Have had a look around but can't see any concrete information. Essentially, if anyone could help it would be great. We are building reporting in the cloud and looking to ingest data from Dataverse that can then be reported on in Power BI
Looking at everything i can see, there is Azure Synapse and Data Factory. What i am trying to understand and learn is whether we use either ADF or Synapse or if its a combination of both
Going into ADF Studio and Synapse Studio, they look very similar so not quite sure what i should be using for this
If anyone could help or provide some info, that would be great
Thanks
Azure synapse provides all the functionalities of Azure Data factory and even more. Using both Azure Synapse studio and Azure data factory, you can perform ETL (extract, transform, load) operations without using any code. Azure Synapse provides enterprise data warehousing and big data analytics.
Azure data factory is a data integration service that allows user to create workflows for moving data and transforming it. Azure synapse, however, will provide additional services like notebooks, SQL scripts, store tables etc. All these functionalities help to ingest, prepare, manage, and analyze data using Power BI or Machine learning.
If you want to use Azure data factory to ingest data, you need to use either azure synapse or Power BI to analyze your data and build reports. But using Azure synapse is a much better choice because it has an integrated Power BI service which allows you to build reports or datasets within the Synapse studio. Hence it would be a better choice to use Azure Synapse instead of Azure data factory or a combination of both.
To understand more about the differences between azure synapse and azure data factory, refer to the following link.
https://azurelessons.com/azure-synapse-analytics-vs-azure-data-factory/
The following link provides an insight about how to use azure synapse studio to work on Power BI.
https://learn.microsoft.com/en-us/azure/synapse-analytics/get-started-visualize-power-bi
Related
I have a requirement to copy the table from on premise sql database hosted on linux server to Azure datalake using azure data factory. Self hosted integration works natively for windows system. Can someone share your thoughts or work around to achieve this requirement?
Regards
Aravindan
Unfortunately, this cannot be achieved as the SHIR has below system requirements and in order to connect to onPrem data sources ADF requires SHIR.
A workaround could be using SSIS packages in Linux to extract the data. For more information, please refer to this documentation: Extract, transform, and load data on Linux with SSIS
is there any automated way to directly create bugs in Azuredevops projects dashboard and assigned to team whenever Aure loganalytic query based alerts triggered?
Basically, if the Azure Log Analytics query based alerts can call other services or APIs, then it's possible to create work items by calling the REST API Work Items - Create. But, there doesn't seem to be a built-in way to do this.
However, there's an Azure Log Analytics connector in Power Automate. You can try to setup a flow using the Azure Log Analytics and Azure DevOps connectors in Power Automate. The flow will be triggered when the Azure Log Analytics query based alert is trigged.
You need to call the Work Items - Create REST API in flow to create the bug. More information please reference Add an Attachment in Azure Dev Ops using MS Flow and Azure DevOps Integration (via Microsoft Power Automate)
I have 150 pipelines and many datasets defined in Azure data factory. I want to take backup of live code everyday and save it to the code repository.
What is the best approach to backup the Code/pipelines/datasets/linked services to GIT repository. Do we have any API's available for the task?
Can we achieve this with PowerShell code? if yes, please share the PS code if you have it handy.
Appreciate your help..
Set up a code repository in the Azure data factory, then you can save all your resources to Azure DevOps or GitHub and get the Backup.
Please follow the below reference it has detailed expiation of GitHub code repository setup and Restores, backup of Azure data factory.
You can use another way to take Backup and Restore Azure Data Factory using an ARM template.
Reference:
https://www.sqlshack.com/using-source-control-in-azure-data-factory/
How to Backup and Restore Azure Data Factory from ARM Template ?
https://www.youtube.com/watch?v=X5uMYO06aMI
How to Backup and Restore Azure DevOps code repositories ?
How do I trigger a notebook in my Azure Machine Learning notebook workspace from Azure Data Factory
I want to run a notebook in my Azure ML workspace when there are changes to my Azure storage account.
My understanding is that your use case is 100% valid and it is currently possible with the azureml-sdk. It requires that you create the following:
Create an Azure ML Pipeline. Here's a great introduction.
Add a NotebookRunnerStep to your pipeline. Here is a notebook demoing the feature. I'm not confident that this feature is still being maintained/supported, but IMHO it's a valid and valuable feature. I've opened this issue to learn more
Create a trigger using Logic apps to run your pipeline anytime a change in the datastore is detected.
There's certainly a learning curve to Azure ML Pipelines, but I'd argue the payoff is in the flexibility you get in composing steps together and easily scheduling and orchestrating the result.
This feature is currently supported by Azure ML Notebooks. You can also use Logic apps to trigger a run of your Machine Learning pipeline when there are changes to your Azure storage account.
So I am facing the following problem: I have a bunch of Azure Data Factory V1
Pipelines in one specific data factory, these pipelines, each have, around 400 data sets.
I need to move all of them to a new resource group / environment and put their json definition in a git repo.
So my questions is, how can I download all the pipelines definitions for a data factory and all the data sets definitions in their json format from Azure?
I don't want to click each one and copy-paste from the Azure UI, as it will take ages.
Call Rest API is good way for both V1 and V2. See this doc.
For ADF V1, you can try using Visual Studio.
Connect via Cloud Explorer to your data factory.
Select the data factory and choose Export to New Data Factory Project
This is documented on SQL Server Central.
Another thing to try is to have Azure script out an ARM template of the Data Factory.