Let’s Talk Data: Business Technology Podcast | SAP Let’s Talk Data
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- Technologie
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Exploring SAP’s business technology platform and success with our revolutionary data tech.
Discover key solutions and technologies that power SAP’s Business Technology Platform by listening in on conversations with partners, developers, and innovators across the SAP ecosystem.
Get real-world stories and stats on topics like data governance, data integration and orchestration, machine learning, all things database, enterprise architecture, and more.
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Is it Data Product or Data as a Product?
Listen as SAP data experts, Gebhard Roos, Maria Villar, and Tina Rosario discuss the concepts that fall under the umbrella of “Data as a Product.” They will converse on the nuances and value of various approaches to data sharing, including democratization, monetization, and data marketplaces, with both inside and outside views.
Host: Corrie Birkeness
Speakers:
Gebhard Roos – Product Manager for SAP Datasphere Data Marketplace
Maria Villar – Head of North America Data Strategy and Transformation
Tina Rosario – Chief Data Officer, SAP Europe
Important Links:
SAP solutions for Data & Analytics: https://bit.ly/3IDy9kS
Blog on SAP Datasphere Marketplace: https://bit.ly/4d39Fzq
SAP Business Network: https://bit.ly/3JmF56p
SAP Sustainability Data Exchange: https://bit.ly/3Q3GeU0
Key Topics of Discussion:
Distinguishing Data Product vs. Data as a Product: Exploring the operational model and overarching principles that define these concepts.
Characteristics of Data Products: Delving into the transparency, alignment with consumer needs, and governance constraints that distinguish data products.
Role of Data Marketplaces: Understanding the significance of data marketplaces in facilitating internal and external data exchange, monetization, and collaboration.
Models of Data Sharing: Exploring various models of data sharing, including public domain data, commercial data sharing, and indirect monetization, both internally and externally.
Organizational Challenges: Addressing the organizational buy-in, education, and mindset shift required to prioritize consumer needs and navigate the complexities of data product implementation.
Technical Challenges: Discussing the technical considerations and architectural models necessary for effective data product creation and management.
Transparency and Trustworthiness: Highlighting the importance of transparency, trustworthiness, and consumer-centric design in building successful data products and marketplaces.
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SAP S/4HANA Cloud Extensions with SAP Build Best Practices: An Expert Roundtable
SAP experts discuss SAP S/4HANA extensions best practices and SAP Build Code.
Topics discussed:
Introduction to S/4HANA Extensions Best Practices
What is Clean Core
Extensibility Options and Best Practices for S/4HANA Cloud Private Edition customers
Advantages and disadvantages of on-stack vs using BTP tools
Extensibility changes for S/4HANA over the past few years.
Best practices for UI-focused applications and mobile services with SAP S/4HANA
SAP Build Code for SAP S/4HANA developers
What is AI bringing to the table for S/4HANA implementers and developers
Build Code scenarios for developers who are using Business Application Studio right now
Build Code roadmap plans to help developers work more easily with S/4HANA
How S/4HANA developers can improve governance
Pragmatic recommendations for the type of extensions developers should create
Speakers:
Vanessa Micelli-Schmidt, Chief Product Manager, SAP Build
Felix Wente, Chief Development Architect, SAP S/4HANA
Mark Wright, Director, Marketing and Solutions, SAP Build Code
Host: Terry Penner, Marketing and Solutions, SAP BTP
Call to Action:
Explore SAP Build Code at SAP.com/Build-Code
Learn more about SAP BTP for S/4HANA and RISE at sap.com/btp-for-s4hana -
Enterprise Automation: SAP and Third-Party Integration and Connectivity | feat. AG Consultancy
Hear from SAP Gold partner, AG Consultancy and Apps, on their continued delivery of successful customer engagements and technical and commercial expertise in the enterprise application development and automation space. Discover the community RPA bots created by AG and how Enterprise Automation from SAP can elevate your existing app and automation investments.
Speakers:
Nick Champion - Co-Founder & Director, AG Consultancy and Apps
Rahul Kumar - Technical Solution Lead, AG Consultancy and Apps
John Luu - Product Marketing Manager, SAP Build Process Automation
Additional Resources:
Learn more about Enterprise Automation
Check out AG's SAP Build implementation and support services
Browse the partner-built community bots
Topics Include:
Overview of AG Consultancy & Apps
Customer Trends and Challenges
The Role of SAP Build
Taking Automation to the Next Level
Third-Party Connectivity
Development of Automation Bots
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Thriving with A Business Outcome-Driven Data Strategy
While companies know that managing their data is essential, it can also be tough – and technology is not necessarily the hardest part, it is the people and the process. Join, Maria Villar, Head of North America Data Strategy and Transformation at SAP, and Vinny Maurici, Vice President of Data Engineering at Object Edge as they discuss current challenges companies experience when developing a data strategy and an approach to developing one that is outcome-driven.
Host: Corrie Birkeness
Speakers:
Maria Villar – Head of North America Data Strategy and Transformation
Vinny Maurici - Vice President of Data Engineering at Object Edge
Additional Resources:
SAP Enterprise Data Strategy Master Class: https://bit.ly/4abjwB1
SAP Enterprise Data Strategy Workbook: https://bit.ly/4ausB8v
SAP solutions for Data & Analytics: https://bit.ly/3IDy9kS
Discussion Highlights:
Overview of Data Strategy Challenges
Business Outcome Focus in Data Strategy
Foundations of Master Data Management (MDM) and Data Governance
Agile Data Governance and Leadership
Executive Support and Organizational Capabilities
The importance of aligning data strategy with business outcomes
Modernizing MDM and data governance practices
Securing executive support for effective data transformation -
2023 Trends in Master Data Management
Hear from Andy Hayler, Practice Lead – Data as an Asset at Bloor Research, and Markus Kuppe, VP & Chief Product Owner for SAP Master Data Governance, and Corrie Birkeness, Senior Director Master Data Product & Solution Marketing at SAP, as they discuss various master data management (MDM) market trends. They will discuss what is happening relative to automation, AI as well as approaches to more flexible, modular MDM deployments and a business data fabric. They will discuss what the trends are and why they are important in upping your game in MDM to drive increased business value.
Speakers:
Andy Hayler, Practice Leader - Data as an Asset at Bloor ResearchMarkus Kuppe, VP & Chief Product Owner for SAP Master Data GovernanceCorrie Birkeness, Senior Director Master Data Product & Solution Marketing at SAP
Additional Resources:
Learn more about SAP Master Data Governance and Bloor Research by visiting:SAP MDG Product Page: https://bit.ly/3E2r8Xb
SAP MDG Community: https://community.sap.com/topics/master-data-governanceBloor Research: https://bit.ly/3RyhZNP
Bloor InBrief on SAP Master Data Governance: https://bit.ly/3Rx3iun
Bloor Article on SAP Master Data Governance: https://bit.ly/3GS9kAT
Benefits of Federated Master Data Governance (SAP blog): https://bit.ly/47opgWB
Key Points:
Master Data Management Market Update:
Bloor Research published an MDM market update, emphasizing the merging of MDM and data management platforms with trends in data governance, quality, and integration.
The shift from on-premise to cloud or hybrid environments requires MDM platforms to be deployable in the cloud.
Automation and AI in MDM:
Automation in MDM brings efficiency and quality, leveraging technology and AI.
SAP MDG applies AI, machine learning, and rules-based approaches to enhance data quality, identify implicit data rules, and automate data population.
Federation of Master Data Governance:
Federated MDM model allows distributed management of data, aligning with organizational structures, and ensuring local understanding.
SAP MDG supports federation through multiple instances, enabling both local and global benefits in master data management.
Role of MDM in Data Fabric and Data Mesh:
MDM plays a crucial role in complementing concepts like data fabric and data mesh.
Data fabric focuses on connecting enterprise data without physically moving it, with MDM providing a foundation for high-quality trusted master data.
Data mesh, a domain-specific approach, aligns well with MDM, especially when dealing with key data domains.
Conclusion:
Intelligence, modularization, modernization, and data fabric are key trends in MDM.
Encourages listeners to access additional resources and share their insights on MDM trends in their organizations. -
Bridging the Gap: Connecting Modern Integration to Business Value
Organizations are on a quest to a modern technology stack. This includes integration, which is the glue that brings it all together. Yet, selling the value of integration can get technical too quickly and hard to articulate. Understanding the business and technical benefits of integration and how they translate into business value is key to building the case for investment in this technology and in a broader digital platform.In this episode, Shari Lava, Research Director at IDC, discusses with Emily Mui, Sr. Director, Solution Marketing at SAP, the IT and business value of integration, and how you can tie it to business objectives and measure the business impact of integration.
Speakers:
Shari Lava - Research Director, IDC
Emily Mui - Sr. Director, Product Marketing Lead For SAP Integration Suite
CTA's:
Modernize Your Integration Landscape Virtual Summit https://bit.ly/3S8UUmM
The Integration Scoop Podcast
Introduction:
Special edition presented by SAP and Let's Talk Data podcast.
Focus on game-changing technology and strategies for innovation through business application and process integration.
Guest Speaker: Sheri Lava from IDC:
Sheri leads marketing strategy for SAP's iPASS solution (SAP Integration Suite).
Sheri is the Research Director of Automation at IDC, covering AI, automation, API management, and integration markets.
Integration Market Overview:
Integration market reached $8.5 billion in 2022, expected to reach $18 billion by 2027.
Shift from on-premise to cloud-delivered solutions.
Importance of integration in becoming a digital business with connected, data-driven systems.
Why Integration Delivers Strategic Business Value:
Connectivity is the bedrock for building a strong foundation for digital businesses.
Importance of having data driving decisions for better customer solutions, service offerings, and decision-making.
Integration crucial for process automation and resilience.
Challenges and Growth:
Integration market growth driven by the need for data connectivity in digital businesses.
Transition from on-premise to cloud solutions.
Overcoming challenges in translating technical benefits into business value.
Business Challenges in Implementing Integration:
Change management for developers adapting to new ways of working.
Historical concerns about product suitability.
Importance of defining success uniformly across the organization.
Business Outcomes and Objectives:
Translation of technical benefits to business value.
Examples include lower operating costs leading to greater efficiency, improved customer satisfaction, and increased revenue.
Focus on efficiency, reducing integration sprawl, and achieving a 360-degree view of the customer.
Low-Code and Measurement of Success:
Evolution of low-code tools and their impact on traditional metrics.
Emphasis on business outcomes and value instead of lines of code written.
Generative AI enhancing low-code tools and improving efficiency.
Integration for Automation:
Integration as a key player in holistic automation strategies.
Addressing challenges of integrating processes with business partners.
Ensuring the integration stack is strong and ready for future automation initiatives.
Trends in Integration:
Significance of AI in integration solutions, enhancing capabilities like error detection and prediction.
Importance of a bi-directional relationship between AI and integration.
Caution against investing in AI without addressing integration challenges first.