企業無須再擔心硬體空間不夠、資料存取效率受限、災難回復等問題，且可透過運用各式雲端的分析工具，包含各式預訓練的AI等模型，將數據價值迅速體現。

Businesses do not need to worry anymore about insufficient hardware or computing storage, limited data/ file access capacity, and disaster recovery, etc. Data value can be realized as your data stored on the cloud can be easily and efficiently applied to analysis tools including pre-trained AI models.

Amazon Web Services (AWS) 除了最為知名，及高耐用性的Simple Storage Service (S3) 物件儲存服務外，亦提供超過10種以上不同類型的資料庫以因應不同使用情境，包含關聯式資料庫、鍵值資料庫、文件資料庫、記憶體內資料庫、圖形資料庫、時間序列資料庫、寬欄型資料庫和總帳資料庫。透過AWS的全受管式的服務，可確保該資料庫底層運作正常，維持高可用性、高可靠性和高安全性效能。針對儲存服務內的搜尋與分析，AWS亦有提供SQL友善的服務，使資料分析師可以在不需額外學習成本下，輕易地分析雲端中保存的資料，並且也有提供完善的AI模組供資料科學家使用。

In addition to the most well-known and highly durable Simple Storage Service (S3) object storage service, Amazon Web Services (AWS) also provides more than 10 different types of databases, including relational, key-value, document, in-memory, graphic, time series, wide column, and ledger databases to support different user scenarios. Through the fully managed services of AWS, databases are highly available, reliable, and secured without users worrying about database management tasks such as server provisioning, patching, configuration, or backups. For search and analysis in storage services, AWS also provides SQL-friendly services so that data analysts can easily analyze data stored in the cloud without additional learning, and it also provides comprehensive AI modules for data scientists’ needs.

Google Cloud Platform (GCP) 提供與Google自身服務相同的底層儲存與分析方案，使用者可輕易使用經優化高效與高可用性的資料存儲方案，並且輕易將資料與Google於AI深耕多年的服務做結合，不論是資料工程師、資料分析師或資料科學家都可輕易上手。

Google Cloud Platform (GCP) provides businesses the same underlying storage and analysis solutions as Google’s own services. Users can easily on-board data storage solutions that are optimized, efficient, and highly available. They can also simply integrate their own data with Google’s leading AI services. The service comes in handy for data engineer, data analyst, or data scientist.