Link to the Machine Learning and AI applications podcast series.
Here is an updated blog that shall guide you with the resources needed to the machine learning journey with SAP S/4HANA.
While the blog series provides you a quick start into the concepts around machine learning with SAP S/4HANA, I want to discuss a few other things and provide pointers in that direction. This blog series discusses in detail, the historical background of SAP's journey into machine learning and the various techniques of leveraging machine learning with SAP S/4HANA, the architecture details, the processes involved and the scope & functionality of how these are implemented into the SAP S/4HANA's business processes. Machine Learning and infusing intelligence into SAP S/4HANA business processes is a very important topic here at SAP and the key ingredient is the ISLM framework (Intelligent Scenario Lifecycle Management). You can find a host of information at our ISLM community.
There is a host of information available at our SAP AI community with a bunch of blogs around the topics of how to use SAP AI tools in the context of building machine learning models and productizing them to be deployed into ERP applications. With the GA of SAP AI Core and SAP AI Launchpad in the Q4 of 2022, SAP customers and partners can now create their own ML models using this ML Ops platform or bring-in the AI models from other external frameworks to be deployed using SAP AI Core. We have also discussed the concepts around how to consume the pre-built AI Business Services in our side-by-side machine learning blog. More information about the AI Business Services can be found in the SAP AI community blog.
Additionally, the blogs around AI and Machine Learning talk more on this topic with special focus on Gen AI as well. Also refer to the blogs around SAP Joule on the topics around conversational intelligence and SAP digital Assistants.
I would also recommend you to walk thru' another legacy blog series written by Orla Cullen and few of her colleagues on how to leverage the SAP Analytics Cloud Smart services and create predictive models for the data source based out of SAP S/4HANA. Please check this blog series in the context of SAC with S/4 and also the wider community on SAP Analytics Cloud.
Continuing further, the OpenSAP platform at SAP provides huge set of online material and curriculum to understand the various aspects of machine learning and predictive analytics with SAP S/4HANA. Currently, even though there are no new upcoming courses on the topics of machine learning and predictive analytics, there are a lot of other self-paced courses when you search on those topics. These self paced courses would provide you the right ammunition to get started into the machine learning journey with SAP S/4HANA. Here is the link to the OpenSAP platform at SAP. We are planning a few openSAP courses in the machine learning and predictive analytics space in tWenty21.
One such OpenSAP course was delivered in September 2021 and which gave an in-depth view into the general concepts, strategies, and features around embedded analytics. This course also included the predefined business content and tools for the business user as well as the tools for the analytics specialist. In addition, the course also provided an introduction to embedded predictive and machine learning features and detailed information about the integration of SAP S/4HANA data into SAP Analytics Cloud and SAP Data Warehouse.
There are also other resources such as the best practices explorer that also helps your journey in understanding machine learning with SAP S/4HANA. At the best practices explorer, you will need to find the different packages with SAP S/4HANA by selecting either S/4 Cloud or S/4 OnPremise or Analytics etc. You can pick any of these or other packages and understand the different SAP S/4HANA business processes. Now while navigating into a particular business process, you can always search for any machine learning functionality that is implemented into SAP S/4HANA by reviewing the provided documentation and knowledge assets there-in! For a complete understanding of the available machine learning functionality in S/4, you can always check this blog!
Additionally, there is also a best practices package specifically around "Machine Learning & Predictive Analytics with SAP S/4HANA" which provides a step-by-step guide on the different aspects of machine learning with SAP S/4HANA, explains the different approaches of doing machine learning with SAP S/4HANA and finally provides access to all the different use cases along with the scope items corresponding to them. We have a created 2 different scope items or documentation that explains how to use ISLM while embedding in the SAP S/4HANA Cloud as well as embedding the the SAP S/4HANA On-premise. Additional 2 different scope items or documentation are created that explains how to use the ISLM with ML services built on BTP and configured to run with SAP S/4HANA both on-premise and cloud. There is another scope item which explains how to use ML with SAP Analytics cloud.
Though the year tWenty20 was completely different due to the pandemic, the customer conferences such as SAPPHIRE, TechEd continued in a virtual mode with welcome and appreciation by our customers, partners and consultants. The virtual conferences continue for the year tWenty21 as well. There have been numerous amount of these sessions and learnings around machine learning and predictive analytics that could help your journey into the enterprise AI space. You can virtually listen into this content.
To top this all, the help portal provides a lot of information and resources that you can search around machine learning and predictive analytics for SAP S/4HANA.
Also an SAP CAL appliance image is available for customers and partners to try out some of the example ISLM ML scenarios which are embedded into SAP S/4HANA. You can find more information here about the SAP CAL appliance. Our new update in dec 2022 to the CAL appliance now helps you to try out not only the embedded ML scenarios but also the side-by-side ML scenarios built on BTP and configured to run on SAP S/4HANA. Please check the blog section "Analytics and AI" for more details and specifically the 2022 blog update.
Other opportunities also include purchasing a book that was authored in 2020 by me along with my colleague Dr. Siar Sarferaz. You can find the details of that book at the blog or searching for "Implementing Machine Learning with SAP S/4HANA" at any of the major online stores.
Finally I would like to conclude this blog introducing the podcast series on AI and machine learning. You can find more details about this podcast series by searching on the web or looking up here and subscribing or following me on spotify!
The journey into the AI world of enterprise technology has just started and it is interesting to see the amount of progress made even in an eventful year like tWenty20 though with all the strange things going on around. With the advent of the enterprise AI start-ups getting into the IPO race, history shall witness the year 2020 as a major turning point for the enterprises transitioning at a major scale into the AI space. Now with the introduction of Generative AI in the year 2022, the topic of LLMs gained a lot of interest with AI in the center. The tools, technologies and services currently available are easily helping to democratize AI into the enterprise world by infusing the business processes with contextual intelligence while adding historic perspectives to predict better outcomes. Stay tuned for interesting updates in the space of AI and Gen AI from SAP!
Happy predicting the future with SAP!
Stay safe and let's predict a better future!!!
Here is the list of the blogs in the series:
Resources and journey to machine learning with SAP S/4HANA (this blog)
Blog series on ISLM: Machine Learning with SAP S/4HANA using ISLM (Updated May 5th 2022)
Blogs and Community: Community page for SAP AI Business Services
Blogs on topics around AI:
Blogs on SAP Analytics Cloud - Smart Predict
Custom Machine Learning Blogs & Demo guides:
Additional Material:
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