Apache Airflow vs. SAP Data Quality Management

For a quick job scanning of status and deep-diving into job issues, details, and flows, AirFlow does a good job. No fuss, no muss. The low learning curve as the UI is very straightforward, and navigating it will be familiar after spending some time using it. Our requirements are pretty simple. Job scheduler, workflows, and monitoring. The jobs we run are >100, but still is a lot to review and troubleshoot when jobs don't run. So when managing large jobs, AirFlow dated UI can be a bit of a drawback.

Incentivized

When reporting, we use accurate data with no duplications since they are addressed by SAP DQM, we get the right target audience by analyzing marketing data, and also helps us to understand the current situation of our firm by comparing metrics.

Incentivized

• In charge of the ETL processes.
• As there is no incoming or outgoing data, we may handle the scheduling of tasks as code and avoid the requirement for monitoring.

Incentivized

• Eliminate all data duplicates, which affects the space and the inefficiency of the database.
• Further, SAP Data Quality Management has determined address cleaner, very friendly in making systems and data verification a success.
• Simplistic customization strategies, that personalize all the business processes.

Incentivized

• they should bring in some time based scheduling too not only event based
• they do not store the metadata due to which we are not able to analyze the workflows
• they only support python as of now for scripted pipeline writing

Incentivized

• Sometimes it is hard to find which is the correct report to run to find the desired details.
• We attach contractor invoices in SAP and it isn't very easy to get in to them.
• The user interface could overall use a little work to make the system more user friendly and ultimately more efficient to use.

Incentivized

Easy to learn Easy to use Robust workflow orchestration framework Good in dependent job management

Incentivized

As with other SAP products, there is excellent support from SAP on this new tool.

Incentivized

There are a number of reasons to choose Apache Airflow over other similar platforms- Integrations—ready-to-use operators allow you to integrate Airflow with cloud platforms (Google, AWS, Azure, etc) Apache Airflow helps with backups and other DevOps tasks, such as submitting a Spark job and storing the resulting data on a Hadoop cluster It has machine learning model training, such as triggering a Sage maker job.

Incentivized

The client was on a SAP platform for most of their applications and also is planning to implement SAP Hana very soon. This tool was fitting good for the requirement of the client to manage the quality of the data and hence adapt it in the system. Also, it can go well with the BO reporting.

Incentivized

• A lot of helpful features out-of-the-box, such as the DAG visualizations and task trees
• Allowed us to implement complex data pipelines easily and at a relatively low cost

Incentivized

• The merging of data, from numerous sources, makes the metrics of analytics accurate and they manage decisions.
• Besides, SAP Data Quality has a robust cleansing tool for data, making it effective to obtain it from different secure and affirmed sources.
• Finally, SAP Data Quality deals with sales analysis, very reputable in making information available for competitive market support.

Incentivized