论文代写:信息技术研究报告

论文代写:信息技术研究报告

大数据的另一个特点包括它的多样性。这意味着数据进行非常多样化。它聚集在各种不同的格式。这些不同的数据格式,包括数字数据、非结构化的文本文件,视频,音频,数据收集电子邮件,结构化数据,股票数据,从业务线应用程序生成的信息,有关的金融交易数据,等所有这些不同来源的数据生成大量具有不同格式的数据。组织,分析和分类这些数据集是不是一个容易的任务,为许多组织。(斯尼德斯,C.,Matzat,美国,和reips,u.d.,2012)。
大数据具有另一个主要特征,即变异性。数据流往往是非常不一致的周期性峰,随着几个品种的数据集和上升速度。它可能是非常困难的,以维持和处理事件触发,每天和气候峰值数据负载。当非结构化数据包含在数据集中时,这就变得更加复杂了。(斯尼德斯,C.,Matzat,美国,和reips,u.d.,2012)。
大数据的关键特征之一是它的复杂性。目前,有许多来源的数据收集。从多个变量源收集的数据,不容易匹配,分类,净化,连接和转换系统。然而,为了避免失去对收集到的数据的控制,它是至关重要的关联和链接关系,多个数据的联系和层次结构。(乔,H,2008)。
大数据使用的几种可能的未来趋势包括以下几。
第一个未来的趋势是大数据作为服务解决方案。需要大量的成本,以适用大数据,因此,中小型企业发现更难以实现大数据。另外,大数据作为一个服务解决方案包括基础设施作为一个服务,数据作为一个服务和分析服务,因此也很容易为中小型企业采用大数据。

论文代写:信息技术研究报告

Another characteristic of big data includes its variety. This means that the data being conducted is very diversifies. It is gathered in all different kinds of formats. These various data formats include numeric data, unstructured text documents, videos, audios, data collected via emails, structured data, stock ticker data, info generated from line-of-business applications, data related to financial transactions, etc. all these varied sources of data generate huge amounts of data which have different formats. Organizing, analysing and classifying such data sets is not an easy task for many of the organizations. (Snijders, C., Matzat, U., & Reips, U.D., 2012).

Big data possesses another major characteristic which is variability. Data flows can tend to be greatly inconsistent with periodic peaks, along with several varieties of data sets and the rising velocities. It can be very difficult to maintain and process event triggered, daily and climatic peak data loads. This becomes even more complicated when unstructured data is included in the data sets. (Snijders, C., Matzat, U., & Reips, U.D., 2012).

One of the key characteristics of big data is its complexity. At present, there are many sources of data collection. Data collected from several variable sources, is not easy to match, classify, purify, connect and transform across the systems. However, in order to avoid losing control over the gathered data, it is crucial to correlate and link relationships, multiple data linkages and hierarchies. (Joe, H., 2008).

Several possible future trends of big data usage include the following.

The first future trend is big data as a service solution. Heavy costs are needed in order to apply big data and as a result the small and medium enterprises find it more difficult to implement big data. Alternatively, big data as a service solution comprises of infrastructure as a service, data as a service and analytics as a service, hence making it easy for the small and medium enterprises to adopt big data as well.