What happens when a company with 100,000 employees needs to turn massive amounts of data into something everyone can actually use?

In this episode of Let’s Talk Data, Bradley Vaslik sits down with Oliver Huth, Head of Platform and Engineering at SAP, to unpack SAP’s journey from a centralized data warehouse and thousands of dashboards to a scalable data product economy.

Oliver shares the real-world challenges behind SAP’s transformation—including data silos, changing business demands, governance, and the struggle to give employees faster access to trusted data.

The conversation explores how SAP Business Data Cloud, SAP Datasphere, and Databricks are helping SAP build a more flexible and reusable data foundation—and why data products are becoming increasingly important as AI changes the way businesses work.

But there’s a bigger story: AI is only as powerful as the data behind it.

Oliver explains why trusted enterprise data is becoming the critical foundation for analytics, applications, AI, and intelligent agents—and why measuring data product adoption and reuse may be one of the most important metrics for modern data teams.

A practical conversation about data strategy, governance, AI, and what it takes to make enterprise data truly work at scale.

5 Key Topics of Discussion:

• The Evolution from Data Warehouses to Data Products SAP’s shift from a centralized data warehouse and dashboard model to a scalable, self-service data product approach.

• Building Trust and Governance in Data How data ownership, quality, governance, lineage, and adoption help organizations create trusted data that can be reused across teams.

• How SAP Defines and Manages Data Products The role of data product owners, domains, output ports, primary and derived data products, and the processes used to build and consume them.

• Business Data Cloud and the Modern Data Architecture How SAP Business Data Cloud, Datasphere, Databricks, and existing BW investments work together to support SAP’s data product strategy.

• Data Products as the Foundation for AI Why trusted, governed enterprise data is becoming increasingly important for analytics, applications, AI, and agent-based use cases—and why adoption and reuse are critical measures of success.

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Additional Resources:

• To learn more about SAP Data and AI 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

What does it really take to become a data-driven organization? In this episode of Let's Talk Data, host Corrie Birkeness is joined by data strategy expert Shelly McQuigg and SAP Product Marketing Director Kara Reed for a practical discussion on building a successful data strategy that delivers measurable business value. Together, they explore why effective data strategies must begin with business outcomes—not technology—and how trusted, governed data is the foundation for analytics and AI success.

Shelly and Kara share lessons from decades of experience leading enterprise data initiatives, including standardizing global KPIs, establishing executive sponsorship, and creating governance models that balance control with business agility. They explain why data professionals need both technical expertise and business knowledge to influence organizational change and drive adoption.

The conversation also examines how modern data architectures, including data fabric, enable organizations to create a single definition of the truth without physically centralizing data. Finally, the discussion turns to AI, highlighting why data quality, governance, and trusted information have become more critical than ever before. Whether you're a data leader, architect, analyst, or executive, this episode provides actionable guidance for creating a scalable data strategy that supports business growth, operational efficiency, and trusted AI initiatives.

Key Topics of Discussion:

• Building a business-first data strategy focused on corporate KPIs, measurable outcomes, and business value.

• The importance of data governance in creating trusted, standardized, and high-quality enterprise data.

• The evolving role of data professionals as business partners, strategists, and organizational influencers.

• Modern data architecture and data fabric, enabling a single definition of the truth across distributed systems.

• Preparing data for AI, emphasizing why governance, quality, and trusted data are essential for successful AI adoption.

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Additional Resources:

To learn more about SAP Data and AI solutions, please check out SAP Business Data Cloud at https://www.sap.com/products/data-cloud.html

To engage further, please join our Data Professionals Community on https://community.sap.com/t5/data-professionals/gh-p/data-professionals

In this episode of Let’s Talk Data, host Venkata Giduthuri sits down with Justin Lynch, SAP Data Architect Program - Americas Regional Lead, to discuss the modernization journey with SAP Business Data Cloud for on-premises SAP BW, SAP BPC, SAP BusinessObjects, and SAP HANA systems to embark on the Autonomous Enterprise journey. The conversation specifically focuses on what it takes to modernize SAP BW with SAP Business Data Cloud.

Justin outlines the importance of the modernization journey and how it differs from migration. The discussion highlights options for modernizing SAP BW to take advantage of the latest AI innovations in SAP Business Data Cloud.

The key highlight is the process of readiness assessment, getting into the details of how the information is collected and analyzed, taking into consideration various complexities built by the customers over the years.

Finally, Justin shares the benefits customers gain from the latest innovations in SAP Business Data Cloud after the migration, such as data products and knowledge graphs, which are the foundational elements of an autonomous enterprise platform.

Whether you are a BW engineer, NetWeaver administrator, enterprise architect, data architect, or platform engineer, this episode offers valuable insights into how to choose the best path for modernization with SAP Business Data Cloud to build for AI-driven architectures.

Key Topics of Discussion:

• Why Modernization with SAP Business Data Cloud: Explore why organizations are modernizing SAP BW and moving toward a more cloud-ready, AI-enabled data landscape.
• Options to Modernize SAP BW: Compare the lift-and-shift and greenfield approaches for moving SAP BW to Business Data Cloud.
• Getting Started with SAP BW Modernization: Learn how organizations can assess their current environment and determine the right modernization path.
• Readiness Assessment Insights: Understand what the SAP BDC assessment evaluates and how its findings help guide modernization decisions.
• Innovation Benefits with SAP Business Data Cloud: Discover how BDC enables new AI, data product, knowledge graph, and analytics capabilities.

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Connect With Venkata Giduthuri

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Links to CTA:

https://www.sap.com/products/data-cloud/sap-bw-migration.html

https://www.sap.com/products/data-cloud/sap-migration-assessment.html

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 Bill Piotrowski

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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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Connect With Thierry Audas

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 Leona Hasani

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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