Azure Data Factory vs. Salesforce Data 360

Best scenario is for ETL process. The flexibility and connectivity is outstanding. For our environment, SAP data connectivity with Azure Data Factory offers very limited features compared to SAP Data Sphere. Due to the limited modelling capacity of the tool, we use Databricks for data modelling and cleaning. Usage of multiple tools could have been avoided if adf has modelling capabilities.

Incentivized

Great tool for client management, sales tracking, cases studies. Using is as the source of truth for all client communication. Allowing more integration options for cc and ACH payments. Right now the options are limited and only integrate with strict processing capabilities that are not always in the businesses best interest.

Incentivized

• Data Ingestion - it works very well with numerous data sources.
• Data pipeline orchestration: It is a generic, popular tool for orchestrating data pipelines.
• Works well in Azure ecosystem, Azure services and data platforms like Databricks.
• It is a serverless and scalable solution for cloud data integration.

Incentivized

• Allows use to bring external data into Salesforce as zero-copy
• Is able to present data using standard Salesforce reports familiar to our users
• Allows us to establish multiple relationships between our CRM data and the external data to contextualize the imported data.

Incentivized

• Granularity of Errors: Sometimes, Azure Data Factory provides error messages that are too generic or vague for us, making it challenging to pinpoint the exact cause of a pipeline failure. Enhanced error messages with more actionable details would greatly assist us as users in debugging their pipelines.
• Pipeline Design UI: In my experience, the visual interface for designing pipelines, especially when dealing with complex workflows or numerous activities, can become cluttered. I think a more intuitive and scalable design interface would improve usability. In my opinion, features like zoom, better alignment tools, or grouping capabilities could make managing intricate designs more manageable.
• Native Support: While Azure Data Factory does support incremental data loads, in my experience, the setup can be somewhat manual and complex. I think native and more straightforward support for Change Data Capture, especially from popular databases, would simplify the process of capturing and processing only the changed data, making regular data updates more efficient

Incentivized

• pricing or costing visibilty, we can't estimate what would be consumption this month and suddenly we get surprised
• CI/CD can be improved, that looks a difficult and hard
• Also sandbox comes with many limitation so very hard to replicate production like environment to test

Incentivized

So far product has performed as expected. We were noticing some performance issues, but they were largely Synapse related. This has led to a shift from Synapse to Databricks. Overall this has delayed our analytic platform. Once databricks becomes fully operational, Azure Data Factory will be critical to our environment and future success.

Incentivized

Most of the daily use features, are very usr friendly, intuitive, every end user can learn how to manage and operate basic activities such as enter information, send an email, send a campaign, create an email marketing template, run a report on the renewals for the month, open and close a support case, create new account or a new contact, etc

Incentivized

We have not had need to engage with Microsoft much on Azure Data Factory, but they have been responsive and helpful when needed. This being said, we have not had a major emergency or outage requiring their intervention. The score of seven is a representation that they have done well for now, but have not proved out their support for a significant issue

Incentivized

Azure Data Factory helps us automate to schedule jobs as per customer demands to make ETL triggers when the need arises. Anyone can define the workflow with the Azure Data Factory UI designer tool and easily test the systems. It helped us automate the same workflow with programming languages like Python or automation tools like ansible. Numerous options for connectivity be it a database or storage account helps us move data transfer to the cloud or on-premise systems.

Incentivized

we have evaluated Snowflake, adobe rt-cdp as well. They also offer a very strong capabilities but the Data 360 is more suitable for us because of the same Salesforce ecosystem. The main key factor is without any custom code we were able to include it into our automations. And ofcourse with agentforce already in plans, we had to pick Data 360

Incentivized

• Facilitate better decision-making and improve business processes.
• Optimize business process outcomes by increasing internal efficiency and operational effectiveness.
• Boosts revenue growth while improving business process agility.

Incentivized

• Salesforce Data Cloud has a positive impact on me as a realtor because it is easy to generate reports on customer data and see what is needed to be bumped to the next level. We have to earn a certain commission by the end of the year and it makes it easy to see how close you are
• It has a positive impact on keeping track of customers because it is nice to have it all in one place which is a nice time saver
• I like that you can even see customer info from other agents making it nice to compare and try and pass others
• Makes the customers journey smooth sailing because everything is in one place

Incentivized