I have a requirement to produce some PowerBI reports. I have three different SSAS Cubes having most of the measures already available/calculated. So I want to use these cubes as source for PowerBI. But there are few calculations those need measures from different cubes. PowerBI does not allow to create measures with live connection to Cubes. Also due to data volume import is not the feasible solution.
I am looking for a possible solutions for this problem please. Please suggest.
It should be possible now to connect to multiple SSAS sources now using DirectQuery and a composite data model.
I recommend these articles for an overview:
DirectQuery for Power BI datasets and Analysis Services. The composite model with Analysis Services. What is it and why it is a big deal?
Power BI Composite Models using Analysis Services -Direct Query Mode
Related
We are having difficulty finding a method of sharing a dataset and allowing users to use that dataset to create and publish their own reports. This would include ability to create new measures (Dax) and then publish themselves. Using the "service" live connection does not seem to allow that and if not using that there seems to be an issue of refreshing the data once that dataset is downloaded and modified with new columns/measures etc.
Greatly appreciate any help on this. So far I have seen nothing that shows how to do any of this so I have to assume it may not be possible? Thank you.
Live Connect to a Power BI Dataset allows for local measures.
If you need more modeling changes when working with a remote Data Set, the DirectQuery for Power BI Datasets and AAS feature (currently in preview) enables you to mash-up remote Data Set tables, with local tables, and allows for adding calculated columns to remote tables.
But you should use this with some care, as the query processing is split between the local model and the remote model(s), which can cause performance issues.
This is a newbie question. Currently, I connect to an SSAS service from Excel and bring back data from multi-dimensional cubes. Some calculations (using cube data and one or two numbers are hardcoded in the excel) and what-if-analysis are performed and the data is filtered for a specific week of the calendar year (Week 2 - Jan 3, 2022 - Jan 9, 2022) and moved to another tab and that forms the basis of the Power BI report along with the original cube data.
Since this is a weekly report and someone has to open the excel, refresh data from the cube, perform what-if-analysis using goal seeker and then move it to another sheet, etc. before refreshing Power BI. This is the current setup and I want to simplify/automate this and yet not overload the Power BI report that it takes forever to refresh or load.
My question: If there are calculations to be done in between the multidimensional cube data and Power BI, where should it be placed? Should I complicate the Power BI report with all these calculations or move the calculations and logic elsewhere such as for example a Python program that will connect to SSAS (I am somewhat familiar with Python). I was told to consider Databricks to run the Python code by a colleague.
Options:
Perform all calculations in Power BI. Yet to test how well the report can handle this.
Do the calculations elsewhere, for example on Databricks. Don't have Databricks yet. I can start with local Jupyter notebooks. I am concerned if I will run out of memory.
What is the best/industry practice in such scenarios? There are concerns about complicating the presentation layer in Power BI and impacting user experience with heavy Powe BI reports.
In general, you want all logic in the cube and use Power BI for reporting. If you can't put the logic in the cube, I would prefer to do it in Power BI to eliminate other points of failure, manual steps, or timing issues.
I am new to Power BI and trying to build a report for one of our business requirements. I have access to a Power BI dataset which I imported in the Power BI desktop version. I also need to import an excel file placed in SharePoint/OneDrive and merge the data in these two sources. When I am trying to do this, I am getting the below error.
Is this feature not available in Power BI?
If not, is there a way to achieve this objective?
You are connected to a Tabular SSAS cube or Power BI Service dataset, you can't add other data sources.
You can only mix data source types in the modes direct query and import. See the limitations section of the MS docs
One option would be to recreate the Tabular data model in Power BI, over the base table/views it is based on in direct query mode, then add the SharePoint list, or add it as a table in the Tabular/Power BI Service Dataset
I'm new to Data visualization and currently I'm migrating couple of dashboards from tableau to powerBi.
Both tableau and powerBi imports data from sql server.
Which is the best way to create an efficient data model in powerBi while taking into consideration of views from tableau?
The best way to create a data model in Power BI is to create a Star Schema. If you are not familiar with a Star Schema do some research on the web. It will be something that it is well worth your while to learn.
You may end up having to use Power Query to deal with tables from both sources that hold similar data.
I have a collection of .pbix models that follow a similar structure, ie, have the same tables and relationships.
It is too complex to combine them all into a single .pbix.
Is there a way to upload all these tables into a single repository, like PBI Service dataflows or a data warehouse, or something similar.
And then get the data back to PBI Desktop and perform DAX calculations, visualizations and report.
Any suggestions/ ideas?
Thank you so much for helping!
You can publish them to Power BI Service, and then create separate reports, but using these published datasets as a data source.
See Connect to datasets in the Power BI service from Power BI Desktop.
After publishing your "model" reports to Power BI Online, start making a new blank report, but instead of getting the data from files/databases/etc., choose Power BI service as a data source and select the previously published dataset. After that, you can publish your report the same way, but in this case you can share one dataset (your model) between multiple reports.