I'm looking for some advice around using Azure Data Factory to migrate data from Salesforce to Dynamics365.
My research has discovered plenty of articles about moving salesforce data to sinks such as azure data lakes or blob storage and also articles that describe moving data from azure data lakes or blob storage into D365.
I haven't found any examples where the source is salesforce and the sink is D365.
Is it possible to do it this way or do I need to copy the SF data to an intermediate sink such as Azure Data Lake or blob storage and then use that as the source of a copy/dataflow to then send to D365?
I will need to perform transformations on the SF data before storing it in D365.
Thanks
I would recommend to add ADLS Gen 2 as a Stage between SalesForce and D365
I am afraid that a direct sink as D365 can be done
Related
I have a requirement to export data from Azure SQL managed instance to data lake storage as json documents. I have to use SQL Server Integration Services to accomplish this. I tried using the Flexible File Destination Data Flow task but when I see the supported file formats there's no json being supported. What other options do I have to accomplish this.
Azure Data Factory support data movement between Azure Managed Instance and Data lake account, but unfortunately when the destination is Azure Data Lake storage it also doesn't support JSON format using SSIS.
Azure Data Lake Store Destination
The Azure Data Lake Store Destination component enables an SSIS
package to write data to an Azure Data Lake Store. The supported file
formats are: Text, Avro, and ORC.
Workaround: The possible workaround you can try to use Data Flow activity in Azure Data Factory. Load the data from Managed Instance and transform it using Pivot transformation and store the processed data in Data Lake. This approach doesn't involve SSIS. Check this similar kind of request and approach here.
I have been looking for options to migrate data present in my ADLS in one subscription to ADLS in another subscription within Azure. I tried ADF for this purpose and it worked fine.
But the copy speed is too slow in ADF. It copies at a speed of 10-15 KB/sec. Is there some way to increase speed of copy while using ADF?
Yes, there is a way you can migrate data from Azure Data Lake between different subscription: Data Factory.
No matter Data Lake Gen1 or Gen2, Data Factory all support them as the connector. Please ref these tutorials:
Copy data to or from Azure Data Lake Storage Gen1 using Azure Data Factory.
Copy and transform data in Azure Data Lake Storage Gen2 using Azure
Data Factory.
You can create the source and sink dataset in different subscription through linked service:
But this option may cost you some money. You also could ref the Azure Az-copy tutorials: Copy blobs between Azure storage accounts by using AzCopy.
Here is another blog How To Copy Files From One Azure Storage Account To Another:
In this post, Bloger will outline how to copy data from one Azure
Storage Account in one subscription to another Storage Account in
another subscription.
These maybe what you're looking for.
I am just going through some Microsoft Document and doing handOn for Data engineering related things.
I have couple of queries for a scenrerio - "copy CSV file(s) from Blob storage to Synapse analytics (stage table(s)):
I read that we can do direct data pull in Synapse with the process of creating external tables. (https://learn.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/load-data-wideworldimportersdw)
If above is possible, then in what cases we do use Azure Data factory Copy or data flow method?
While working with Azure data factory, is it a good idea to use Polybase, because it will use Blob storage again as staging in this scenrerio (i.e. I am copying file from Blob only and again using blob for staging)?
I searched for answers to my queries but haven't found any satisfactory answer yet.
If you're just straight loading data from CSV into DW, use Copy. Polybase is recommended, but not always needed for small files.
If you need to transform that data or perform updates, then use data flows.
My company has two Azure environments. The first one was a temporary environment and is being re-purposed / decommissioned / I'm not sure. All I know is I need to get files from one Data Lake on one environment, to a DataLake on another. I've looked at adlcopy and azcopy and neither seem like they will do what I need done. Has anyone encountered this before and if so, what did you use to solve it?
Maybe you can think about Azure Data Factory, it can helps you transfer files or data from one Azure Data Lake to Another Data Lake.
You can reference Copy data to or from Azure Data Lake Storage Gen2 using Azure Data Factory.
This article outlines how to use Copy Activity in Azure Data Factory to copy data to and from Data Lake Storage Gen2. It builds on the Copy Activity overview article that presents a general overview of Copy Activity.
For example, you can learn from this tutorial: Quickstart: Use the Copy Data tool to copy data.
In this quickstart, you use the Azure portal to create a data factory. Then, you use the Copy Data tool to create a pipeline that copies data from a folder in Azure Blob storage to another folder.
Hope this helps.
Currently as part of our requirements we are working with the below Azure components
Azure Event Hub
Azure Stream Analytics
Azure Table Storage
Azure Sql DB
Basically with first 3 components, we will be building an Analytics and Reports platform.
Currently as we just started we analyze the data from Azure Table Storage and display it in the analytics dashboard.
Recently we came across a new Azure product Azure Data Lake . Doing some research on microsoft website , we could see we can easily migrate data from Azure Table Storage (with help of Azure Data Factory) to Azure Lake Store. Creating big data pipelines using Azure Data Lake and Azure Data Factory
As we go through the above link, it's mentioned that we need to create an Azure Data Lake Analytics pipeline to process the data.
So what am unclear is the where will be analytics output data will be saved. Do we need to save the analytics output to some DB ? or can we real-time analytics through a Http request ?
We have huge number rows of records in Azure Table Storage that will be moved to Azure Data Lake. For this scenario is it a good option or Can we go an analytics-based solution from Azure Table Storage itself.
Please share your thoughts
You can store your analytics output data on Azure Data Lake Store (a data repository that enables you to store all kinds of data in their raw format without defining schemas.) after processing it through Azure Data lake Analytics (An analytics service that enables you to run jobs on data sets without having to think about clusters.)
As you said "We have huge number rows of records in Azure Table Storage that will be moved to Azure Data Lake.", I think performing analytics on data placed on Azure data lake store is much more efficient because it offers unlimited storage with immediate read/write access to it and scaling the throughput you need for your workloads. It's also offers small writes at low latency for big data sets. So I believe it is better choice then Azure Table storage.