深入浅出谈“大数据”

欢迎来到 MTData 小讲堂，第一期 MT 酱跟大家聊聊大数据本身

首先来看维基百科是怎么解释的：

Big data is data sets that are so big and complex that traditional data-processing application software are inadequate to deal with them. Big data challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating, information privacy and data source. There are a number of concepts associated with big data: originally there were 3 concepts volume, variety, velocity. Other concepts later attributed with big data are veracity (i.e., how much noise is in the data) and value.

Lately, the term "big data" tends to refer to the use of predictive analytics, user behavior analytics, or certain other advanced data analytics methods that extract value from data, and seldom to a particular size of data set. "There is little doubt that the quantities of data now available are indeed large, but that’s not the most relevant characteristic of this new data ecosystem." Analysis of data sets can find new correlations to "spot business trends, prevent diseases, combat crime and so on."Scientists, business executives, practitioners of medicine, advertising and governments alike regularly meet difficulties with large data-sets in areas including Internet search, fintech, urban informatics, and business informatics. Scientists encounter limitations in e-Science work, including meteorology, genomics, connectomics, complex physics simulations, biology and environmental research.

balabala......

提炼出来就是庞大且复杂又不知道咋处理的数据

背概念太烦

我们通过边边角角来逐步了解吧

先看看大数据有什么特点

介绍完 MT 酱脑海里出现了这个画面

我们要在这堆虫里找到最肥的那几只！！！

言归正传

接下来说说大数据都有哪些技术手段

有了这些技术却依然需要面临种种挑战

海量数据存储系统要有相应等级的扩展能力

由大数据应用拓展的安全问题

「大」意味着成本代价不菲

......

那么对于这些难题拥有百亿级用户数据的美图是如何解决的呢？

8月11日美图大数据技术总监卢荣斌空降深圳给你面对面开小讲堂！

美图经历过从 0 到 1 的数据平台建设过程。从数据收集、数据落地存储、数据加工清洗再到数据平台建设，近几年也逐步构建了稳定可靠的数据平台以及数据基础服务，驱动美图各业务更高效稳定地使用数据、挖掘数据价值、驱动业务增长。本次沙龙卢荣斌将给大家介绍美图大数据平台架构以及在平台演进过程的思考和实践。