The tsunami of data — set to exceed 180 zettabytes by 2025 — places significant pressure on companies. Simply having access to customer information is not enough — companies must also analyze and refine the data to find actionable pieces that power new business.
As businesses collect these volumes of customer data, they rely on Salesforce Data Cloud — a single source of truth for harmonizing, storing, unifying, and nurturing this information as it dynamically evolves over time. Consequently, businesses understand their customers’ needs better than ever — powering enhanced customer experiences.
当企业收集这些大量的客户数据时，他们依赖于Salesforce Data Cloud- 一个单一的真理源，用于协调、存储、统一和培养这些信息，因为这些信息会随着时间的推移而动态变化。因此，企业比以往任何时候都更了解其客户的需求，从而为增强客户体验提供动力。
Looking under the hood of Data Cloud reveals a couple key layers. The platform’s bottom-most layer, the storage layer, consists of a data lake that ingests petabytes of customer data. Above that lies a compute plane layer, which processes, massages, and interprets the big data — enabling the information to be segmented and activated.
Essentially the engine behind Data Cloud, this tier-zero fabric layer’s journey began with a complex data migration orchestration to Data Cloud’s data lake from Dataroma — Salesforce’s cloud-based marketing intelligence platform — leading to the creation of Data Cloud’s big data processing compute layer team in India.
Executing this task was massive as it involved multiple teams — who managed the migration orchestration effort? Say hello to Data Cloud’s compute layer team. The migration initially challenged them because they had no experience in big data processing. How did they successfully orchestrate the migration in mere months and then immediately launch their tier-zero layer to ...