Bringing together machine and human intelligence in business applications at enterprise scale (sponsored by SAP)
Adopting AI and machine learning in an enterprise environment can be tricky for a number of reasons. Data scientists and enterprise IT are often in different parts of the organization with different capabilities, tools, and requirements. Managing and integrating the governed data of enterprise IT systems and the comprehensive, but often ungoverned, world of large-scale data lakes, sensors, and unstructured or object store data is often fractured and fragmented across multiple tools and processes. Implementation of ML into production can be delayed by a lack of understanding of how experimental models should be implemented into an enterprise IT environment and managed. Getting rapid access to the latest frameworks and languages supported by the necessary hardware and infrastructure can be a nightmare.
Kevin Poskitt and Andreas Wesselmann dive into the challenges and business value of connecting all this data. The challenges, ultimately, are not only in operationalizing machine learning but also in embedding the results of models into the business process where it can drive tangible business value. You’ll learn how SAP approaches the use of ML internally to enhance its market-leading business applications and the important lessons learned along the way.
What you'll learn
- Learn how to unify fractured and distributed data landscapes to create a foundation for enterprise AI, how to bring together data management and data engineering practices with more traditional data science approaches and why this matters, and how cloud and container-based solutions can help accelerate development efforts and productization and operation of ML models
Kevin Poskitt is a senior director at SAP, where he’s focused on machine learning, data science, and artificial intelligence. He’s responsible for leading SAP’s next-generation projects in unified machine learning. His experience encompasses more than 10 years in various technology companies ranging from small startups to large software vendors, where he’s worked in multiple departments including sales, marketing, finance, and product management. He’s a graduate of the University of Toronto with a specialty in economics and finance, and he holds a bachelor’s of commerce and a diploma in accounts from the University of British Columbia.
Andreas Wesselmann is the senior vice president of SAP products and innovations big data at SAP. He leads the development organization for SAP Data Hub and SAP Data Intelligence. His development leadership roles have included cloud and on-premises integration, access management, and data orchestration topics.
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