Effective liquidity management is crucial for financial services to maintain regulatory compliance. Deloitte's solutions, powered by Snowflake, enhance data accuracy, scalability, reduce costs, and provide real-time insights.

Deloitte and Snowflake are working together to achieve cloud modernization and data-sharing solutions in the public sector by combining Deloitte's advanced capabilities in strategy and analytics with Snowflake's Data Cloud to streamline data management.

For organizations struggling with expensive, legacy on-premises data and analytics ecosystems, moving to a modern platform can be daunting. Deloitte’s Migration Factory can help mitigate risk in data migration while expediting the move to a future-ready platform.

As new privacy laws and regulations place more limits on how data can be collected, used stored, and shared, it’s becoming more important to establish data clean rooms, which can help organizations derive insights while keeping data safe and compliant.

Deloitte and Snowflake offer a unique combination of tools, capabilities, and resources that help organizations accelerate modernization using a business-driven approach. Deloitte’s extensive network and experience in cloud and data analytics, coupled with the Data Cloud can help businesses achieve stronger insights, reduce IT costs, secure their data exchange, and gain a competitive advantage.

• Reduce costs—Leveraging a consumption-based pricing model and self-managing capabilities, we empower organizations to pay for only what they use and easily monetize their data.
• Enhance AI capabilities—We help organizations understand their existing data ecosystem holistically and use it to drive greater business impact with AI-powered insights.
• Increase scalability and flexibility—We can help organizations capitalize on advanced data-sharing capabilities to improve data integration, management, and security.
• Accelerate deployment—We help businesses develop a comprehensive roadmap to move workloads to hybrid or multi-cloud environments utilizing a factor-oriented strategy for faster deployment.
  

Data Mesh is an architectural framework designed to address data governance and security challenges through decentralized ownership. It empowers business functions to maintain control over data access and formats, fostering faster access to relevant data and improving business agility. Key principles include autonomy, cross-domain collaboration, scalability, adaptability, improved data quality, and compliance. Domain-driven ownership allows business functions to develop and manage data products, ensuring data governance and privacy. Self-serve data infrastructure supports analytical data product development, while federated governance balances centralization and decentralization. Snowflake facilitates data mesh implementation by enabling decentralized ownership, providing elastic compute, and supporting multiple programming languages. It also offers robust governance through features like data masking and lineage tracking. The Snowflake Marketplace supports data sharing within and outside the organization, promoting data democratization while maintaining security. Adopting a data mesh enhances scalability, flexibility, and innovation by decentralizing data ownership and promoting a domain-oriented approach.