PowerPlatform – Page 21 – Nishant Rana's Weblog

How to – Use Advanced lookup in Model-driven Power Apps / Dynamics 365

To enabled Advanced Lookup, log into to Power Platform Admin Center, navigate to

Environment >> [Select Environment] >> Settings >> Behavior

Enable the Lookup behavior and Save.

This adds the Advanced Lookup option in the Lookup dialog.

Clicking on it opens the Advanced Lookup Grid

We can perform SEARCH within a selected View, CHANGE a view, can FILTER it the results further to show only records owned, ADD a new record, SORT the grid.

The best part is we can open/edit an existing record as well as add new ones without losing the existing context.

Opening an existing record from the result opens the record in the new pop-up window as shown below.

Similarly, the Add new option opens the Quick Create form.

In case of special data type like Party List or Regarding, we can select multiple records of different entities we are presented with.

Similar the option to Add new records list all the tables/entities applicable to that lookup.

Thus the new advanced lookup makes working with Lookup much simpler and effective and we should start adapting / using it.

Blog posts on 2021 Release Wave 1 – Dynamics 365

Hope it helps..

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How to setup – Azure Synapse Link – Microsoft Dataverse

Azure Synapse Link (earlier known as Export to Data Lake Service) provides seamless integration of DataVerse with Azure Synapse Analytics, thus making it easy for users to do ad-hoc analysis using the familiar T-SQL with Synapse Studio, build Power BI Reports using Azure Synapse Analytics Connector or use Azure Spark in Azure Synapse for analytics.

Posts on Azure Data Lake

As a first step, we need to create the Azure Synapse Workspace.

https://docs.microsoft.com/en-us/azure/synapse-analytics/get-started-create-workspace

Wait for the deployment to be complete. Below are the resources created as part of the deployment.

Click on Azure Synapse Link and check the Connect to your Azure Synapse Analytics workspace (preview) and specify the storage account created in the previous step

Here we have selected the Contact and System User table for export.

On clicking Save, we got this error couple of times, even though the account being used was Owner across the Azure resources. Trying save 3-4 times more, allowed the link to be created.

Click on Go to Azure Synapse Analytics workspace, opens the Azure Synapse Studio

Within Synapse Studio we can see our Dataverse Database and run query.

Similarly, we create a Power BI report with Azure Synapse Analytics (SQL DW) connector.

Copy the Serverless SQL endpoint of the Synapse workspace.

Select the Direct Query option.

https://azure.microsoft.com/en-gb/blog/power-your-business-applications-data-with-analytical-and-predictive-insights/

Hope it helps..

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How to – improve data migration performance – SSIS & Azure Data Factory (Dataverse / Dynamics 365)

In one of our projects, we were executing SSIS Packages (KingswaySoft’s Dynamics 365 SSIS Integration Toolkit) under Azure-SSIS Integration Runtime in Azure Data Factory.

Check out –

Deploy and run SSIS Package in Azure Data Factory

Deploy and run SSIS Packages that use KingswaySoft’s SSIS Integration Toolkit on Azure Data Factory.

After trying out different combinations, we eventually settled with batch size as 10 and thread as 15.

https://nishantrana.me/2021/06/08/data-migration-optimum-batch-size-and-threads-for-maximum-throughput-microsoft-dataverse-dynamics-365/

Also, we used multiplexing – running the CRM Destination Component under different application users.

To be precise, 4 in our case and we can increase it get further improvement in the throughput.

And also based on the recommendation of our Microsoft’s Fast Track Architect we raised a Microsoft ticket to increase the number of web servers allocated from 2 to 3.

Below were our findings,

the earlier run was using batch size as 100 and thread as 20 with the number of servers as 2.

On updating the batch size to 10 and thread as 15 and with the number of servers allocated increased to 3, there was a huge performance gain.

Check the table below –

The above table is sample run in the sandbox environment, during the final run in production we got the number of servers allocated, increased to 6, gaining further improvement.

Also, check out the below blog post to understand about the affinity cookie and its affect on performance, in case if we doing migration using custom code –

https://markcarrington.dev/2021/05/26/improving-bulk-dataverse-performance-with-enableaffinitycookie/

Hope it helps..

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How to – Enable Notification in Model-Driven App (Dynamics 365)

By making use of appsetting and settingdefinition table, we can enable notifications in the Model-Driven App. (not sure if it is documented somewhere / or supported way) – so try in a trial environment.

I think the supported way is through customization.xml

https://docs.microsoft.com/en-us/powerapps/developer/model-driven-apps/clientapi/reference/events/form-onsave#enable-async-onsave-using-app-setting

Thanks to the below post and tweets by Mehdi EL Amri, which describes the steps to be followed.

https://xrmtricks.com/2021/05/26/a-glance-of-the-onload-event-on-a-model-driven-app-form-async-onload-event/

Basically, we need to add a new record inside appsetting table which will have reference to the settingdefinitionid of that particular setting (Alert notification early access) inside settingdefinition table along with id of the app to which we want it to be associated.

Let us get the settingdefinitionid for Allow notification early access.

App Id for the Sales Hub.

Here we are creating a new record through a console application

parentappmoduleid – appid of the model driven app
settingdefinitionid – id of the specific setting
uniquename – name
value – set as true

Now let us create a flow on the creation of contact which will send the notification. (create the notification record)

On creating the contact record, we can see the notification inside our Sales Hub.

Settings allow us to enable/disable toasts and set the toast duration as shown below

Hope it helps..

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Azure Synapse Link / Export to Data Lake Service – Performance (initial sync)

Recently we configured the Export to Data Lake service for one of our projects.

Just sharing the performance, we got during the initial sync.

Entity	Count
Contact	2,36,2581
Custom entity	1,61,3554

The sync started at 11:47 A.M and was completed around 4:50 P.M. – around 5 hours i.e. 300 minutes

Let us consider total records synced as 3975000 – 1613446 + 2362581 + 2 = 3976029.

So the performance here comes down to

795000 records per hour
13250 records per minutes
220 records per second.

Of course, it will vary depending on the specific environment, table / entity type, attributes in it etc. it gives us a rough idea.

Posts on Azure Data Lake

Hope it helps..

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Advanced configuration settings – Azure Synapse Link / Export to Data Lake service (Dataverse/ Dynamics 365)

The Export to Data Lake service now has some Advanced configuration settings available.

To learn more on Export to Data Lake service

https://nishantrana.me/2020/12/10/posts-on-azure-data-lake/

The new settings allow us to configure how the DataVerse / CRM table data is written to Azure Data Lake.

In-Place update or upsert (default)
Append Only

With the in-place update, the default setting, the file will contain the full data set, and any update in the source will update the same in the synced CSV file or the data partition, similarly, any record deleted will delete the row from the data partition, unlike Append Only where a new row will be added in case of both update and delete.

For huge volume of data, Microsoft recommends opting for Append only mode. This mode is also preferable when an organization wants to incrementally review the changed data.

The other option is to define the data partition strategy.

By Month (default)
By Year

With this option, files generated are partitioned by either year or more granular month-wise, which can be specified per-table basis.

Microsoft recommends Monthly partition if data volume is high.

Now, let us see it in action.

For the Lead table, we haven’t selected the option for advanced configuration settings and are going by default.

Append Only – No
Partition Strategy – Month

For contact, we have enabled the advanced configuration settings and opted for Partition Strategy as Year.

For Account , we have opted for Append Only as true, for which the Partition strategy option is disabled and set as Year.

The final configuration à

Within the container inside the Storage Account, we can see corresponding folders created per table/entity along with model.json as shown below.

Let us explore the Lead folder –

We can see 2 CSV created with format YYYY-MM.csv i.e. having the month part in it because we had specified Partition Strategy as Month i.e. the default value.

For Contact and Account, the Pattern Strategy was Year, so we have files generated in format YYYY.csv

Let us update one of the lead records by appending ‘Updated’ in the last name field.

After the successful sync,

we can see the record updated in the .csv / partition.

The same is the case with the contact record.

Now let us update an account record, it had Append Only specified as Yes.

Here we update the Account Name field from Litware to Litware Updated.

After the sync

We can see a new row appended with the updated record along with the original record.

Let us delete the same account record

As expected, being Append Only mode, we can see a new row added for the Litware record.

We have 2 additional rows apart from the original row, one created for update and the other for delete action.

Export to Data Lake service is Microsoft’s recommended way of synchronizing Dataverse Data with external storage, and we can see them continuously investing and adding enhancements to it.