In this episode of Let’s Talk Data, host Daniel Dukes of SAP America is joined by Lisa Horwich, founder of Pallas Research and a leading B2B tech qualitative researcher who interviews CISOs, data architects, and security professionals to surface actionable insights for technology companies.

Lisa and Daniel explore how AI is fundamentally reshaping the cybersecurity landscape- from AI-powered phishing and expanded attack surfaces to risks like prompt injection, jailbreaking, and data poisoning. They also tackle the persistent challenge of shadow data and data sprawl, where sensitive information lives outside sanctioned IT infrastructure, making it nearly impossible to classify and protect.

The conversation covers the spectrum of security tools available to organizations, from point solutions to holistic Data Security Posture Management (DSPM) platforms, and closes with key best practices: zero trust, least privileged access, multi-factor authentication, and using AI defensively to combat the very threats it enables.

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Additional Resources:

To find out more about Lisa and security research, visit Pallas Research

To connect with others on the topic, check out the Data Professionals community

SAP Trust Center: Data Protection & Privacy: SAP’s dedicated trust center resource covering data protection policies, privacy safeguards, and the security protocols SAP employs across its cloud ecosystem — directly relevant to the episode’s discussion of data visibility, shadow data, and keeping sensitive organizational data secure.

In this special episode of Let's Talk Cloud ERP, host Jennifer Frank McGrory welcomes IBM Consulting leaders Bill Pietrowski, Devraj Bardhan, and Jim Griffin to the podcast to discuss the latest developments in IBM's enterprise-wide cloud ERP transformation and the business value achieved since their last conversation.

The team shares how IBM has generated more than $4.5 billion in savings through a transformation strategy centered on process simplification, operational efficiency, and SAP modernization. Listeners will hear how IBM continues to advance its clean-core approach across finance, procurement, supply chain, and other critical business functions while creating a more agile and connected enterprise.

A significant portion of the discussion focuses on Human Capital Management and the role of SAP SuccessFactors within IBM's broader business transformation. The guests explore how integrating HR with SAP S/4HANA has improved workforce planning, governance, employee experiences, and manager self-service while reducing HR operating costs and accelerating response times across the organization.

The conversation also highlights IBM's AI-first strategy and how intelligent automation is being applied across HR, procurement, finance, and employee services. With more than 155 AI use cases deployed, IBM shares lessons learned around prioritization, change management, governance, and scaling AI responsibly to drive measurable business outcomes.

Whether you're leading a cloud ERP initiative, modernizing HR operations, or evaluating enterprise AI strategies, this episode provides valuable insights from one of the world's largest transformation programs.

Key Topics of Discussion:

• IBM's Cloud ERP Transformation Journey How IBM has generated more than $4.5 billion in value through process simplification, SAP modernization, clean-core principles, and enterprise-wide operational transformation.

• The Strategic Role of SAP SuccessFactors in Business Transformation Why IBM views Human Capital Management as a critical component of its ERP strategy and how integrating SAP SuccessFactors with SAP S/4HANA improves workforce planning, governance, and employee experiences.

• The "Eliminate, Simplify, Automate" Framework The framework IBM uses to evaluate business processes, reduce complexity, eliminate non-value-added activities, and prepare operations for automation and AI.

• Scaling AI Across the Enterprise Lessons from deploying more than 155 AI use cases across HR, procurement, finance, and supply chain, including how IBM prioritizes opportunities and measures business impact.

• Governance, Change Management, and the Future of Work How IBM balances innovation with governance, security, and data privacy while helping employees and managers adapt to new AI-powered workflows and digital ways of working.

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Connect With Devraj Bardhan

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Connect With Jim Griffin

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Connect With Jennifer Frank McGrory

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Don’t stop here – discover more:

Experience SAP Like Never Before: Cloud ERP Simulation Challenge:

https://events.sap.com/noam-cloud-erp-sim-vew/en_us/home.html

In this episode of the Let’s Talk Data Podcast presented by SAP, host Thierry Audas sits down with Jürgen Faisst and Kristian Rümmelin to explore how the International Business Communication Standards (IBCS) is transforming business reporting, dashboard design, and enterprise analytics.

The discussion highlights why inconsistent dashboards and reporting standards create confusion, slow decision-making, and reduce trust in analytics — especially in the age of AI and generative AI. The guests explain how IBCS establishes a common visual language for business reporting by standardizing charts, tables, colors, variances, and data storytelling conventions.

Listeners will learn how organizations can improve report comprehension, reduce interpretation errors, and accelerate executive decision-making using standardized analytics practices in SAP Analytics Cloud and SAP Business Data Cloud. The episode also explores the newly approved ISO 24896 notation standard for business reporting and what it means for the future of AI-driven analytics.

Practical guidance includes how to launch an IBCS initiative, build executive-ready dashboards, create reporting governance, and scale visualization standards across finance, supply chain, sales, and HR teams.

5 Key Topics of Discussion

• What Is IBCS and Why It Matters Understanding how standardized business reporting improves dashboard clarity, analytics consistency, and faster decision-making.

• The Role of AI in Business Reporting Why AI-generated analytics requires strong visualization standards and semantic consistency to avoid “scaling confusion.”

• SAP Analytics Cloud and IBCS Integration How SAP customers can operationalize IBCS standards using reusable templates, themes, dashboards, and reporting governance.

• ISO 24896 and the Future of Reporting Standards The impact of the new international standard for business reporting notation and its importance for enterprise analytics.

• Best Practices for Dashboard Design and Data Visualization Actionable strategies for CFO dashboards, KPI reporting, variance analysis, semantic consistency, and executive communication.

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Additional Resources:

www.ibcs.com www.ibcs.com/software/sap-analytics-cloud/

In this episode of Let’s Talk Data, host Jose Chicas sits down with Leona Hasani, Product Manager for SAP Business Data Cloud and former data scientist, to explore how modern data platforms are transforming the data science workflow. The conversation dives into the real-world challenges data scientists face—from fragmented data access and lack of business context to time-consuming data preparation and trust issues with datasets.

Leona outlines the end-to-end data science lifecycle, emphasizing that up to 70% of a data scientist’s time is spent on data cleaning and preparation rather than modeling. She explains how SAP Business Data Cloud (BDC), combined with SAP Databricks, streamlines this process by providing ready-to-use, governed data products enriched with business context, definitions, and hierarchies.

A key highlight is the concept of zero-copy data sharing, enabling real-time access to unified SAP and non-SAP data without duplication. This reduces latency, lowers costs, and ensures data consistency across teams. The discussion also explores how integrated tools like MLflow enhance model tracking, governance, and auditability—critical for enterprise and regulated environments.

Through a practical use case—predicting purchase order delays—Leona demonstrates how BDC accelerates time-to-value by eliminating manual data extraction and enabling seamless model deployment back into business systems.

Whether you’re a data scientist, engineer, or analytics leader, this episode offers valuable insights into building scalable, efficient, and business-aligned data workflows in today’s AI-driven landscape.

Key Topics of Discussion:

• SAP Business Data Cloud for Data Scientists Explores how SAP Business Data Cloud (BDC) empowers data scientists with governed, ready-to-use data products that include business context, improving efficiency and accelerating insights.

• Data Science Workflow Optimization & Automation Covers how modern tools reduce manual tasks like data access, cleaning, and preparation—allowing data scientists to focus more on modeling, analysis, and delivering business value.

• SAP Databricks Integration & Machine Learning at Scale Highlights the native integration of SAP Databricks within BDC, enabling scalable machine learning, AI workflows, and seamless access to enterprise SAP and non-SAP data.

• Zero-Copy Data Sharing in Enterprise Data Architecture Explains how zero-copy data sharing allows real-time access to data across systems without duplication, reducing costs, improving performance, and ensuring consistency.

• Data Governance, Data Trust, and Business Context in Analytics Focuses on the importance of trusted, well-defined data with embedded business semantics, enabling accurate analysis, better decision-making, and compliance in enterprise environments.

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Connect With Jose Chicas

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Additional Resources:

• To learn more about SAP Data and Analytics solutions, please check out SAP Business Data Cloud athttps://www.sap.com/products/data-cloud.html • And to engage further, please join our Data Professionals Community on https://community.sap.com/t5/data-professionals/gh-p/data-professionals • To see what's new and upcoming with all SAP solutions, please look at our roadmap explorer on https://pages.community.sap.com/topics/road-map-explorer

What does a day in the life of a data steward really look like? This podcast pulls back the curtain on the people who keep enterprise data trustworthy, usable, and compliant. We will discuss how these data steward navigate through the rhythms of their day—triaging data incidents, curating metadata, negotiating business definitions, enforcing access controls, and coordinating fixes across engineering, analytics, and business teams. We explore both process realities and the best practices in place to ensure trust.

Listeners will hear examples of the types of data sources stewards wrestle with and learn how stewards set and enforce quality rules, measure trust, and assign clear ownership to ensure accountability. From root-cause investigations and remediation workflows to balancing speed with governance, the podcast surfaces recurring pain points and pragmatic solutions, with real-world stories, lessons learned, and actionable tips for improving processes, tooling, and cross-team collaboration.

Key Topics of Discussion:

• The evolving role of data stewards How data stewards act as “data guardians,” ensuring data is accurate, consistent, and usable across the business, and how the role is becoming more strategic over time.

• Cross-functional collaboration and breaking silos The importance of working across finance, IT, and other business units to treat data as a shared enterprise asset rather than something owned by one team.

• Data governance, prioritization, and business value How teams decide which data issues or projects to tackle first based on impact, business value, and dependencies across processes.

• Challenges: stakeholder management, education, and pushback The need to educate others about data, handle difficult conversations, and push back on requests that could harm data quality or long-term outcomes.

• Technology and tooling enabling data stewardship The role of tools like data catalogs, lineage tracking, master data governance (MDG), and unified data platforms in supporting transparency, quality, and scalability.

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Connect With Ralitsa Dakova

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Connect With Grigor Kartev

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Connect With Tina Rosario

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Additional Resources:

To learn more about SAP Data and Analytics solutions, please check out SAP Business Data Cloud at https://www.sap.com/products/data-cloud.html And to engage further, please join our Data Professionals Community on https://community.sap.com/t5/data-professionals/gh-p/data-professionals

This episode of Let’s Talk Cloud ERP features Jennifer Frank McGrory in conversation with Lindsay Callaghan, Director of Business Systems at Rytec Corporation, a North American leader in high-speed, high-performance doors. The discussion explores how Rytec's ERP transformation journey has evolved within a long-standing SAP environment and how new business realities are shaping its future.

Rytec has operated in a stable SAP system for over a decade, supported by a lean team and strengthened by a recent smart factory manufacturing transformation. As the company began planning its move toward SAP S/4HANA, it was acquired by Nucor in 2024—an event that increased the urgency for process visibility and strategic alignment.

A major turning point was the use of SAP Signavio. Within 24 hours, Lindsay’s team gained clear, data-driven insight into real business processes, data gaps, and system flows. This shifted conversations away from opinion-based workshops and toward visual, fact-based discussions. As a result, meetings became more focused, resistance rooted in past ERP project fatigue decreased, and the organization could better determine which legacy processes should be improved or retired.

Looking ahead, 2026 is set to be a pivotal year, with Rytec evaluating RISE with SAP and preparing for S/4HANA—emphasizing continuous improvement, strong partnerships, and process intelligence as keys to long-term success.

Key Topics of Discussion:

• Fact-based transformation beats assumptions – Real process data from SAP Signavio replaced guesswork and opinion-driven workshops.

• A stable ERP foundation enables smarter modernization – Rytec’s long-running SAP system allowed for strategic planning toward S/4HANA rather than reactive change.

• Process visibility reduces resistance to change – Visual insights help business users understand impacts, shortening meetings and easing “ERP fatigue.”

• Transformation is a chance to eliminate legacy baggage – Data helps identify which processes add value and which are just being carried forward out of habit.

• Strong partners plus modern tools accelerate success – Combining SAP best practices, experienced partners, and process intelligence supports better decisions and continuous improvement.

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Connect With Jennifer Frank McGrory

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Don’t stop here – discover more:

Experience SAP Like Never Before: Cloud ERP Simulation Challenge:

https://events.sap.com/noam-cloud-erp-sim-vew/en_us/home.html

In this episode of the SAP Let’s Talk Data podcast, SAP’s Lauren Wong sits down with Robin Bloor and Daniel Howard from Bloor Research to discuss findings from their recent study on SAP HANA Cloud and its role as a modern, in-memory cloud database for developers.

Drawing from interviews with SAP customers across industries, the conversation uncovers real-world insights into how organizations are using SAP HANA Cloud to modernize applications, scale efficiently, and bring intelligence closer to their data. Robin and Daniel share developer perspectives on the platform’s most valued capabilities and discuss how these features are shaping productivity and performance outcomes for teams of all sizes.

Together, they explore key trends revealed through the study, highlight the measurable benefits developers are achieving, and share their broader perspective on SAP HANA Cloud’s versatility as a foundation for building intelligent applications that adapt, learn, and innovate in real time.

Key Topics of Discussion:

• About Bloor Research – An introduction to Bloor as a long-standing technology analyst firm, with Robin Bloor and Daniel Howard sharing their background in data, analytics, and database research.

• Inside the SAP HANA Cloud Study – A breakdown of the study’s goals, methodology, and findings, based on interviews with customers across automotive, financial services, and green energy sectors.

• Customer Use Cases and Outcomes – How organizations are adopting SAP HANA Cloud to support high-performance analytics, scalability, and modernization, including a financial services example using it for workload forecasting and optimization.

• Key Capabilities of SAP HANA Cloud – A look at the platform’s standout performance, multi-model support, reduced need for tuning, and the ability for small teams to manage large-scale environments efficiently.

• AI Readiness and Future Innovation – Insights into how customers are approaching AI, the role of vector and RAG capabilities, and how SAP HANA Cloud is positioned to support the next generation of intelligent data-driven applications.

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Connect With Robin Bloor

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Connect With Daniel Howard

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Connect With Lauren Wong

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Don’t stop here – discover more:

Read the InBrief report from Bloor Research for their perspective on SAP HANA Cloud for SAP and non-SAP customers https://bit.ly/4odk28k

Learn more about Bloor Research: https://bit.ly/3LQGozb

Join the SAP Community and get involved with other developers: https://bit.ly/4abD2Rc

Learn more about SAP HANA Cloud: https://bit.ly/4oTy3Jv\

Don’t have time to read The Top Reason Why Organization Choose SAP HANA Cloud? Well you’re in luck! Step into the future of business innovation with SAP HANA Cloud! In this AI generated episode of The Let’s Talk Data Podcast, we unveil how SAP’s in-memory cloud database is revolutionizing the way organizations harness their data. This isn’t just another database—it’s a game-changing platform that unifies structured and unstructured data, powers AI workloads, and delivers real-time insights, all while slashing complexity and simplifying infrastructure.

You’ll hear the 10 powerful reasons why leading businesses are making the switch: from multi-model capabilities that eliminate juggling multiple databases, to true multi-cloud freedom across AWS, Azure, Google Cloud, and beyond. Discover how intelligent data tiering saves costs without sacrificing performance, and how built-in engines for vectors, graphs, and spatial data supercharge the development of smarter applications.

But that’s not all—SAP HANA Cloud also delivers native AI capabilities, elastic scalability, seamless data integration, enterprise-grade security, and even AI-powered automation that transforms database administration into a strategic advantage. And for developers? The SAP Build ecosystem brings no-code, low-code, and pro-code development together, accelerating innovation at every level.

Don’t miss this episode! Find out how SAP HANA Cloud can help your business move faster, modernize infrastructure, and unlock the full power of your data today.

Key Topics of Discussion:

• Multi-Model Data Management – Unifying relational, JSON, spatial, graph, and vector data in one platform for faster insights and simplified applications.

• Cloud Flexibility & Scalability – Multi-cloud deployment across AWS, Azure, Google Cloud, and more, with elastic scaling to handle unpredictable workloads.

• Cost-Optimized Storage – Intelligent data tiering that balances hot, warm, and cold storage while keeping access seamless for users.

• AI at the Core – Native vector support, semantic search, and retrieval-augmented generation to power smarter business applications.

• Developer & DBA Empowerment – SAP Build’s no-code to pro-code ecosystem plus AI-powered DBA tools that reduce manual work and accelerate innovation.

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Additional Resources:

Read the brochure, Top 10 reasons organizations chose SAP HANA Cloud: http://bit.ly/4pqNOs4

What’s the potential value of SAP HANA Cloud for your organization? Complete this short assessment: http://bit.ly/46oekJO

Learn more about SAP HANA Cloud: www.sap.com/hana