After setting up my ETL, now I'm preparing the reporting phase. I want to know the diffrence between Import and Connect live a SQL Server analysis Services database methods knowing that I'll be working with measures.
In my example : I need to create a measure which count the emails with failed status by department.
I have (after importing the cube) :
Fact Mailing Count
Mail Status Dimension
Message Template Dimension (having the application name which is the
same name of the department)
Live connect: This will connect power bi to analysis services data model directly.so you will be building your model completely on analysis services project and deploying it frequently. So the power bi will have a live connection to the model and make updates when necessary. when new data processed or new measures or tables created. Here the limitation is you cannot combine multiple sources of data and you have to rely on the SASS Model you have already connected with.
Import: This will import tables to the Power bi and you will be allowed to create and manipulate your facts and dimensions as per your wish inside the power bi(in live connect mode you have to do it in analysis services model itself).
The main obstacle of import mode is When you import large tables will a large number of data, power bi has limitations(1GB) on that.
Creating measures and calculated tables are allowed in both modes.the difference is on which side you create them.
A detailed comparison of both Live connect and Import
https://community.powerbi.com/t5/Community-Blog/Power-BI-Live-connection-vs-Import-comparison-and-limitations/ba-p/84377
Related
I am trying to create PowerBI Datamart from Azure Analyis service. There is a datamodel available in the Azure Analysis Service and I can connect using URL and Database Name. The datamodel has ~100 tables present in it and relationship also setup. So my question is, if I want to create a PowerBI datamart from the Azure Analyis service datamode, I need to do the Get Data option of PowerBI datamart and connect to Azure Analyis service, select table, select fields 100 time for getting all the tables of Azure Analyis service datamode into my PowerBI datamart? Is there any import function available where I can import all the tables in a single time?
Why do you want to copy data from AAS into a database?
The reason you find it difficult is that it's an odd thing to do. The query designer for AAS/SSAS generates MDX queries which are indented to run aggregate queries that return a handful of rows, and are wholly unsuitable for extracting whole tables. If you try, the queries will just run forever and fail.
It's possible to extract data from AAS/SSAS tabular models, but you must use DAX not MDX, and so you need to the Power Query or "Transform Data" window, and use the advanced editor.
Each query to load a table should look like this, eg to load the 'Customer' table:
let
Dax = "evaluate Customer",
Source = AnalysisServices.Database("asazure://southcentralus.asazure.windows.net/myserver", "mydatabase", [Query=Dax])
in
Source
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.
I am working on a PowerBi project and I need some advice/questions on the best way to approach this project. I am tasked to create a dashboard for employee metrics pulled from an onsite SQL Server database. The managers here are going to have access to the PowerBi cloud, so I will end up uploading this to the cloud. There are 10 or so metrics that need to be shown on the dashboard. We have 5000+ employees. My first thought was to create a table and dump all the metrics into a table and set the PowerBi report to import the data, but that seems excessive and a waste of space to upload all that data to the CLOUD because all of the managers don't need access to every employee. They may want to see 1 or 2 employees' metrics on the dashboard.
My second thought is to (and if this is possible) create a stored procedure that will take the employee id and output a dataset for PowerBi to create a visual for. On the dashboard, have a list of employees and when a manager selects one, PowerBi will call the stored procedure with the employee id and the dataset will be returned for PowerBi to decipher into a visual based on my measurements. I guess I would set the PowerBi report connection type as DIRECT QUERY?
Here are my questions:
Is this possible? Is it possible to what I am thinking for my second plan? Is this how DIRECT QUERY works?
If so, how does DIRECT QUERY work with the PowerBi cloud?
What is setup like? Do I just install the PowerBi Data Gateway/configure it like IMPORT DATA and PowerBi does the rest?
A couple of queries:
What is the frequency of data update ?
In case if it is a batch job, it is ideally preferable to import that data from source into powerbi model and do reporting on the imported data as
a) The performance would be quicker
b) There would be no to and for of data across on prem database and cloud
c) the source would not be impacted constantly
So is the ask to have RLS wherein the managers should see only the employees under them?
Then it is pretty easy to implement RLS in imported version rather than in case of direct query.
Also you won't be able to pass parameters to stored procedures, and you can't execute them in direct query mode. You can however, create table valued functions which give you the ability to use table variables and perform other functions that are more complex in nature in Direct Query mode
you can refer this for additional details :
https://community.powerbi.com/t5/Desktop/Can-i-call-Stored-Procedure-with-Direct-Query/m-p/267141#:~:text=%40Pallavi%20you%20won't%20be,nature%20in%20Direct%20Query%20mode.
This is what I am trying to do: I have various SQL server databases with data. I created views in all of them. All views will need to be imported, and I specify their relationships. I want this to be refreshed nightly. I want to build various reports of the same data source.
Do I have to use a PowerBI desktop application to import data into PowerBI Report Service? [I have done this so far, but then can create new reports in the cloud on existing data. It would make sense to connect directly from PowerBI report service to my SQL servers.]
Once I uploaded data using a desktop application (as I have done so far), how can I view the data model in the report service once it is uploaded in the cloud?
In order to get routinely refreshed data I need to setup a gateway. Is the local PowerBI desktop application still involved in this process, or could I [in theory] delete the local desktop application that pushed the data in initially?
For your questions:
You have two options, use PBI Desktop to connect to the data using import/direct query, then load it to the service. You can use dataflows to create an import based on your views, but you will then need to create reports from those. Using dataflows, you'll have to set up a refresh schedule, then for the dataset(s) built on top of those, you'll have to set another refresh schedule.
You will be limited to the dataset sizes of 1GB for the workspace if importing data. You cannot use direct query on dataflows (unless you have enhanced compute with PBI premium). Once the dataset is loaded, you can then create new reports in the service or via desktop on top of that dataset. If possible it is recommended to use direct query.
To see the data model, you can use desktop to connect to PBI Service Dataset. This will connect in 'Live Connection' mode, and will be limited to that one dataset, you can't add others to it, Excel, CSV, SQL etc. You can also use Analyse in Excel, a plugin for Excel, that can connect to the data model. You can create new reports in the service for existing data models as well.
When creating the report in PBI Desktop it does not use the Gateway, you connect to your data sources as normal, then once you load the dataset to Power BI it will match the data sources in the file to the ones set up in the Gateway Admin settings. So you will still need PBI Desktop to create reports, but the gateway is there for the refreshing. The Desktop is not used in the process for refreshing. You could delete the workbook or application, but if you have to make changes, what will you refer to? (You could download a copy of the report from the service).+ It is easier to make changes in the desktop app, then the service, as there is a feature difference between dataset creation in the desktop vs service.
So, currently I'm having difficulty understanding how Power BI Embedded can be setup so that each customer can access data from their own separate Azure Analysis Service, this is an App Owns Data situation. Analysis Services will be running in In-Memory mode and it will be accessed from Power BI via Live Connect.
Ideally I would like the Power BI Report to be ignorant of the data set/data source until the embedded report is provided with a parameter (e.g. connection string) which the report interprets so that it knows which server to connect to. So, ideally have: one Workspace, one Report, and zero (or a fake) Dataset.
The following is roughly what I'm looking to do (note the Red and Blue flow access a different server):
It looks like if I created both a Report and Dataset per customer I can achieve my goal but this seems like a poor approach since if the Report needs to be updated this involves updating, potentially, hundreds of reports. Also creating hundreds of Reports seems like unnecessary overhead when all Power BI needs to change for each request is the connection string pointing to the data source.
So is it possible to share the Workspace and Report across all customers but having completely separate data sources? Or is my approach in conflict with the way Power BI expects to function?
To date, I've tried using Query Parameters when configuring the data source in Power BI Desktop but I get the following error:
The connect live option for this file is disabled because it already contains data from another data source. You cannot explore live data and connect to another type of data source in the same file.
Please note,
Every report in Power BI can be connected to only one Dataset.
There is NO ability to dynamically change a connection string on the fly.
Currently, and in the foreseeable future, you'd have to clone the report & dataset per customer (or per connection setup) and modify the new dataset's connection string to match.
You can then dynamically choose which report to display based on your customer's needs.
Cloning a report can be done using:
POST https://api.powerbi.com/v1.0/myorg/reports/{report_id}/Clone
POST https://api.powerbi.com/v1.0/myorg/groups/{group_id}/reports/{report_id}/Clone
https://msdn.microsoft.com/en-us/library/mt784674.aspx
Changing the connection string would be done using:
POST https://api.powerbi.com/v1.0/myorg/datasets/{dataset_id}/Default.SetAllConnections
(similar API for groups)
https://msdn.microsoft.com/en-us/library/mt748181.aspx
using the C#.NET library provided by Power BI team, you'd use
Reports.CloneReport(string reportKey, CloneReportRequest requestParameters)
Datasets.SetAllDatasetConnections(string datasetKey, ConnectionDetails parameters)