Core Insights - The success of AI strategies heavily relies on reliable data, with 94% of technology leaders focusing more on data due to the ongoing AI trend [2] - Companies face challenges in selecting the right partners to unlock data value and drive AI projects amid rapid market changes [2] Group 1: Data Transformation Strategies - Companies can follow three actionable paths for successful data transformation: empowering critical business applications, transitioning from transactional to intelligent applications, and leveraging open ecosystems [3][5][7] - Only 34% of business leaders express high trust in their data, indicating a significant challenge in data integration and management [3] - Business data fabric can simplify data management by providing an integrated, semantically rich data layer, enabling easier access to trustworthy data [3] Group 2: SAP Business Data Cloud - SAP Business Data Cloud offers a fully managed SaaS solution that unifies and governs both SAP and third-party data, facilitating strategic data projects [4] - The "zero copy share" method of SAP Business Data Cloud reduces complexities in data environments, allowing companies to focus on transformative data initiatives [4] - SAP's intelligent applications, built on its extensive business process experience, are designed to embed smart capabilities directly into core business processes [5][6] Group 3: Importance of Open Ecosystems - Companies should choose vendors with an open ecosystem strategy to access diverse industry expertise and extend solutions across multiple cloud platforms [7] - SAP's partnership strategy exemplifies this approach, as seen in collaborations with Adobe and Moody's to enhance data insights and application capabilities [7] - The integration of data and AI is crucial for future business success, with companies viewing data as a strategic asset leading to a 28% higher AI adoption rate [8]