has been published.
I read in a flat table in PBI and create some measures in PBI. Basically, it's about account numbers and the limits. A calculation is not necessary or possible here.
If I now want to analyse the data in Excel Pivot Table, I can only display the measures as values. An analysis of account numbers and limits is not possible, as limits are not measures.
What do I have to do to be able to select original data as values?
Thank you very much for your feedback and best regards
Andi
Try adding a measure from the table you are wanting to analyze and then double clicking on the measure value. This will pop open a new sheet and drillthrough to the rows detail behind that cell. It may give you the detail you are wanting. I also believe it will give you proper data types on columns so you can do Excel analysis.
Sorry! I do not get it.
To make it clear - I stripped down a very easy example of my problem:
I'm loading a flat file with account, currency, date and balance information.
The respective Power BI looks like:
After publishing the report into the cloud I would analyse the data within Excel
However, when I try to bring the "balance" information as value in, I'm receiving the following message:
The balance is not a measure in Power BI. Any idea what I can do?
Thank you and best regards
Andi
I'm using Power Query in Power BI to retrieve tables from Dynamics 365 using the Dataverse connector in Import mode. I'm currently having a problem where I have a table that has 23 columns and 6M+ rows, and a lot of the keys are alphanumeric GUIDS (which I intend to replace with numeric keys). So far I have retrieved a base table from D365 (TableBase), which I referenced to another table (Table0) to do some basic transformation like changing text types to integers, replacing nulls with 0, and changing column labels. My next step would be to create 3 smaller fact tables referencing Table0 (Table1, Table2, Table 3) by filtering on a category code for each table.
I have two problems occurring:
When I create a dimension table and left join to the fact table on the GUID, then expand the table to only include the numeric key I created in the dim table, it gives an error saying the file size is too large.
I tried filtering Table1 to return a decreased number of rows (the current table has 6,213,553 rows, I want to get it down to 567,458) it also gives an error saying the file size is too large.
The error message I get is this: Microsoft SQL: Return records size cannot exceed 83886080. Make sure to filter result set to tailor it to your report.
Of course my alternative is to use the OData connector instead of the Dataverse connector for Dynamics 365, but it's dreadfully slow and one simple model I have build with the OData connector is not even refreshing anymore due to the refresh taking so long. Also, I'm confused as to why filtering a table to have fewer rows throws this error, as I'm trying to reduce the file size.
Do you all have any suggestions on why this is happening, and how I can get around it? I know the most obvious answer is that I should remove some columns from the fact table, and I'm going to have a talk with one of my consumers about doing this because that is the only solution I can figure out at this point.
I appreciate any help you can provide!
I have a report in Power BI that cannot refresh because the data from the table is too large:
The amount of data on the gateway client has exceeded the limit for a single table. Please consider reducing the use of highly repetitive strings values through normalized keys, removing unused columns, or upgrading to Power BI Premium
I have tried to shrink the columns used in the data set to the best of my ability, but it is still too large to refresh. I did a test where, instead of using just a single query to retrieve the data, I made two queries that split the columns roughly half and half and then link them back together in Power BI using their ID column. It looked to me that the test data refresh started working upon splitting up the table's data into two separate queries.
Please correct me if there is a better method to trim the data down to allow the data set to refresh, but for now this is the best solution I see. What I am wondering is, since now my data is split into two separate queries, what is the best way to adapt the already existing visualizations I have that are linked up to the full, non-refreshable query to the split, refreshable queries? It looks to me like I would have to recreate the visuals from scratch, but if there is a way to simply do a mass replace of the fields that would save so much time. The split queries I created both have the same fields as the non-split query.
I'm using a calculated column that is an average. The problem is, the average is above the range of possible values, which should be impossible. I made a calculated column that calculates the average star rating (out of a range of 1-5) and the value on a visual is coming up as 6, which shouldn't be possible, even if all the values were 5 stars, which it isn't. So there must be an outlier causing the average to be above the range of possible values, but it isn't in the original data source which Power BI pulls from. The original data source shows me a value of 4.1 as an average, which is within the expected range. But Power BI's dataset has introduced an outlier or (data is missing) that caused the average to become a 6.
I can elaborate on the dax below, but what I want to try to do is pull the dataset down from power bi to figure out why it's calculating its average that way. Looking at the source data, the average is 4.1 and there are no outliers in the source data. So, it's not the source data that's the problem. Basically, I want to find the outlier that's causing the average rating to differ in Power BI.
Avg Rating = IF(SUM(data[Total Reviews]) = 0, BLANK(), SUM(data[Monthly Stars])/SUM(data[Total Reviews]))
Here's a screencap that shows the two
relevant columns
Notice that I had to manually calculate (aka eyeball the columns and type into a calculator then calculate manually) these two columns, which came out to ~4.6. I'm trying to download this dataset to explore it in further detail without having to eyeball the dataset, as the source doesn't show this discrepancy.
To get to the data you have a number of options.
Create a new report in Power BI Desktop, and then use the connect to PBI Dataset option to access that data, in for example, a table. You can create your own report based on the dataset in the service as well.
Access that data via Analyze in Excel, which should allow you to access the data in a pivot table using Excel
Use the Export data from the visual option, using this you can download 30,000 rows into a csv, or 150,000 in to xlsx formats
Please note, that these options may not be available to you if you do not have the right permissions in the workspace, or options have been turned off in the Power BI Admin tenancy settings.
I made some changes to my dataset in Power BI via the Power Query Editor.
I went to close the editor and apply my changes to the data.
I get "Query Errors" that appear, despite having handled the records. I've confirmed the error does not appear in any other columns.
When I go to apply the changes, the errors still appear.
Any suggestions?
Edit #1:
I tried changing the column to a text data type and then sorting to look at all of the values, but it says "Invalid cell value: '#N/A', which is weird. I wonder why it won't let me sort the data.
Seems the only way you can handle these types of values are to handle them outside of Power BI. Power BI cannot handle these values at this time.