The Value of Automation in Master Data Management (MDM)

Let’s Talk Data: Business Technology Podcast | SAP

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Expert mode marketing technology, AI, and CX insights from top brands and Martech platforms fill every episode, focusing on what leaders need to know to build customer lifetime value and long-term business value. The Agile Brand with Greg Kihlström® features executives and thought leaders from top brands and platforms discussing the industry's trends, like first-party data strategies, artificial intelligence, consumer data privacy, omnichannel customer experience, and more. The Agile Brand is hosted by Greg Kihlström, advisor and consultant to leading brands, speaker, entrepreneur, and best-selling author. It provides a fresh perspective on the continually evolving dynamic between brands and the audiences they serve.

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In this episode of the SAP Let's Talk Data podcast, host Corrie Birkeness is joined by experts Andreas Seifried (Product Manager at SAP) and Kai Hüner (CTO of CDQ) as they discuss the critical role of automation and data quality in master data management (MDM). They dive into the value of automation in master data management (MDM) and the critical role of high-quality, trusted data in enabling reliable and efficient automation. They explore the challenges of manual data management, such as errors, inefficiencies, and delays, and highlights how automation can improve data accuracy, save costs, and support business growth.

Andreas and Kai also explain how their collaboration integrates CDQ's trusted data services with SAP's Master Data Governance (MDG) solution. They share examples of companies achieving faster processes, reduced compliance risks, and enhanced scalability through automation.

Key Topics of Discussion:

The Importance of Trusted, High-Quality Data - Trusted data is essential for reliable automation, compliance, and AI initiatives. The concept of "trusted data" emphasizes accuracy, traceability, and verified sources like tax authorities or trade registers.
Challenges of Manual Master Data Management (MDM) - Manual MDM is labor-intensive, error-prone, and causes inefficiencies, delays, and bottlenecks. Mistakes in master data lead to operational issues like delayed logistics, compliance failures, and rework costs.

Benefits of Automation in MDM - Automation reduces manual effort, errors, and compliance risks while improving speed and scalability. Examples highlight significant cost and time savings, such as reducing supplier onboarding from 50 minutes to 1 minute.

Collaboration Between SAP and CDQ - SAP MDG integrates with CDQ's trusted data services to enable seamless data lookup, enrichment, and validation. Simplified setup processes, like value mapping and trusted data sourcing, streamline automation implementation.

Features Supporting Automation in SAP MDG - Tools like derivation rules, rule mining, and AI-powered features enhance data accuracy and governance. These features help organizations automate repetitive tasks, reduce errors, and enable growth.

Subscribe to The Let’s Talk Data Podcast

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Connect With Corrie Birkeness

Connect With Andreas Seifried

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Additional Resources:

CDQ Business Value Study: https://hubs.la/Q02YwW-_0

Enrichment of Business Partner Master Data using CDQ blog: https://community.sap.com/t5/technology-blogs-by-sap/mass-enrichment-of-business-partners-with-tax-and-id-numbers-found-using/ba-p/13915206

SAP Master Data Governance product page: www.sap.com/mdg

CDQ on the SAP Store: https://store.sap.com/dcp/en/product/display-2001000790_live_v1

100 פרקים

#Tech #SAP HANA #Lets Talk Data

The Value of Automation in Master Data Management (MDM)

Let’s Talk Data: Business Technology Podcast | SAP

published לפני שנה

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MP3•בית הפרקים

Key Topics of Discussion:

The Importance of Trusted, High-Quality Data - Trusted data is essential for reliable automation, compliance, and AI initiatives. The concept of "trusted data" emphasizes accuracy, traceability, and verified sources like tax authorities or trade registers.
Challenges of Manual Master Data Management (MDM) - Manual MDM is labor-intensive, error-prone, and causes inefficiencies, delays, and bottlenecks. Mistakes in master data lead to operational issues like delayed logistics, compliance failures, and rework costs.

Benefits of Automation in MDM - Automation reduces manual effort, errors, and compliance risks while improving speed and scalability. Examples highlight significant cost and time savings, such as reducing supplier onboarding from 50 minutes to 1 minute.

Collaboration Between SAP and CDQ - SAP MDG integrates with CDQ's trusted data services to enable seamless data lookup, enrichment, and validation. Simplified setup processes, like value mapping and trusted data sourcing, streamline automation implementation.

Features Supporting Automation in SAP MDG - Tools like derivation rules, rule mining, and AI-powered features enhance data accuracy and governance. These features help organizations automate repetitive tasks, reduce errors, and enable growth.

Subscribe to The Let’s Talk Data Podcast

Apple Podcasts

Spotify

YouTube

Connect With Corrie Birkeness

Connect With Andreas Seifried

Connect With Kia Hüner

Additional Resources:

CDQ Business Value Study: https://hubs.la/Q02YwW-_0

Enrichment of Business Partner Master Data using CDQ blog: https://community.sap.com/t5/technology-blogs-by-sap/mass-enrichment-of-business-partners-with-tax-and-id-numbers-found-using/ba-p/13915206

SAP Master Data Governance product page: www.sap.com/mdg

CDQ on the SAP Store: https://store.sap.com/dcp/en/product/display-2001000790_live_v1

100 פרקים

#Tech #SAP HANA #Lets Talk Data

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Let’s Talk Data: Business Technology Podcast | SAP

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43:37

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Let’s Talk Data: Business Technology Podcast | SAP

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לפני 51 weeks27:05

27:05

A clean core helps customers keep up with the competition and use SAP S/4HANA standard features whenever possible and provides an easier way to keep getting updates without breaking business-specific functionality. During this podcast, Sue Waite, Senior Director for North American Center of Excellence, Business Technology Platform solutions at SAP, and David Sentance, Associate Partner and Head of Data & Analytics at Camelot Management Consultants, will discuss how enterprise data management practices help ensure a clean core as well as mitigate risk to your business transformation initiatives. Speakers: Sue Waite, Senior Director for North American Center of Excellence, Business Technology Platform solutions at SAP David Sentance, Associate Partner and Head of Data & Analytics at Camelot Management Consultants Host: Corrie Birkeness Additional Resources: Building an Information Backbone for the Digital Enterprise: https://bit.ly/3wsYjVg Accelerate Your Move to the Cloud with Trusted Data: https://bit.ly/4bWD7Gj The Business Case for Clean Master Data: https://bit.ly/44LiZnR SAP solutions for Data & Analytics: https://bit.ly/3IDy9kS SAP solutions for Data Management: https://bit.ly/3UXbRBD The Data Tower Setup in SAP S/4HANA Initiatives (Camelot ITLab): https://bit.ly/3WBxokG Your Fast Forward S/4HANA Data Transformation (Camelot ITLab): https://bit.ly/4bjuPYO Data Quality Health Check (Camelot ITLab): https://bit.ly/44J9cig Data Analyzer (Camelot ITLab): https://bit.ly/3V2NnGb Key Topics of Discussion: Importance of a Clean Core: Discuss the significance of establishing and maintaining a clean core in data management, especially in the context of transitioning from classic ERP systems to cloud-based solutions like S/4HANA. Emphasize the benefits of having a clean core, such as improved efficiency, accuracy, and adaptability. Dimensions of a Clean Core: Break down the five core dimensions of a clean core, including data cleanliness, composable approach, extensions, integration, and operational efficiency. Explain how each dimension contributes to the overall cleanliness and effectiveness of the core ERP system. First Steps in Moving to the Cloud: Explore the initial steps organizations should take when transitioning to the cloud, focusing on foundational work related to data management and governance. Highlight the importance of assessing existing data challenges and developing a strategy for data migration and quality improvement. Outcome-Driven Data Strategy: Stress the significance of adopting an outcome-driven data strategy before embarking on migration projects. Provide examples of business objectives, such as compliance, customer experience enhancement, or process optimization, and illustrate how these objectives inform the data strategy. Source Data Assessments and Data Quality Improvements: Discuss the importance of conducting source data assessments to identify gaps, inconsistencies, and data quality issues. Explain how these assessments serve as a foundation for data quality improvements and help organizations avoid pitfalls during migration and implementation. Techniques for Keeping Data Clean: Explore techniques and tools for maintaining data cleanliness, including accurate data capture, enrichment, and ongoing governance. Highlight solutions like SAP Master Data Governance (MDG) and data quality management micro-services for ensuring data integrity and accuracy. Change Management in Master Data Governance: Address the organizational change management aspect of implementing master data governance solutions. Discuss the need for training, stakeholder engagement, and establishing data governance councils and stewardship roles to ensure successful adoption and maintenance of clean data practices.…

Let’s Talk Data: Business Technology Podcast | SAP

1
Skyworks: Revolutionizing Connectivity with RISE with SAP 20:50

לפני 52 weeks20:50

20:50

Guest host, Erik Lossbroek, is joined by Satya Jayadev, CIO of Skyworks, who shares insights into Skyworks transformation journey and adoption of Rise with SAP. Satya discusses challenges, emphasizing organizational change management and governance. Satya explores the partnership between Skyworks, SAP, and Deloitte and envisions the post-go-live roadmap, focusing on efficiencies and innovation. Don't miss this episode for valuable insights into the intersection of technology and business in the semiconductor industry. Speakers: Satya Jayadev - Skyworks, Vice President and CIO Erik Lossbroek - Regional Vice President, SAP Key Topics of Discussion: Transformation Strategy: Discussing Skyworks' approach to transformation, including foundational aspects and the pursuit of innovation. SAP S/4HANA Cloud Adoption: Exploring why Skyworks chose SAP S/4HANA Cloud and its benefits in driving digital transformation. Organizational Change Management: Emphasizing the importance of managing change and involving stakeholders in the transformation journey. Governance and Collaboration: Outlining Skyworks' governance structure and the role of key partnerships, like SAP and Deloitte. Technology and Connectivity: Understanding how Skyworks uses technology to connect people and places across various markets. Post-Go-Live Roadmap: Discussing Skyworks' plans for driving efficiencies and continuous innovation after implementing SAP S/4HANA Cloud. Lessons Learned and Best Practices: Sharing insights and key takeaways from Skyworks' transformation journey, including the challenges faced and how they were overcome.…

Let’s Talk Data: Business Technology Podcast | SAP

1
SAP S/4HANA Data Migration and Master Data Management Best Practices with SAP BTP 39:05

לפני 1 year39:05

39:05

SAP experts discuss best practices and practical approaches for migrating data and master data management with SAP S/4HANA and SAP Business Technology Platform. SAP experts discuss best practices and practical approaches for migrating data and master data management with SAP S/4HANA and SAP Business Technology Platform. Speakers: Randy Connelly - Global Data Governance Practice Lead, Syniti Bill Todd - Principal Solutions Advisor, SAP Terry Penner - Marketing and Solutions, SAP BTP Part 1: Data Migration Key challenges Best practices for system conversion Best practices for selective data transition Best practices for new implementations Data migration tool options Part 2: Master Data Management Challenges and priorities Efficiently working with master data Part 3: Clean Core Data management and clean core Getting started with data migration to S/4HANA Learn more at: SAP BTP for RISE with SAP RISE with SAP SAP S/4HANA Extensions and Clean Core Best Practices SAP Advanced Data Migration and Management Tool SAP Master Data Governance…

Let’s Talk Data: Business Technology Podcast | SAP

1
Is it Data Product or Data as a Product? 31:18

לפני 1 year31:18

31:18

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.…

Let’s Talk Data: Business Technology Podcast | SAP

1
SAP S/4HANA Cloud Extensions with SAP Build Best Practices: An Expert Roundtable 32:50

לפני 1 year32:50

32:50

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…

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