Practice Free C_BCSBS_2502 Exam Online Questions
Question #11
What are some key differentiators of SAP Business AI? Note: There are 3 correct answers to this question.
- A . Ecosystem of Innovation
- B . Large foundation models
- C . Embedded AI
- D . Predictive Analytics
- E . AI Foundation
Correct Answer: A, C, E
A, C, E
Explanation:
The question asks for the key differentiators of SAP Business AI, which is a suite of AI capabilities integrated into SAP Business Suite to enhance business processes, decision-making, and automation. According to official SAP documentation and the provided search results, the key differentiators of SAP Business AI include its ecosystem of innovation, embedded AI, and AI Foundation. These align with Options A, C, and E, making them the correct answers.
Explanation of Correct Answers
Option A: Ecosystem of Innovation
This is correct because SAP Business AI is distinguished by its robust ecosystem of innovation, which includes partnerships with leading technology providers (e.g., NVIDIA, Google Cloud, Microsoft, AWS, Cohere) and implementation partners to deliver cutting-edge AI solutions. This ecosystem fosters collaborative innovation, enabling SAP Business AI to integrate advanced AI models, ensure interoperability, and address customer-specific needs through a network of expertise.
The SAP Business AI overview on www.sap.com states:
“SAP’s AI strategy includes a robust partner ecosystem with synergistic collaboration, partnering with industry leaders like NVIDIA, Google Cloud, and Cohere to deliver interoperable AI agents and scalable solutions. This ecosystem enables SAP Business AI to address unique customer challenges through combined expertise and innovation.” sap.com
Additionally, the SAP News Center emphasizes the role of partners in driving innovation:
“A key element of SAP’s AI strategy is leveraging partners’ expertise. Partners develop innovative AI solutions and extensions, enhancing the SAP portfolio with customer-specific use cases built on SAP BTP.” news.sap.com
This ecosystem differentiates SAP Business AI by combining SAP’s deep business process knowledge with external AI advancements, ensuring flexibility and rapid adoption of new technologies.
Option C: Embedded AI
This is correct because SAP Business AI is uniquely differentiated by its embedded AI capabilities, which are seamlessly integrated into SAP applications (e.g., SAP S/4HANA, SAP SuccessFactors, SAP Analytics Cloud) to enhance business processes directly within workflows. Unlike standalone AI solutions, embedded AI automates tasks, provides context-aware insights, and optimizes processes without requiring users to leave their SAP environment. The Exploring SAP’s AI Strategy lesson on learning.sap.com states:
“Embedded AI Capabilities enhance SAP products by automating tasks, analyzing data, improving user experience, optimizing processes, fostering innovation, and ensuring seamless integration. Joule, a generative AI copilot, is embedded within SAP applications, offering generative AI, predictive analytics, process automation, and context-aware recommendations.” learning.sap.com
For example, SAP S/4HANA uses embedded AI for predictive maintenance and supply chain optimization, while SAP Concur automates expense reporting.
The SAP Business AI page on www.sap.com further notes:
“Drive impact with AI grounded in your business data and embedded into every business function. … With access to over 230 AI-powered scenarios―expanding to 400 by the end of 2025―SAP Business AI streamlines operations across finance, supply chain, and more.” sap.com
This embedded approach ensures that AI is relevant and immediately applicable, distinguishing SAP Business AI from generic AI platforms.
Option E: AI Foundation
This is correct because the AI Foundation on SAP Business Technology Platform (BTP) is a key differentiator, providing a comprehensive toolkit for developers to build, extend, and run custom AI solutions tailored to business needs. It includes services like SAP AI Core, Generative AI Hub, and access to leading AI models, ensuring scalability, security, and integration with SAP and non-SAP data. The AI Foundation, SAP’s all-in-one AI toolkit article on community.sap.com states:
“AI Foundation is SAP’s all-in-one AI toolkit, offering developers AI that’s ready-to-use, customizable, grounded in business data, and supported by leading generative AI foundation models. It is also the basis for AI capabilities that SAP embeds across its portfolio.” community.sap.com The SAP Sapphire Innovation Guide 2025 further elaborates:
“AI Foundation is the backbone of SAP’s AI technologies and provides comprehensive developer tools to build, extend, and run custom AI solutions at scale―all in one system. It simplifies AI development and operations, offering tools like the Prompt Optimizer and access to models like GPT-4.1, Claude 3.7 Sonnet, and Gemini 2.5 Pro.” sap.com
This differentiates SAP Business AI by enabling businesses to create bespoke AI applications while leveraging SAP’s enterprise-grade infrastructure, ensuring flexibility and governance.
Explanation of Incorrect Answers:
Option B: Large foundation models
This is incorrect because SAP Business AI does not primarily differentiate itself through the development or use of large foundation models (e.g., large language models or LLMs). Instead, SAP partners with leading LLM providers (e.g., Cohere, Mistral AI, Meta) to integrate their models into the SAP BTP Generative AI Hub, focusing on business-contextualized AI rather than building proprietary LLMs. The SAP Business AI article on community.sap.com clarifies:
“SAP leverages a rich ecosystem of technology partner LLM offerings through SAP BTP’s AI Foundation and Generative AI Hub, rather than developing SAP-specific LLMs. This approach ensures access to the latest innovations while prohibiting partners from training on customer data.” pages.community.sap.com
While SAP plans to fine-tune generic LLMs and create proprietary foundation models for structured data (e.g., SAP Foundation Model for tabular data), these are not yet a primary differentiator compared to the ecosystem, embedded AI, and AI Foundation. learning.sap.com
Option D: Predictive Analytics
This is incorrect because, while predictive analytics is a significant capability of SAP Business AI (e.g., forecasting demand in SAP Integrated Business Planning or predicting equipment failures in SAP S/4HANA), it is not a unique differentiator. Predictive analytics is a common feature in many AI platforms and is one of many capabilities within SAP Business AI, not a defining characteristic. The SAP Business AI documentation on www.fingent.com notes:
“SAP Business AI solutions use machine learning and advanced analytics, including predictive analytics, to gain insights into complex data. However, its differentiation lies in its integration with business processes and data, not the analytics techniques alone.” fingent.com
The unique value of SAP Business AI comes from its ecosystem, embedded nature, and developer-centric AI Foundation, rather than specific techniques like predictive analytics, which are widespread across AI solutions.
Summary:
The key differentiators of SAP Business AI are its ecosystem of innovation (leveraging a robust partner network for collaborative AI solutions), embedded AI (seamlessly integrated into SAP applications for process optimization), and AI Foundation (providing a scalable toolkit for custom AI development), corresponding to Options A, C, and E.
Option B is incorrect because SAP relies on partner LLMs rather than proprietary large foundation models as a differentiator.
Option D is incorrect because predictive analytics, while important, is not a unique differentiator compared to the broader ecosystem and integration capabilities. These differentiators align with SAP’s strategy to deliver relevant, reliable, and responsible AI within SAP Business Suite, as supported by the provided search results and official documentation.
Reference: Positioning SAP Business Suite, learning.sap.com
Exploring SAP’s AI Strategy, learning.sap.com learning.sap.com
SAP Business AI: Release Highlights Q1 2025, SAP News Center news.sap.com
SAP Sapphire Innovation Guide 2025, www.sap.com sap.com
SAP Business AI, www.sap.com sap.comsap.com
AI Foundation, SAP’s all-in-one AI toolkit, SAP Community community.sap.com SAP Business AI: A Fundamental Change, IgniteSAP ignitesap.com
SAP Business AI: Revolutionizing Enterprise Decisions, www.fingent.com
A, C, E
Explanation:
The question asks for the key differentiators of SAP Business AI, which is a suite of AI capabilities integrated into SAP Business Suite to enhance business processes, decision-making, and automation. According to official SAP documentation and the provided search results, the key differentiators of SAP Business AI include its ecosystem of innovation, embedded AI, and AI Foundation. These align with Options A, C, and E, making them the correct answers.
Explanation of Correct Answers
Option A: Ecosystem of Innovation
This is correct because SAP Business AI is distinguished by its robust ecosystem of innovation, which includes partnerships with leading technology providers (e.g., NVIDIA, Google Cloud, Microsoft, AWS, Cohere) and implementation partners to deliver cutting-edge AI solutions. This ecosystem fosters collaborative innovation, enabling SAP Business AI to integrate advanced AI models, ensure interoperability, and address customer-specific needs through a network of expertise.
The SAP Business AI overview on www.sap.com states:
“SAP’s AI strategy includes a robust partner ecosystem with synergistic collaboration, partnering with industry leaders like NVIDIA, Google Cloud, and Cohere to deliver interoperable AI agents and scalable solutions. This ecosystem enables SAP Business AI to address unique customer challenges through combined expertise and innovation.” sap.com
Additionally, the SAP News Center emphasizes the role of partners in driving innovation:
“A key element of SAP’s AI strategy is leveraging partners’ expertise. Partners develop innovative AI solutions and extensions, enhancing the SAP portfolio with customer-specific use cases built on SAP BTP.” news.sap.com
This ecosystem differentiates SAP Business AI by combining SAP’s deep business process knowledge with external AI advancements, ensuring flexibility and rapid adoption of new technologies.
Option C: Embedded AI
This is correct because SAP Business AI is uniquely differentiated by its embedded AI capabilities, which are seamlessly integrated into SAP applications (e.g., SAP S/4HANA, SAP SuccessFactors, SAP Analytics Cloud) to enhance business processes directly within workflows. Unlike standalone AI solutions, embedded AI automates tasks, provides context-aware insights, and optimizes processes without requiring users to leave their SAP environment. The Exploring SAP’s AI Strategy lesson on learning.sap.com states:
“Embedded AI Capabilities enhance SAP products by automating tasks, analyzing data, improving user experience, optimizing processes, fostering innovation, and ensuring seamless integration. Joule, a generative AI copilot, is embedded within SAP applications, offering generative AI, predictive analytics, process automation, and context-aware recommendations.” learning.sap.com
For example, SAP S/4HANA uses embedded AI for predictive maintenance and supply chain optimization, while SAP Concur automates expense reporting.
The SAP Business AI page on www.sap.com further notes:
“Drive impact with AI grounded in your business data and embedded into every business function. … With access to over 230 AI-powered scenarios―expanding to 400 by the end of 2025―SAP Business AI streamlines operations across finance, supply chain, and more.” sap.com
This embedded approach ensures that AI is relevant and immediately applicable, distinguishing SAP Business AI from generic AI platforms.
Option E: AI Foundation
This is correct because the AI Foundation on SAP Business Technology Platform (BTP) is a key differentiator, providing a comprehensive toolkit for developers to build, extend, and run custom AI solutions tailored to business needs. It includes services like SAP AI Core, Generative AI Hub, and access to leading AI models, ensuring scalability, security, and integration with SAP and non-SAP data. The AI Foundation, SAP’s all-in-one AI toolkit article on community.sap.com states:
“AI Foundation is SAP’s all-in-one AI toolkit, offering developers AI that’s ready-to-use, customizable, grounded in business data, and supported by leading generative AI foundation models. It is also the basis for AI capabilities that SAP embeds across its portfolio.” community.sap.com The SAP Sapphire Innovation Guide 2025 further elaborates:
“AI Foundation is the backbone of SAP’s AI technologies and provides comprehensive developer tools to build, extend, and run custom AI solutions at scale―all in one system. It simplifies AI development and operations, offering tools like the Prompt Optimizer and access to models like GPT-4.1, Claude 3.7 Sonnet, and Gemini 2.5 Pro.” sap.com
This differentiates SAP Business AI by enabling businesses to create bespoke AI applications while leveraging SAP’s enterprise-grade infrastructure, ensuring flexibility and governance.
Explanation of Incorrect Answers:
Option B: Large foundation models
This is incorrect because SAP Business AI does not primarily differentiate itself through the development or use of large foundation models (e.g., large language models or LLMs). Instead, SAP partners with leading LLM providers (e.g., Cohere, Mistral AI, Meta) to integrate their models into the SAP BTP Generative AI Hub, focusing on business-contextualized AI rather than building proprietary LLMs. The SAP Business AI article on community.sap.com clarifies:
“SAP leverages a rich ecosystem of technology partner LLM offerings through SAP BTP’s AI Foundation and Generative AI Hub, rather than developing SAP-specific LLMs. This approach ensures access to the latest innovations while prohibiting partners from training on customer data.” pages.community.sap.com
While SAP plans to fine-tune generic LLMs and create proprietary foundation models for structured data (e.g., SAP Foundation Model for tabular data), these are not yet a primary differentiator compared to the ecosystem, embedded AI, and AI Foundation. learning.sap.com
Option D: Predictive Analytics
This is incorrect because, while predictive analytics is a significant capability of SAP Business AI (e.g., forecasting demand in SAP Integrated Business Planning or predicting equipment failures in SAP S/4HANA), it is not a unique differentiator. Predictive analytics is a common feature in many AI platforms and is one of many capabilities within SAP Business AI, not a defining characteristic. The SAP Business AI documentation on www.fingent.com notes:
“SAP Business AI solutions use machine learning and advanced analytics, including predictive analytics, to gain insights into complex data. However, its differentiation lies in its integration with business processes and data, not the analytics techniques alone.” fingent.com
The unique value of SAP Business AI comes from its ecosystem, embedded nature, and developer-centric AI Foundation, rather than specific techniques like predictive analytics, which are widespread across AI solutions.
Summary:
The key differentiators of SAP Business AI are its ecosystem of innovation (leveraging a robust partner network for collaborative AI solutions), embedded AI (seamlessly integrated into SAP applications for process optimization), and AI Foundation (providing a scalable toolkit for custom AI development), corresponding to Options A, C, and E.
Option B is incorrect because SAP relies on partner LLMs rather than proprietary large foundation models as a differentiator.
Option D is incorrect because predictive analytics, while important, is not a unique differentiator compared to the broader ecosystem and integration capabilities. These differentiators align with SAP’s strategy to deliver relevant, reliable, and responsible AI within SAP Business Suite, as supported by the provided search results and official documentation.
Reference: Positioning SAP Business Suite, learning.sap.com
Exploring SAP’s AI Strategy, learning.sap.com learning.sap.com
SAP Business AI: Release Highlights Q1 2025, SAP News Center news.sap.com
SAP Sapphire Innovation Guide 2025, www.sap.com sap.com
SAP Business AI, www.sap.com sap.comsap.com
AI Foundation, SAP’s all-in-one AI toolkit, SAP Community community.sap.com SAP Business AI: A Fundamental Change, IgniteSAP ignitesap.com
SAP Business AI: Revolutionizing Enterprise Decisions, www.fingent.com
Question #12
How does integrating SAP Databricks within SAP Business Data Cloud reduce IT overhead for customers?
- A . By automating data ingestion pipelines
- B . By providing pre-built connectors to various data sources
- C . By streamlining data governance processes and minimizing the need for complex data security configurations
- D . By eliminating the need for rebuilding data structures and business logic externally
Correct Answer: D
D
Explanation:
SAP Business Data Cloud (BDC) is a fully managed Software-as-a-Service (SaaS) solution that unifies and governs SAP and non-SAP data, integrating SAP Databricks to enable advanced analytics and AI-driven insights. The question asks how the integration of SAP Databricks within SAP BDC reduces IT overhead for customers, with one correct answer. Below, each option is evaluated based on official SAP documentation, SAP Learning materials, and relevant web sources from the provided search results, ensuring alignment with the "Positioning SAP Business Data Cloud" narrative and focusing on the role of SAP Databricks.
Option A: By automating data ingestion pipelines
While SAP BDC, including its SAP Datasphere component, supports data integration and pipeline management, the automation of data ingestion pipelines is not a primary focus of SAP Databricks’ integration. SAP Databricks is designed to enhance AI/ML, data science, and data engineering capabilities, leveraging zero-copy data sharing via Delta Sharing to access data products. Although SAP BDC as a whole may reduce some pipeline management overhead, the specific role of SAP Databricks is not to automate ingestion pipelines but to utilize pre-curated data products without requiring complex ETL processes. The documentation does not emphasize automated ingestion pipelines as a key IT overhead reduction mechanism for SAP Databricks.
Extract: "SAP Business Data Cloud is deeply integrated across SAP applications, so your most critical data retains its original business context and semantics and the hidden costs of data extracts are eliminated―saving you time, resources, and effort." This option is incorrect.
Option B: By providing pre-built connectors to various data sources
SAP BDC provides pre-built connectors to SAP and non-SAP data sources through its foundation services and SAP Datasphere, enabling seamless data integration. However, this capability is not specifically tied to the SAP Databricks component. SAP Databricks leverages these connections indirectly by accessing data products shared via Delta Sharing, but it does not provide the connectors itself. The documentation highlights SAP BDC’s overall integration capabilities, not SAP Databricks’ role in providing connectors, as the primary mechanism for reducing IT overhead.
Extract: "Effortlessly connect to contextual SAP data and blend with third-party data―without managing pipelines and copying data." This option is incorrect.
Option C: By streamlining data governance processes and minimizing the need for complex data security configurations
SAP Databricks integrates with Unity Catalog for governance, which enhances data management and security within the SAP BDC environment. SAP BDC itself provides unified provisioning, security, and compliance, reducing some governance overhead. However, while governance is improved, the primary IT overhead reduction from SAP Databricks comes from eliminating the need to replicate and re-engineer data externally, not from streamlining governance processes. The documentation emphasizes data sharing and semantic preservation over governance simplification as the key benefit of SAP Databricks integration.
Extract: "SAP Databricks uses both generative and traditional AI to understand your organization’s data, business terms, and key metrics, so teams can work with data using natural language. It makes it easier to find, organize, manage, and govern data through Unity Catalog…" This option is incorrect.
Option D: By eliminating the need for rebuilding data structures and business logic externally
The integration of SAP Databricks within SAP BDC significantly reduces IT overhead by eliminating the need to rebuild data structures and business logic externally. Traditionally, customers replicate SAP data into external platforms, requiring complex ETL processes to clean, transform, and recreate business logic, which increases costs and maintenance efforts. SAP Databricks, through native integration and zero-copy Delta Sharing, provides direct access to curated, semantically rich SAP data products (e.g., from SAP S/4HANA) within the SAP BDC environment. This preserves business context and semantics, avoiding the need to re-engineer data structures or logic, thus reducing development, maintenance, and operational overhead. This is explicitly highlighted in the documentation as a key benefit of the SAP-Databricks partnership.
Extract: "Today, customers often replicate SAP data into external platforms to clean, train models, deploy them, run inference, and push results back―introducing complexity, higher costs, and governance gaps. SAP Databricks offers a better path. Customers can now run end-to-end AI, ML, and analytics directly within SAP Business Data Cloud―without needing separate platforms or physical data replication."
Extract: "Built-In Business Semantics: Because SAP data already carries deep business context and semantics, Databricks can provide powerful analytics and machine learning without forcing customers to re-invent data pipelines or guess at the meaning of fields." Extract:
"SAP Databricks also offers significantly improved data latency… This enhanced latency is possible due to the Delta Sharing approach which enables direct access to clean, curated and context-rich data products with business semantics already incorporated. … [This] results in a reduction of processing costs and lowering the overheads for initial development and ongoing maintenance of ETL processes." This option is correct.
Summary of Correct Answers:
D: Integrating SAP Databricks within SAP BDC reduces IT overhead by eliminating the need to rebuild data structures and business logic externally, leveraging zero-copy Delta Sharing to access curated SAP data products with preserved business semantics, thus minimizing complex ETL processes and maintenance costs.
Reference: SAP.com: SAP Business Data Cloud
SAP.com: SAP Databricks in Business Data Cloud
SAP Learning: Illustrating the Role of SAP Databricks in SAP Business Data Cloud
Databricks Blog: Announcing the General Availability of SAP Databricks on SAP Business Data Cloud
Advancing Analytics: SAP Databricks: Solving The SAP Interoperability Challenge?
SAP Community: SAP Databricks in SAP Business Data Cloud: Unifying SAP Business Data with Lakehouse Intelligence
SAP Business Data Cloud ― Making Data Work Together | by Sandip Roy | Medium
D
Explanation:
SAP Business Data Cloud (BDC) is a fully managed Software-as-a-Service (SaaS) solution that unifies and governs SAP and non-SAP data, integrating SAP Databricks to enable advanced analytics and AI-driven insights. The question asks how the integration of SAP Databricks within SAP BDC reduces IT overhead for customers, with one correct answer. Below, each option is evaluated based on official SAP documentation, SAP Learning materials, and relevant web sources from the provided search results, ensuring alignment with the "Positioning SAP Business Data Cloud" narrative and focusing on the role of SAP Databricks.
Option A: By automating data ingestion pipelines
While SAP BDC, including its SAP Datasphere component, supports data integration and pipeline management, the automation of data ingestion pipelines is not a primary focus of SAP Databricks’ integration. SAP Databricks is designed to enhance AI/ML, data science, and data engineering capabilities, leveraging zero-copy data sharing via Delta Sharing to access data products. Although SAP BDC as a whole may reduce some pipeline management overhead, the specific role of SAP Databricks is not to automate ingestion pipelines but to utilize pre-curated data products without requiring complex ETL processes. The documentation does not emphasize automated ingestion pipelines as a key IT overhead reduction mechanism for SAP Databricks.
Extract: "SAP Business Data Cloud is deeply integrated across SAP applications, so your most critical data retains its original business context and semantics and the hidden costs of data extracts are eliminated―saving you time, resources, and effort." This option is incorrect.
Option B: By providing pre-built connectors to various data sources
SAP BDC provides pre-built connectors to SAP and non-SAP data sources through its foundation services and SAP Datasphere, enabling seamless data integration. However, this capability is not specifically tied to the SAP Databricks component. SAP Databricks leverages these connections indirectly by accessing data products shared via Delta Sharing, but it does not provide the connectors itself. The documentation highlights SAP BDC’s overall integration capabilities, not SAP Databricks’ role in providing connectors, as the primary mechanism for reducing IT overhead.
Extract: "Effortlessly connect to contextual SAP data and blend with third-party data―without managing pipelines and copying data." This option is incorrect.
Option C: By streamlining data governance processes and minimizing the need for complex data security configurations
SAP Databricks integrates with Unity Catalog for governance, which enhances data management and security within the SAP BDC environment. SAP BDC itself provides unified provisioning, security, and compliance, reducing some governance overhead. However, while governance is improved, the primary IT overhead reduction from SAP Databricks comes from eliminating the need to replicate and re-engineer data externally, not from streamlining governance processes. The documentation emphasizes data sharing and semantic preservation over governance simplification as the key benefit of SAP Databricks integration.
Extract: "SAP Databricks uses both generative and traditional AI to understand your organization’s data, business terms, and key metrics, so teams can work with data using natural language. It makes it easier to find, organize, manage, and govern data through Unity Catalog…" This option is incorrect.
Option D: By eliminating the need for rebuilding data structures and business logic externally
The integration of SAP Databricks within SAP BDC significantly reduces IT overhead by eliminating the need to rebuild data structures and business logic externally. Traditionally, customers replicate SAP data into external platforms, requiring complex ETL processes to clean, transform, and recreate business logic, which increases costs and maintenance efforts. SAP Databricks, through native integration and zero-copy Delta Sharing, provides direct access to curated, semantically rich SAP data products (e.g., from SAP S/4HANA) within the SAP BDC environment. This preserves business context and semantics, avoiding the need to re-engineer data structures or logic, thus reducing development, maintenance, and operational overhead. This is explicitly highlighted in the documentation as a key benefit of the SAP-Databricks partnership.
Extract: "Today, customers often replicate SAP data into external platforms to clean, train models, deploy them, run inference, and push results back―introducing complexity, higher costs, and governance gaps. SAP Databricks offers a better path. Customers can now run end-to-end AI, ML, and analytics directly within SAP Business Data Cloud―without needing separate platforms or physical data replication."
Extract: "Built-In Business Semantics: Because SAP data already carries deep business context and semantics, Databricks can provide powerful analytics and machine learning without forcing customers to re-invent data pipelines or guess at the meaning of fields." Extract:
"SAP Databricks also offers significantly improved data latency… This enhanced latency is possible due to the Delta Sharing approach which enables direct access to clean, curated and context-rich data products with business semantics already incorporated. … [This] results in a reduction of processing costs and lowering the overheads for initial development and ongoing maintenance of ETL processes." This option is correct.
Summary of Correct Answers:
D: Integrating SAP Databricks within SAP BDC reduces IT overhead by eliminating the need to rebuild data structures and business logic externally, leveraging zero-copy Delta Sharing to access curated SAP data products with preserved business semantics, thus minimizing complex ETL processes and maintenance costs.
Reference: SAP.com: SAP Business Data Cloud
SAP.com: SAP Databricks in Business Data Cloud
SAP Learning: Illustrating the Role of SAP Databricks in SAP Business Data Cloud
Databricks Blog: Announcing the General Availability of SAP Databricks on SAP Business Data Cloud
Advancing Analytics: SAP Databricks: Solving The SAP Interoperability Challenge?
SAP Community: SAP Databricks in SAP Business Data Cloud: Unifying SAP Business Data with Lakehouse Intelligence
SAP Business Data Cloud ― Making Data Work Together | by Sandip Roy | Medium
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