We built our free Azure DataFactory template to help you build your data pipelines from Salesforce to Snowflake in 5-30 minutes. Quick extraction and loading of data into your data lake or data warehouse is important. The value of data is not realized by collecting and moving it. Transforming data into analytics insights and visibility for business consumption is the objective when you invest in a data warehouse like Snowflake. That is why we have built our free templates to reduce the level of effort to get your data ready for analysis up to 90%! View our documentation to lean how
In 2023, we launched the first version of our template tagging it as a “5 min data lake with Azure DataFactory”. Adoption and feedback led us to close 2024 with an upgraded version of our template alongside our new DataTools doctor service and our revised Snowflake rapid adoption service to help you get extract value from data and technology faster.
Download our Azure DataFactory Template Now
Why we build Salesforce to Snowflake pipelines with Azure DataFactory?
Fast, cheap and easy rarely happens in technology, but the Azure team, without a massive marketing blitz or fanfare created a very solid product for moving data between enterprise data sources in to Microsoft data platform and Snowflake.
We use Azure DataFactory pipelines to move massive volumes of data daily for customers who have invested in Azure. They save thousands of dollars per month while getting enterprise grade data extraction and migration.
When do we turn to other solutions than DataFactory?
We stick to technology tools that are flexible, practical, and well adopted. DataFactory in particular we like deploying with customers who are running MS SQL or Snowflake in Azure. When it comes to data transformation and ETL patterns, DataFactory does offer a no/low code Spark based Flow builder. However, depending on customer needs, scale, and team makeup, we do recommend alternative solutions that is catered to the existing processes, investments, team makeup and roadmap. We are always on the lookout for new, streamlined data pipeline solutions.
What’s Next for our Azure DataFactory template?
We are actively working on client projects for MySQL and MS SQL version of our template. Contact us for more details
Salesforce data pipelines to Snowflake free template
1. Create Data Connections
Connect Azure Data Factory to Salesforce.com (New 2024)
Connect Azure Data Factory to Snowflake
2. Create Data Sources
Create a Snowflake Data Source in Azure Data Factory
Connect to Salesforce Lead and Account Object with Azure ADF
3. Move Data Between Applications
Create a Data Pipeline to Connect Salesforce to Snowflake
4. Publishing and Administration
What’s New in our Salesforce to Snowflake Pipelines
This week, we rolled out a long overdue update for our free Azure DataFactory template that makes extracting Salesforce data into Since 2023, there have been a lot of changes to Azure DataFactory, so we have rolled out a long overdue update and upgrade.
From our version 1.0.1 release notes:
- New meta data staging process and table called “SFDC_METADATA_STAGE_TEMP” that feeds SFDC_METADATA_STAGE
- Support for new field detection and addition (enable append fields)
- New parameter AppendFields will insert new fields when detected
- New parameter SnowErrorHandling allows for configurable error handling to skip error rows, skip file, or throw an error.
- New MetaData field called “Status” that allows for “Disable” attribute that will ignore fields from being synchronized.
- Update to Salesforce metadata request that supports compound fields by default like FirstName, LastName, Street, City, etc.
- Pre-install check – End to end flow checks for existence of the metadata object
- Added status variables to determine results for each pipeline for easier debugging
- Schema insert and updates managed via merge by object.field ID
- Changed field from ID to DurableId Salesforce field to Snowflake SFDC_METADATA_STAGE “ID”
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