一種簡單的存儲和可視化物聯網傳感器數據的方法

　　物聯網（IOT）設計的應用有望產生數據填補云提供可操作的信息，令。然而，對于大多數物聯網開發商，流數據的云和意義，它需要專家級的數據交換和分析技術的理解。

　　沒有簡單的方法來深入分析數據流的實時從多個來源，物聯網開發人員可以發現自己很難理解其應用程序的整體功能性能的數據質量問題的影響。

　　為了幫助這一點，初始狀態技術提供了一個分析服務，開發人員可以使用輕松獲得深入了解物聯網設備數據。然后，他們可以轉換成有用的信息，可訪問桌面或移動設備。

　　The need for embedded analytics

　　For any IoT application， the product of interest to its users is the actionable information derived from data streams generated by sensor nodes attached to individuals， equipment， or structures. Among the challenges facing IoT developers， the verification of these data streams requires the ability to visualize and measure the data itself.

　　For this， IoT application developers can take advantage of a growing array of cloud-based services to transform raw data into the required result. Within these data processing workflows， data analytics provides a critical capability for humans to understand the nature of the data to ensure its quality and identify useful events or anomalies that cannot be anticipated in the workflow.

　　For developers， IoT data analytics brings an entirely new set of requirements beyond those familiar to Web developers. While the latter typically requires offline batch processing of large log files， IoT data analytics combines large data repositories （“big data”） with “fast data.” To be effective， IoT applications must process large streams of data in real time to react to real-world events.