Azure Logic App – Copying a file from Sharepoint to a Data Lake

I have been asked to set up a Logic app in Azure (That is Power Automate for anyone outside Azure) to copy specific file(s) from a Sharepoint folder and add to an Azure Data Lake.

The first example file is around 16,00 rows and not likely to grow too significantly. This is the same with the other files.

There is a specific use case behind this First logic app:

  • The Data in the csv file(s) is updated every day so the file name remains the same
  • We need to copy the File and overwrite the file in the data lake every day after the task has been done to update the Sharepoint File (Around 5PM every day)
  • we want the Logic App to run via Data Factory
  • Once the logic app has run we want to trigger the pipeline to populate the SQL database from the file in the data lake.

Set up the Logic App

In azure go to Logic App and New

Log Analytics: to get richer debugging information about your logic apps during runtime

Consumption Plan: Easiest to get started and fully managed (Pay as you go model). Workflows increase slowly or are fairly static

Standard Plan: Newer than the consumption plan. Works on a single tenant. Works on a flat monthly fee which gives you potential cost savings.

Create the Logic App

Once you have added tags and created its time to create the logic App

Because we want to trigger in Azure Data Factory we want to go for When a HTTP request is triggered

The HTTP Post URL will be used in Data Factory to trigger the Logic App.

I have added a JSON Schema that supports some of the important information for this project. Like Container for the data lake, Folder , File name and isFolder (Which becomes more important a little later.

     "properties": {       
        "Container": {            
           "type": "string"        
        "fileName": {            
           "type": "string"        
       "folder": {           
            "type": "string"        
       "isFolder": {            
           "type": "boolean"        
"type": "object"

List Folder

Now we want to List Sharepoint folder. So create a new step and search for List Folder

Returns files contained in a Sharepoint Folder.

Next you have to Sign into Sharepoint with a valid account that has access to the Sharepoint site.

Here is where we have a question. For this test, my own username and password has been used but obviously I change my password at certain points which means that this will need manually updating when this happens.

What we need is a way of logging into Sharepoint that isn’t user related and we can use within the logic app. This needs further thought and investigation.

When you log in you create a Sharepoint API connection in Azure Resource Group

To get the site address you can go into Sharepoint, Click on the … against the file and copy link.

The link needed amending slightly because it needs to be

If you have access you should then be able to click the folder against File Identifier and select the correct area

For Each

Next Stop, For each ‘Body’ from the List Folder step. We get the File Content. Go to Next Step and choose the For Each Condition (Because there will be multiple files)

Get File Content

Now We want to Get File Content From Sharepoint

Gets File contents using the File Identifier. The contents can be copied somewhere else or used as an attachment

You need to access the same Sharepoint site address as before. Then click on File identifier and choose ID from the Sharepoint Dynamic Content pop up

so here we can see that from the list folder step we have lots of file metadata we can use like DisplayName. ID, LastModified etc.

We know we need ID for Get File Content

We are at a point where we can run this now as a test.

Note that so far we have this set up

but we hit specific issues

Status 404 File not found

cannot write more bytes to the buffer than the configured maximum buffer size of 10457600

So we have two issues to resolve and after a bit of help on the Q&A Forums we find out that:

List Files “Returns files contained in a Sharepoint Folder. ” Actually also returns folders which are erroring because they are not files

Logic Apps aren’t really set up for large files. There doesn’t appear any way we can get past the size issue. So we need to check our files and also think of ways to bring through smaller data sets if needs be.

Thankfully our files are way below the threshold and the business thinks that they won’t increase too much.

So here is where we can start applying criteria, which we want to do anyway because we only want certain files.

  1. If its a folder we don’t want to use it
  2. If its over 10457600 in size we don’t want to use it
  3. Only bring through files called…….

So we need to change our For Each

Within For each add a new step and search for Condition

And add your conditions (And Or)

Then you can move the Get File content into True

So If IsFolder is false and the size is less than 10457600 we can grab file A OR File B.

When you now test this Logic App Get File content should succeed with most not even hitting the criteria.

Create Blob

Finally within the True section we need to add the file to our Data Lake.

Search for Create Blob

Here you have to sign into your Blob Storage which again creates another API Connection in Azure

You have to supply the Storage account name and choose an authentication type. Access Key has been used, the details added here. Normally in data Factory the Access Key is obtained through a Key Vault so, more information is needed to come up with the most secure way of doing this. There are two other authentication types to choose from.

More investigation is needed into these other approaches.

Now we can do a full test of the Logic App

Testing the Logic App

When you trigger the logic app

The Body contains a long list of every object. Really handy to know what the details are inside this action.

To test this was copied into a word document.

Next comes the Get File Content

Now most of the files don’t satisfy the condition.

Next was clicked to get to a file in Get File Content (first one appeared as number 32)

And now we can see the Body of the Create Blob. (This happens for every file specified in the criteria

And if you use Microsoft Storage Explorer app you can check that they have indeed been updated (Either its a new file or it updates what is already there)

Data Factory

Now we have saved the Logic App we want to trigger it in Data Factory

Create a pipeline and choose a web activity

Copy the URL from the Logic App and paste here

For the Body I simply used the Simply JSON at the start of this article.

Now you can trigger this pipeline along with all your other pipelines to run the Data into your Data Lake and then into SQL to be used for Analytics.

Data Factory to move daily snapshot data in Azure SQL DB to files in a Gen2 Data Lake

I have the following problem to resolve (And this was my initial attempt at figuring out a solution)

I have a data source with data that contains a date. the data contains daily snapshot of a record. this means that a record will be in the data set once per day. This will amount to a lot of data and we would rather hold it as files in Azure Data Lake Gen2 Storage

The logic is to pull daily files from the source database into dated files within the Azure data Lake

Once running this will probably pick up a days data because the rest are already created. However on the initial run I want it to pick up all the days that have been loading.

At the minute I have about 6 months of data to load

Tables in Azure SQL Database (destination)

CREATE TABLE [audit].[MemberDailyMetricsDates](
     [DATEUTC] datetime2 NULL

This table collects all the dates from the source snapshot table

Remember, the table records the same record every day with any changes to the record.

CREATE TABLE [audit].[IdWatermarks](
     [TableName] nvarchar NOT NULL,
     [WatermarkValue] [bigint] NOT NULL,
     [WatermarkDate] [datetime] NULL,
     [WatermarkDate2] datetime2 NULL

this is where I add the dates from the tables to show where we are.

For example if we add the last lot of data from 02/01/2020 then this value will be stored in the watermark table. I record them in different formats just in case.

CREATE TABLE [audit].[ProcessingMetrics](
     [ID] [int] IDENTITY(1,1) NOT NULL,
     [TableName] varchar NULL,
     [DateProcessed] [datetime] NULL,
     [DateUTC] datetime2 NOT NULL,
     [Duration] [int] NOT NULL,
     [NoRows] [int] NULL,
     [ID] ASC
 ALTER TABLE [audit].[ProcessingMetrics] ADD  DEFAULT (getdate()) FOR [DateProcessed]

We can record meta data from the data factory Pipeline as it runs

Stored Procedures in SQL Database (destination)

/*Debbie Edwards
 17/12/2019 Created initial SP
 Create a watermark table
 EXEC [audit].[audit].[USP_Watermark]    '2014-12-31 00:00:00.000'

 ALTER PROCEDURE [audit].[USP_Watermark] @NullDate datetime2



 IF EXISTS (Select * FROM [audit].[IdWatermarks]  
 WHERE TableName = 'DailyMetrics')

 DELETE FROM [audit].[IdWatermarks]  
 WHERE TableName = 'DailyMetrics';

 --DECLARE @NullDate datetime2 SET @NullDate = '2014-12-31 00:00:00.000'

 WITH CTEDailyMetricsDates (DATEUTC)
 (SELECT ISNULL(MAX(DATEUTC),@NullDate) FROM [audit].[DailyMetricsDates]) 

 INSERT INTO [audit].[IdWatermarks] 
 (TableName, WatermarkValue, WatermarkDate, WatermarkDate2)
 FROM CTEDailyMetricsDates

This is the Stored procedure that you run to create the watermark

Currently I’m just running this for one table. You could redesign to run this SP for different tables.

Also note, If there is nothing in the table I am setting a default date to work from @NullDate

/*Debbie Edwards
 18/12/2019 Created initial SP
 Update Processing details
 EXEC [audit].[USP_UpdateMetrics]
 ALTER PROCEDURE [audit].[USP_UpdateMetrics] @TableName varchar(100),   @DateUTC datetime2, 
 @Duration int,  @NoRows int



 INSERT INTO [audit].[ProcessingMetrics]
 (TableName, DateUTC, Duration, NoRows)

 (@TableName, @DateUTC, @Duration, @NoRows)


the Pipeline will run this stored Procedure to add meta data to the ProcessingMetrics table

Data Lake Gen2 Storage Account

Along with the Destination SQL Database you need to have an Azure Data Lake

Quick Set up for the Azure Data Lake. Setting up an Azure Data Lake V2 to use with power BI dataflows in Service (As a data source) …. and Setting up a service principal will give you information on how to:

  • Set up the Storage Account
  • Ensure Hierarchical name space is enabled
  • Create a file system
  • Grant reader Role to power BI service
  • Set up the Service Principal (Set up the App Registration)

Set up Data Factory

Now we are ready to set up everything with a Data Factory

create your data Factory and then go to author and monitor


AzureSQLDatabasereportingdb is the Source Azure SQL Database

Our Destination is a Destination Azure SQL Database AzureSQLDatabase[destination]reportingdb

And we have a gen 2 Data Lake Storage Account AzureDataLakeStorageGen2 (Which will need the Service Principal account setting up in order to use) See setting up a service principal….


the Linked Services are in place. Now we can add Data sets

Source Data Set – Azure SQL database

Add an Azure SQL Server Dataset. the first thing we need are two parameters for the TableName and Table Schema

Connect this up to the Source Linked Service and use the parameters to create a table with schema

The Schema will change when ever you use different table parameters so no need to set at this point

Destination Data Set – Azure SQL database

Destination Data Set – Azure data Lake Gen2

First of all, create a FileName parameter. Because we are creating multiple files, each file needs to be renamed to the UTCDate from the Foreach loop later. We need to set this up within the For each rather than here. Therefore will just set the name as a parameter at this point.

What we want to do is add the file into our file system created in the data lake. and we want to add a date to every single file because these will be the snapshots

In add dynamic content


This is where the actual information for Filename from the data set will be added within the copy activity later.

I imported a schema from a test file I already created.

Pipeline 1 Create Member Daily Metric Dates into destination database

Our first part of the process is to create a list of dates in the source data that we dont yet have in the Data Lake. The first time we run it, thats literally every date we have so far in the source data base

Lets have a look at the Activities in the Pipeline


I know that my dates are in datetime2 format so I’m using this and changing it to WatermarkValue so all the steps always use WatermarkValue no matter what the format. Here is the query in full

SELECT MAX(WatermarkDate2) AS WatermarkValue From [audit].[IdWatermarks]
WHERE WatermarkDate2 IS NOT NULL
AND TableName = 'DailyMetrics'

We record the table name of the source in the Watermark table. Basically this will tell us what the date we need to use to work from. remember, we set up a default if there is nothing in the dataset to work with which will run everything into the data lake


This is where we get to the Copy part of the activity. We are simply copying the dates into the table of the snapshots that we haven’t done yet.

Here we add the parameters of the table we want to use from Source. These parameters were set up in the data set section.

Add a Query. We want the Distinct Date from the source table Where the DATEUTC (The column in the table) is greater than WatermarkValue from the Previous Watermark Activity

SELECT DISTINCT DateUTC FROM [dbo].[DailyMetrics]
WHERE DateUTC > ‘@{activity(‘LookupWatermarkOld’).output.firstRow.WaterMarkValue}’

Now we are at the destination data set

The only item in here is DateUTC


This will trigger the Watermark Stored procedure and uses the Azure SQL database destination Linked Service

This is everything required for Section 1 that will run all the dates into our table based on snapshots we haven’t yet prepared

Pipeline 2 CopyMemberDailyMetricsDateUTC

Again, lets have a look at these Activities in more detail


this is the Lookup Activity that takes the full record set of Dates from the destination SQL Server

Note that we haven’t ticked First row only because the entire data set is required

CopyDailyFilesIntoDL (ForEach Activity)

We are taking the output.value from our activity LookupDates

Because it only has one column we don’t need to specify anything further. output.value means the entire record set

Sequential – The Items will be read one by one from the data set

there are 2 activities within this foreach loop. Doubly click on the activity to see what is happening in the loop

Again Lets have a look at this in more detail


The source is the table in the source database because we want to store everything in daily snapshot files.

The Query is a SELECT FROM WHERE Statement. Select all the columns from the DailyMetric table where the DateUTC in the source data is Equal to DateUTC in @Item which is generated by the ForEach activity 

the sink uses the Data Lake. Remember, in the data set we set the Filename parameter and here is where is gets set. Click on the Filename to view Dynamic content

This is Concatenating a file name, the Item UTC Date and .csv

Use @item() to iterate over a single enumeration in ForEach activity . This value is generated by the ForEach activity (In the Pipeline)

We are setting the date as a string in order to use within the file name. Because the For each loop is setting the item for us and we are inside this activity we can create the filename in this copy activity rather than in the data set its self.

We can then simply Import schemas to view the mappings between the source and sink


Finally, we want to keep a record of everything we are going to be doing in the loop so we can run our stored Procedure to add the meta data into a table in our source database

We can use out SQL destination Linked Service for this

the Stored procedure contains 4 parameters.

We can take the Date from the Item in the foreach loop.

Duration, and NoRows can be added from metadata. See Monitor programmatically

  • Duration @activity(‘CopyDailyMetrics’).output.copyDuration
  • No Rows @activity(‘CopyDailyMetrics’).output.rowsRead

the table name is simple DailyMetrics


Finally, now that everything is complete we can truncate the date table. Outside of the foreachloop

the max date is held in Watermark which will be used to create the new files Next time (Set in Pipeline 1)

Test your solution

Now we have everything in place we can test each pipeline. By Clicking debug

You can see the files coming in via Azure Table Storage

If you get errors, a great way of debugging is to go into the code. I had an error and after a file nam it had /n/n.

I simply removed this empty row and it worked.

Pipeline 3

There is now a Pipeline 1 to create the dates. And pipeline 2 to create the files. This is good because they can be tested separately.

We need a top level Pipeline to run them

And this is the new model for the flow of this Data factory

Add a trigger

now we have successfully tested the Pipelines we can set them up in a trigger by adding a parent pipeline that runs all the Pipelines in order

Another Post will be created on Adding Triggers


You need to make sure that the last file (When you run it is complete) In our case the snapshot table is run at 12 AM and takes around 20 minutes so we need to set this pipeline off at 1 AM

Add Alerts to Monitor the Pipeline

Another Post will be created on Adding Monitors

Setting up a Service Principal for Azure Data Lake Gen 2 (Storage) to use with Data Factory

An Azure service principal is a security identity used by user-created apps, services, and automation tools to access specific Azure resources. Think of it as a ‘user identity’ (login and password or certificate) with a specific role, and tightly controlled permissions to access your resources

Azure Service Principal

I am constantly having to remind myself how to set up the Service Principal for Access to things like Azure Data Lake Gen 2 when I am setting up a data factory (Or using the storage with another web app).

So I wanted to write a blog post specifically on this.

As the example, imagine you are moving data from an Azure SQL Database to files in Azure Data Lake Gen 2 using Azure Data Factory.

You attempt to add a Data Lake Connection but you need a Service Principal account to get everything Authorised.

You need this so the Data Factory will be authorised to read and add data into your data lake

An application (E.g. data Factory) must be able to participate in a flow that requires authentication. It needs to establish Secure credentials. The default method for this is a client ID and a Secret Key.

There are two types of permissions

Application Permissions No user context is required. The App (E.g. data Factory) needs to access the Web API By its self

Delegated Permissions The Client Application (E.g. data Factory) needs to access the Web API as a Signed in User.

Create an App

In Azure choose App Registrations

Here you can create an app – New Registration

Provide a name for your app. e.g. DataFactoryDataLakeApp

Grant your Registered App permissions to Azure Storage

This will enable your app to authorise Requests to the Storage Account With Azure Active Directory (AD)

You can get to your app by going to Azure Active Directory

Then App Registrations and choose the App

In your new App, go to Overview and View API Permissions

Next go to Add a permission

Go to Azure Storage API which contains Data Lake Gen 2

Notice that we are setting up Delegated Permissions for Azure Storage

You are warned that Permissions have been changed and you need to wait a few minutes to grant admin consent.

I am not an admin so I always get my admin to go into Azure Active Directory and Grant Admin Consent for Peak Indicators

Note that your app now has configured permissions for Azure Active Directory Graph and Azure Storage

Assign your new app to a subscription

Now you have an app you need to assign Contributor status to it to the level of service you require in Azure, Subscription level, Resource group level or resource level.

For this app I am going to set it up against the subscription. First go to the Subscription you want to add it to and then Access Control (IAM)

I have added the app as a contributor

Creating a Key Vault

We will be selecting and creating IDs in the next steps, but instead of simply remembering your secret. Why not store it in a Key Vault.

  • Centralise Application Secrets
  • Store Secrets and Keys Securely
  • Monitor Access And Use

Lets set one up in our Proof of Concept area.

Create a Key vault if you don’t have one already

remember to add any tags you need before Review + Create

Once completed you can go to the resource (E.g. Data Factory) but for the time being that is all you need to do

Application ID and Tenant ID

You can now go into your new app in Azure (App registrations) to get more details for Data Factory (When you set up the connection)

Tenant from Data Factory will be mapped to Directory (Tenant ID) from the App Overview

Service Principal ID from Data Factory will be mapped to Application (Client) ID From the App Overview

Create a Client Secret

Next, create your Client Secret.

In your App go to Certificates and Secrets

Click New Client Secret

Im going to allow this secret to Expire in a year (Anything using the app will start to fail so you would need to set a new secret and re-authorise)

We can add this into the Key vault so we don’t lose it because once you have finished here you dont see it again.

Open a new Azure Window and Go to your new Key Vault

Go to Secrets

Click + Generate Import

Notice I have set the expiration date to match the expiry date of the app

Ensuring the Access is set for the Data Lake Storage

For this you need to have a Data Lake Gen 2 set up and Microsoft Azure Storage Explorer downloaded

In Microsoft Azure Storage Explorer, navigate to the storage

Then Right click on the File System (In this case factresellersales) go to Manage Access and add the app.

Notice that we have set Read Write and Execute for the app on the file system and all the files will inherit these permissions

Adding The Data Lake Gen 2 Connector in Data Factory (Test)

I have a Data Lake Gen 2 with some files and I want to move them into a SQL Data base.

To test, Open or create a Data Factory

Go into Author and Monitor. Then Author

Go to Connections, +New and Choose Azure Data Lake Gen 2

Tenant = Directory (Tenant ID) from the App Overview

Service Principal ID = Application (Client) ID From the App Overview

Service Principal Key (You can get it from Azure Key Vault. Click ON secrets,Then the name and current version

You can then copy the secret value and add it into Data Factory

Test your Connection

Create the Data Lake Data Set

Here is where you know that all your efforts all worthwhile.

Create a new Dataset which will be an Azure Datalake Gen 2

This is great. I have access to the files in the data lake. Achievement unlocked.

Use Data Lake Storage V2 as Dataflow Storage

This blog post follows on from

Dataflows are essentially an online collection and storage tool. Power Query Connects to data at source and collects and transforms that data. The dataflow then stores the data in a table within the cloud. They are stored in Data Lakes which is all automated for you.

Dataflows unify data from all your different sources. It should be noted that a Data Warehouse is still the recommended architecture with Data Flows over the top.

Dataflows also introduce the concept of the Common Data Service (CDS) and the Common Data Model (CDM). CDM allows organisations to use data formats to provide consistency across deployments. Now we have Azure Data Lake gen2 storage can be combined with data flows to store the data flows to provide and structured centralised data source.

Thanks to for helping me understand the differences between the two

When you integrate CDM with Data Lake Gen 2 you get structural consistency and you can use CDM Folders in the lake that contain your schemas in standard CDM format.

Dataflow definitions and data are stored in Model.json format. If you have a Model.json file, it shows that you are compliant with CDM.

Dataflows store their definition and data in CDM folders, in the Model.json formats. If you have Model.Json it shows you are adhering to CDM.

Of course, this can be quite difficult when you are working with data that does not adhere to CDM format. I can see it being really useful when you are starting from scratch but I have done some work looking at my data sources and they are always quite far from CDM format.

You can find information about the CDM here

And more information about CDS here

Advantages to setting up your own Data Lake Gen2 Store

Essentially, you can get by using the internal Data Lake Store but there are lots of reasons (And some of these advantages will be coming in future releases) why setting your own store up is a good thing.

  • Great for Re-use, If you are given access to the workspace you can use the dataflows already created for you.
  • Centralise your prepped data

Remember this doesn’t replace your data warehouse. It just adds a preparation and transformation layer above the data warehouse. Instead of having to wait to get your small change added to the warehouse you can add it to this layer.

  • Data within your data lake can be integrated into other solutions by developers
  • Data Lake Gen 2 is enormously scale-able for data
  • Dataflow data and definition file can be leveraged by developers for AI Services

Steps to Set Azure Data Lake Gen2 as Dataflow Storage

  • The storage account must be created in the same Azure Active Directory tenant as the Power BI tenant.
  • The storage account must be created in the same region as your Power BI tenant. To determine where you Power BI tenant is located
  • The storage account must have the Hierarchical Name Space feature enabled.
  • Power BI service must be granted a Reader role on the storage account.
  • A File system named powerbi must be created.
  • Power BI services must be authorized to the powerbi filesystem you create.

Once configured, it cant be changed. You cant go back to the default data store for your dataflows

Set Storage Account in Same Region as your Power BI tenant

Log into Power BI service , then Help ? and About Power BI

The Data is Stored in North Europe Ireland

When you set up your Data Lake Ensure North Europe region is selected

Set up Azure Data Lake V2 in Azure Portal

When you go into Azure Currently and look for Data Lake V2 you can only Find Gen 1

So the question is, how do you set up Gen 2 in Azure Portal? (Currently we are on the 25th November 2019. Hopefully this may get easier in the future)

First of all I go to the Subscription where I want to add the new data Lake v2

Open up the Portal menu (Now hidden to the left of the screen)

Choose Create a resource

next Choose Storage and Storage Account

Note that the Account kind is Storage V2 (General Purpose)

Make sure Location is the same as Power BI Service. I’m not using this functionality at the moment but there is no harm in applying this logic.

It is recommended to set replication setting to Read-access geo-redundant storage (RA-GRS)

For the time being, I am leaving everything else as standard

Next go to Advanced

the most important setting here is the Data Lake Storage Gen 2 . Enable the Hierarchical namespace and your storage account will now be created as data Lake Storage V2

Click Review and Create

Grant Reader Role to Power BI Service

This is all built in so it should be fairly straightforward.

In Azure go to your new storage account (If you aren’t already in it) and go to Add role Assignment

One there, choose the reader role and select Power BI Service which as you can see is already in the list.

It takes about 30 minutes for this to take effect.

Create a powerbi file System

Power BI Needs to use a Filesystem specifically named powerbi  so data flows can be stored in this specific file system.

We now have a few options available to us. I have some files to add so I am going to add them to a container

Click on Containers And then + File System

Note that to store dataflows its called powerbi Click OK

clicking on your new storage account(s) you are told to Download Azure Storage Explorer.

I already have this Azure Storage Explorer downloaded. If you don’t have this, its something you will absolutely need to work with Azure Storage accounts.

Once downloaded Open Azure Storage Explorer

You will need to Add in your Azure Storage Accounts by clicking the little connector icon

You will be asked to sign into your Account with your Office 365 credentials and 2fa authentication

This will log you into all your Subscriptions and Services

You are good to go

Here you find your subscription, Then go to the data Lake Storage Gen 2 and find the new File system powerbi.

Grant Power BI permissions to the file system

Before we connect we need to grant permission for Power BI to use the File System (Again this is specific to using DLV2 as a data flow store but at this point we may as well set up the permissions)

go to Azure Portal and Azure Active Directory

then select Enterprise Applications

Change the Application type Drop down to All Applications

Power Query Online and Power BI Premium and Power BI Service are in the list.

You will need the Object IDs of these applications.

Back to Azure Storage Explorer (Manage Access)

Navigate back to powerbi file system, Right click and Choose Manage Access

Click Add, Grab the object ID of Power BI Service to Manage Access

Set Read, Write and Execute Access to Service and Repeat the Process for Power BI Premium

Repeat for Power Query Online but Set Write and Execute Access

Other Also needs setting up as follows

Connect the datalake Gen Storage Account to Power BI Dataflows

To do this you need to be Power BI Admin. go to Power BI Service and navigate to the Admin Portal

From here Connect your Azure Data Lake Storage Gen2.

Add your Subscription ID, Resource group Name and Storage Account name of your Data Lake

It is now connected to Power BI

Allow Admins to Assign Workspaces

Finally, still in Admin Portal, go to dataflow Settings

Switch Allow Workspace admins to assign workspaces to this storage account to On

Workspace admins can now assign workflows to the filesystem created

Things to Consider

Here is where it starts to get a little bit hazy

  • This is all very much still in preview and there will be lots of updates coming
  • Once your dataflow storage location is configured it Cant be changed so dont do this on a whim.
  • You have to be an owner of the dataflow or be authorised to the CDM folder in the data lake to use the data flow
  • Once you have created a dataflow you ant change the storage location
  • It is your organisations data flow so there can only be one.

because of this, and the fact that its still in development I am going to wait to set up a central storage account for our workflows.

Im still unsure what you would do with Workflows that are already set up, Do they stay in the default area or can you reprocess them into the central data lake.

What happens if you want to move the data lake to a new subscription? is it not possible?

I will be going back to this when I have a few more answers to these questions

Setting up an Azure Data Lake V2 to use with power BI dataflows in Service (As a data source)

Previous to the brand new Azure Data Lake, I was adding all the files into Blob Storage. However Azure Data Lake V2 is built on Blob storage and DataLake V1

its built for big data and a fundamental change is that we now have a hierarchical namespace. This organises your files into directories.

So now, we can do things like use all files from a specific Directory, delete all files from a specific directory. We can categorise our files within the data lake.

Set up Azure Data Lake V2 in Azure Portal

When you go into Azure Currently and look for Data Lake V2 you can only Find Gen 1

So the question is, how do you set up Gen 2 in Azure Portal? (Currently we are on the 25th November 2019. Hopefully this may get easier in the future)

First of all I go to the Subscription where I want to add the new data Lake v2

Open up the Portal menu (Now hidden to the left of the screen)

Choose Create a resource

next Choose Storage and Storage Account

Note that the Account kind is Storage V2 (General Purpose)

Ive set the Location to North Europe, Simply because I know thats where our Power BI Data in Services is stored and I may as well stick with this.

For the time being, I am leaving everything else as standard

Next go to Advanced

the most important setting here is the Data Lake Storage Gen 2 . Enable the Hierarchical namespace and your storage account will now be created as data Lake Storage V2

Click Review and Create

Create a file System within a Container

We now have a few options available to us. I have some files to add so I am going to add them to a container

Click on Containers And then + File System

Click OK

clicking on your new storage account(s) you are told to Download Azure Storage Explorer.

I already have this Azure Storage Explorer downloaded. If you don’t have this, its something you will absolutely need to work with Azure Storage accounts.

Once downloaded Open Azure Storage Explorer

You will need to Add in your Azure Storage Accounts by clicking the little connector icon

You will be asked to sign into your Account with your Office 365 credentials and 2fa authentication

This will log you into all your Subscriptions and Services

You are good to go

Here you find your subscription, Then go to the Data Lake Storage Gen 2 and find the new File system.

I have added a folder here called Workshop1Files to my File System

Obviously Data Lake Storage gives you so many ways of working with files and automating the files to the storage area. In this case I am going to simply move a file into my new folder to work with

Double click on the folder and then Click Upload and Upload Files

And now your file is in the cloud, in an Azure Data Lake ready to use.

Connect to your Azure File with Power BI Desktop

The first test is can we access this data within Power BI Desktop.

Open Power BI Desktop and Get Data

Choose Azure Data Lake Storage Gen2 (Currently in Beta)

Add the URL

Data Lake Storage Gen2 have the following pattern https://<accountname><filesystemname>/<subfolder> 

Data Lake Storage Gen2 have the following pattern https://<accountname><filesystemname>/<subfolder> 

If you go to Right click on the file in Storage Explorer and go to properties, there is a difference in structure


If you try to connect with the original URL from Data Storage you get the following error

And if you change the URL from blob to dfs

There is a missing part to the puzzle. Go back to the Azure Data Lake Storage Account in Azure and Add Storage Blob Data Reader to your account

Then try again and hopefully you are in .

No need to combine because we have specified the file.

There are different ways you can load the file. I loaded one file but you can load all files in the File System

or all files under a directory in the file system (You can include sub directories in this)

Connect to your Azure File with Power BI Data Flow

I am creating data flows in the power BI Service to ensure they can be reused across the company. The question is, Can I Connect to the above File in Service via a data flow

In Power BI Service, add a Data Flow which takes you into Power BI Query Editor in the Service. I already had some data flows connected to an Azure database.

The data is in Azure Data Lake Storage so the first think I do is try the Azure route

However, there is no Azure Data Lake Storage Gen 2. This must be something coming in the future. so then I go to File and click on Get Data text / csv

You will need to add the File Path and your Credentials (As per previous advice use dfs not blob in the URL. this seems a little flaky at the moment. I choose Organisational Account first before adding the URL and then it seems to work.

Remember Go back to Azure Storage Explorer. if you click on properties, you can grab the URL from here

We don’t need a Gateway Setting up because everything is now in the cloud.

Clicking next, Nothing happens, it just keeps bouncing back to the same window.

Attempting to use the Blob Storage connector also doesn’t work (Using the Azure Account Key as authentication).

with blob in the URL
With dfs in the URL

It would appear that currently I have hit a brick wall and there is no current DLGen2 connector for Data Flows.

I will be keeping an eye open on this because obviously, when you are pushing the new generation of Data Lakes and Data Flows then there needs to be a DLGen2 Connector for Data Flows.


Had a reply back on the Power BI Forum (Not a good one)

The feature haven’t been planed. If there is any new message, the document: What’s new and planned for Common Data Model and data integration  will be updated.

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