Azure Data Factory vs. SAP Subscription Billing

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

The last one, we had to add a historical discount for a customer that sent us its usage data with significant delay. Because the software is designed to have a linear flow of onward-looking data, retroactively fixing previous records felt like working against the system. But when we launched a new product with tiered pricing and setup fees, the configuration was fast

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

• SAP Subscription Billing helps in reconciliations of data , Posting journals and helps in providing accurate data during month end,
• Subscription Billing integrates with S/4HANA and helps use existing models to create accurate reports.
• Subscription Billing also provides AI capability to enhance the functionality to provide accuracy in data reporting.

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

• It is working fine for our organization no improvement needed.

Incentivized

Based on ROI, it seems like a good investment.

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

It scores 8 because it dramatically simplifies SaaS rate configuration and automates complex mid cycle proration out of box. It only looses points due to configuration guard rail

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

No in-house support.

Incentivized

Not involved in implementation.

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

SAP BRIM (Billing and Revenue Innovation Management) is part of SAP portfolio and therefore from package perspective a better choice. We implemented Zuora first but moving over to BRIM; faster implementation, better operations cost and support within SAP RISE Contract Package

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

• Saves around 20-25% time in creating and checking the invoices/billings data .
• ability to integrate with S/4HANA which is our legacy system helps to use existing data models to save time in creating new ones.

Incentivized