Big Data: A Revolution That Will Transform How We Live, Work, and Think

Class Attendance30%Final Report 70%

上課30% 期末報告 70%

Class Attendance30%Final Report 70%

上課30% 期末報告 70%

Big data is that data sets are so large and complex that traditional data-processing applications are not enough to deal with them. Big data challenges include capture data, data storage, data analysis, search, sharing, transmission, visualization, querying, updating, and confidentiality of information. There are five dimensions called batch, multi variety, speed and recently added accuracy and value data. "Big data" often refers to the use of predictive analytics, where user behavioral analytics is the value that is extracted from the data, with little regard to the specific size of the data set, or some other advanced data analysis method. Data sets are rapidly growing - in part because they are increasingly being used by inexpensive and large amounts of sensing information to collect IoT devices such as mobile devices, aviation (remote sensing), software logs, cameras, microphones, RFID readings And wireless sensor networks.it can be applied to Relational database management systems and desktop statistics: And visualization, packaging is often difficult to handle big data. This work may require "dozens, hundreds, or even thousands of server runs of massively parallel software."

大數據是數據集是如此龐大和複雜，傳統的數據處理 應用軟件都不足以對付他們。大數據的挑戰包括捕獲數據，數據存儲，數據分析，搜索，共享，傳輸，可視化，查詢，更新和信息保密。有五個維度稱為批量，多品種，速度和最近添加的準確性和值大的數據。“大數據”往往是指使用預測分析，用戶行為分析是從數據中提取價值，也很少對數據集的特定大小，或某些其他先進的數據分析方法。數據集快速增長-部分是因為他們越來越多地被廉價和大量的傳感信息收集物聯網設備，如移動設備，航空（遙感），軟件 日誌，攝像頭，麥克風，無線射頻識別（RFID）閱讀器和無線傳感器網絡。它可用於關係數據庫管理系統和桌面統計：和可視化，包裝往往難以處理大數據。這項工作可能需要“大規模並行軟件 的數十，數百，甚至數千台服務器運行”