Azure Machine Learning vs. Joule vs. Moveworks

For [a] data scientist require[d] to build a machine learning model, so he/she didn't worry about infrastructure to maintain it.

All kind of feature[s] such as train, build, deploy and monitor the machine learning model available in a single suite.

If someone has [their] own environment for ML studio, so there [it would] not [be] useful for them.

Joule explained ATC findings, including root cause, business impact, recommended APIs, and examples of fixes for S/4HANA readiness checks. Joule today is a point-in-time assistant — great for one question, one generation, one explanation at a time. It is not yet capable of owning a full development flow.

Moveworks is great at automating simple functions with zero human touch and requests, like unlocking user accounts, resetting user passwords, and adding users to DL ticket creation. These functions reduce total calls to our help desk.

Incentivized

• User friendliness: This is by far the most user friendly tool I've seen in analytics. You don't need to know how to code at all! Just create a few blocks, connect a few lines and you are capable of running a boosted decision tree with a very high R squared!
• Speed: Azure ML is a cloud based tool, so processing is not made with your computer, making the reliability and speed top notch!
• Cost: If you don't know how to code, this is by far the cheapest machine learning tool out there. I believe it costs less than $15/month. If you know how to code, then R is free.
• Connectivity: It is super easy to embed R or Python codes on Azure ML. So if you want to do more advanced stuff, or use a model that is not yet available on Azure ML, you can simply paste the code on R or Python there!
• Microsoft environment: Many many companies rely on the Microsoft suite. And Azure ML connects perfectly with Excel, CSV and Access files.

Incentivized

• Users can prompt Joule to create business partners in MDG.
• The change process for Business partner (Customers/Suppliers) updation is made easy, particularly for updating data such as address and communication details.
• The workflow process has been simplified by Joule agents, such as identifying the high-priority task and sharing it with the end user.
• Improved data quality to almost 30%~50% in the CR creation process, which is a significant milestone for us.

Incentivized

• Understanding employee questions and serving up information and answers
• Very easy to add new content into the chatbot
• Excellent customer support

Incentivized

• It would be great to have text tips that could ease new users to the platform, especially if an error shows up
• Scenario-based documentation
• Pre-processing of modules that had been previously run. Sometimes they need to be re-run for no apparent reason

Incentivized

• In SuccessFactors Joule should have more tools out of the box.
• There should be more examples on what is possible to do with Joule or Joule Studio in Successfactors, all available examples seem to focus only on Payroll or Inventory management leaving the HR behind.
• Document Grounding should be easier to implement, and should be possible to have some kind of permissions per couuntry / user group for specific documents. The implementation with Sharepoint makes it harder to complete because normally we need some extra team to join and help and until now, I always had issues implementing it. I believe that it would make it much easier if the documents could be stored and managed inside SuccessFactors.

Incentivized

• Conversations, asking users refining questions to better tailor responses

Incentivized

As we explore, we can learn more. As i believe, we can only learn to live and live to learn stuffs. So as well AI does the same and improve itself. By trying and prompting joule more, we can use it in better ways. I would definitely wait and use the new versions shared in SAP Teched on Joule with more LLM involved

Incentivized

Easy and fastest way to develop, test, deploy and monitor the machine learning model.

- Easy to load the data set

-Drag and drop the process of the Machine learning life cycle.

I would rate Joule’s overall usability a 10 out of 10 because it makes interacting with SAP incredibly simple, intuitive, and fast. The conversational interface removes the complexity normally associated with navigating SAP modules, running transactions, or building reports. Even non-technical users can get meaningful insights within seconds just by asking natural language questions.

Incentivized

as its cloud based, as of now, we see it available all the time and havent faced any issues while accessing. Not sure if this has high availability and Disaster recovery features got set up already with the default version that we are using at our organization. no issues so far.

Incentivized

SAP Joule's pages load quickly and it does display the information on what we are looking for w.r.to the knowledge base or the SAP articles.

Incentivized

Support is nonexistent. It's very frustrating to try and find someone to actually talk to. The robot chatbots are just not well trained.

Incentivized

Usually support for Joule takes longer than normal, and the correct answer always takes a long time to get, or we just don't get it at all, and we fix ourselves.

Incentivized

Not sure

Joule implementation was easy but it has too many steps, it would be nice if part of the steps could be done automatically.

Incentivized

It is easier to learn, it has a very cost effective license for use, it has native build and created for Azure cloud services, and that makes it perfect when compared against the alternatives. As a Microsoft tool, it has been built to contain many visual features and improved usability even for non-specialist users.

Incentivized

Joule is better because it doesn't take only data available on the web, but combines that with data provided directly by the game publisher through API to us which includes every single match played = all data points from all of those matches. That means that for us Joule gives deeper insights than any online AI chat agent could do

Incentivized

Yes as sap is used widely across organisation

Incentivized

• Productivity: Instead of coding and recoding, Azure ML helped my organization to get to meaningful results faster;
• Cost: Azure ML can save hundreds (or even thousands) of dollars for an organization, since the license costs around $15/month per seat.
• Focus on insights and not on statistics: Since running a model is so easy, analysts can focus more on recommendations and insights, rather than statistical details

Incentivized

• Allow us to have everyday operations smoother by automating repetitive tasks and reducing manual efforts, which saves time and improves efficiency.
• Facilitate effortless information access, since it allows us to search and receive instant responses.
• Reduces the complexity of SAP by pulling data from different modules and making it clear quickly.

Incentivized

• 22% reduction in calls to support channels
• Employee growth without needing to add support personnel

Incentivized