Data Foundation for the Age of AI
More than a data management solution, Data Cloud is an evolutionary leap that enables transformative AI experiences and higher degrees of customer-centricity. By unifying any data source with your CRM data from the Salesforce platform, Data Cloud allows business leaders to unlock deep, actionable insights. To deliver these experiences, Salesforce and AWS are expanding their strategic partnership, bringing AWS AI services to Salesforce’s Einstein Trust Layer, and providing Data Cloud with seamless, zero-ETL access to any AWS data service, as well as the ability to execute data processing tasks using AWS compute services. And to make it easier to realize this combined value, Data Cloud and other Salesforce offerings are now available for purchase through the AWS Marketplace. This e-book will show how Data Cloud unifies and harmonizes huge amounts of diverse business data with CRM data from the Salesforce Einstein 1 Platform, providing businesses with an unparalleled view of their data universe and a sturdy foundation for better customer experiences powered by AI.
Key Takeaways
- ✓ Consistency: The use of Apache Iceberg as a table format ensures that every user sees a consistent view of the data, regardless of updates or modifications. This feature, known as snapshot isolation, is critical in a CRM context where different team members could be accessing and modifying data at the same time.
- ✓ Durability: Data Cloud supports schema evolution, meaning that the structure of the data can change over time without breaking existing workflows. This enables CRM customers to modify their data structures as needs change.
- ✓ Interoperability: Data Cloud pushes Salesforce metadata to the level of Iceberg tables, enabling zero-ETL data sharing. This means customers can virtually access data from other sources through zero copy federation, as well as extend their Salesforce data to other systems like Amazon SageMaker, enabling custom machine learning without an added ETL lift.
- ✓ Scalability: Data Cloud can handle huge datasets, scaling easily as demand grows. This is particularly important for large CRM customers who may have extensive customer databases — like a recent customer who brought in over three trillion rows of data in one week.
- ✓ Efficiency: In Data Cloud, tables are designed to optimize data access patterns, allowing for quicker query responses. Here, Salesforce engineers contributed back to the Iceberg project, enabling Iceberg tables to support streaming reads. This enabled engineers to achieve a paradigm where tables can operate as events, and events can operate as tables, making Data Cloud a truly “active” data platform.
- ✓ Flexibility: Data Cloud is compatible with a variety of data computing frameworks, like Apache Spark and Trino, providing flexibility in data processing and analysis. This lets customers bring the tools they want to use for analysis and insight.
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