In the age of the AI revolution, where chatbots, generative AI, and large language models (LLMs) are taking the business world by storm, enterprises are fast realizing the need for strong data control and privacy to protect their confidential and commercially sensitive data, while still providing access to this data for context-specific AI insights.
Snowflake and Salesforce have built on our existing partnership to unify the full breadth of customer and business data and generate actionable insights for our customers. We are happy to announce the general availability of Bring Your Own Lake (BYOL) Data Sharing with the Snowflake Data Cloud from Salesforce Data Cloud. Organizations can now leverage Salesforce data directly in Snowflake via zero-ETL data sharing to accelerate decision-making and help streamline business processes.
Automation, reliability and scale are the seeds for growing innovation.
Semantic layers are a game changer, allowing organizations to define metrics and business logic in one, centralized location. Because business users can trust that their data is built on a single source of truth, the semantic layer also empowers self-service analytics. Looker Modeler has become a leader among semantic layers, allowing users to seamlessly layer on top of their business data.
In the first two parts of our Inside Flink blog series, we explored the benefits of stream processing with Flink and common Flink use cases for which teams are choosing to leverage the popular framework to unlock the full potential of streaming. Specifically, we broke down the key reasons why developers are choosing Apache Flink® as their stream processing framework, as well as the ways in which they are putting it into practice.
