SAP Machine Learning
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Machine Learning Features in SAP Products
What is Machine Learning?
Machine learning (ML) is a subset of artificial intelligence (AI) algorithms. The differentiating aspect of these algorithms is that they can learn from the input data and modify the model based on changes in that data. It is this “learning” aspect that makes these algorithms powerful.
Machine Learning Applications in SAP Portfolio
SAP applications leverage ML algorithms extensively to embed innovative capabilities within their solutions, help end-users perform advanced analytics with minimal technical proficiency, and allow data scientists and ML engineers to build advanced models and solutions. Below are some examples:
- SAP HANA
SAP HANA has been designed to be easily leveraged as a scalable ML platform. A powerful built-in tool is the predictive analytics library (PAL). A component of the application function library in HANA, PAL includes several algorithms to enable the most frequently used predictive analytics use cases. For advanced users who want to explore advanced algorithms like deep learning, extended machine library (EML) in HANA allows such users to leverage TensorFlow to build deep learning algorithms.
- SAP Data Intelligence
SAP data intelligence has a rich ML content library. This library, which has an ML scenario manager and ML operations cockpit, allows engineers and data scientists to collaborate and build ML models.
- SAP Analytics Cloud Smart Predict
Like most best-of-breed analytics tools, SAP Analytics Cloud provides users the ability to leverage advanced ML algorithms. While ML algorithms have many applications, predictive analytics remains a key one.
Key Considerations
Machine Learning Features in SAP Products
What is Machine Learning?
Machine learning (ML) is a subset of artificial intelligence (AI) algorithms. The differentiating aspect of these algorithms is that they can learn from the input data and modify the model based on changes in that data. It is this “learning” aspect that makes these algorithms powerful.
Machine Learning Applications in SAP Portfolio
SAP applications leverage ML algorithms extensively to embed innovative capabilities within their solutions, help end-users perform advanced analytics with minimal technical proficiency, and allow data scientists and ML engineers to build advanced models and solutions. Below are some examples:
- SAP HANA
SAP HANA has been designed to be easily leveraged as a scalable ML platform. A powerful built-in tool is the predictive analytics library (PAL). A component of the application function library in HANA, PAL includes several algorithms to enable the most frequently used predictive analytics use cases. For advanced users who want to explore advanced algorithms like deep learning, extended machine library (EML) in HANA allows such users to leverage TensorFlow to build deep learning algorithms.
- SAP Data Intelligence
SAP data intelligence has a rich ML content library. This library, which has an ML scenario manager and ML operations cockpit, allows engineers and data scientists to collaborate and build ML models.
- SAP Analytics Cloud Smart Predict
Like most best-of-breed analytics tools, SAP Analytics Cloud provides users the ability to leverage advanced ML algorithms. While ML algorithms have many applications, predictive analytics remains a key one.
Key Considerations
- Develop a fundamental understanding of algorithms: Explore what specific algorithms are available and understand where they can be leveraged. This will help you get optimal value from these tools. As an example, you should be aware that you can use clustering algorithms for customer segmentation. Here is an example of a good overview of critical algorithms used in SAP applications.
- Understand the limitations of underlying data infrastructure: Understanding aspects of the underlying database is also critical. This helps you build pragmatic models. As an example, HANA has a 2 billion rows limitation, and hence you may have to partition tables for data sets larger than that. This impacts your model development as well.
- Understand the limitations of tools available: Some PAL algorithms have limits on the number of parameters. This means you will have to pay more attention to feature selection or feature engineering while building models with these algorithms. You can find several examples of these limitations on the SAP help portal and SAP blogs.
25 results
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5 Important Announcements for SAPinsiders
Published: 27/September/2019
Reading time: 3 mins
SAP TechEd took place this week in Las Vegas, unveiling several developments for the SAPinsider community – not the least of which being SAP’s and Microsoft’s joint announcement that Microsoft Azure Blockchain Service and SAP Cloud Platform Blockchain Service will be interoperable. During his main keynote, which outlined SAP’s business technology platform strategy for the…
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Big Data and Machine Learning Tools Flag Fake News and Build Trust and Transparency
Published: 25/June/2018
Reading time: 3 mins
To be successful, companies must operate with complete transparency and gain the trust of employees and customers alike. But with fake news running rampant, it can be difficult to sift through the noise and get to the facts. Membership Required You must be a member to access this content.View Membership LevelsAlready a member? Log in…
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The Future of Finance and Risk Management
Digitization is changing the business environment on a foundational level, and new technologies are providing opportunities to profoundly reimagine finance and risk management. New developments like machine learning and blockchain will pave the way to the truly intelligent enterprise, while those resistant to change will be left behind. In this new landscape, what will the…
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Deploying Machine Learning to Build an Intelligent Enterprise
Published: 18/January/2018
Reading time: 4 mins
An absence of strategy trails only domain expertise as the reason why many companies have yet to adopt artificial intelligence and machine learning. Companies are challenged with how to apply these and other breakthrough technologies for business value. This article details several examples of how organizations can deploy machine learning today, and how SAP S/4HANA…
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Reshaping Business Models for the Digital Era
Published: 06/November/2017
Reading time: 5 mins
Digital technologies are reshaping the world around us, including how companies operate. Mobility, machine learning, Internet of Things (IoT), and other innovations have shifted how companies, customers, partners, and employees interact. Organizations will therefore need to embrace new ways of working and harness their business networks. Learn how SAP plans on keeping the customer at…
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What Are the Prospects for Deep Learning?
Published: 06/November/2017
Reading time: 6 mins
Why, for right now, deep learning is the best universal algorithm.
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How Businesses Can Use Machine Learning to Improve Customer Engagement
Published: 13/September/2017
Reading time: 4 mins
Learn about several ways to incorporate machine learning into your core functions to streamline your overall business.
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Machine Learning and an Enterprise-Worthy AI Platform
Published: 28/August/2017
Reading time: 4 mins
Machine learning capability within an artificial intelligence (AI) platform is where AI is headed.
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Because Seconds, Inches, and Heartbeats Count
Published: 24/August/2017
Reading time: 5 mins
See why machine learning is becoming a game changer across all sports and how it can even address the luck factor.
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Make Machine Learning Work for Your Business
Published: 20/July/2017
Reading time: 9 mins
Andrew Pery, Chief Marketing Officer, Top Image Systems, discusses Machine Learning with Ken Murphy of SAPinsider. Below is a transcript of the conversation. Ken Murphy, SAPinsider: Hi, this is Ken Murphy with SAPinsider. Thank you for listening to this podcast on machine learning and what it means for the SAP customer. Here with me to…
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