Is it Data Product or Data as a Product?
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 Pr…
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April 17, 2024

Is it Data Product or Data as a Product?

Is it Data Product or Data as a Product?
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Let’s Talk Data: Business Technology Podcast | SAP

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.