论文代写：信息技术研究报告
多个数据集是如此复杂和巨大的，他们的处理变得困难。正如名称指定的，大数据是指大量的数据。巨大的和多样化的信息被包含在它。使用广义的仪器或程序来处理这样庞大的数据集是不可能的。为了处理这样的数据集，它是至关重要的，利用特定的数据处理应用程序和仪器。因此，大数据是一个术语，用于那些包含大量和复杂的信息的数据集。（瑞克曼，O.J.，琼斯，M.B.，希尔德豪尔，M.，2011）。
大数据包括这样的数据集是复杂的和大的。有一些元素，增加数据的大小。这些因素主要包括非结构化数据流，大量的机器对机器和传感器数据的采集，交易被储存了一年的数据，等以前海量数据难以存储。然而，随着时间的推移，其他问题已经出现，作为存储成本已下降。这些问题包括确定适当使用分析的方法，使相关的数据有用的和有意义的，并找出方法来确定增加的数据量的相关性。（乔，H，2008）。
大数据的另一个特点是它的速度。目前，数据正在以一种加速的速度产生，因此，它需要快速处理。速度基本上是指速度。数据采集和处理速度增加，这是大多数公司的一个挑战。正在收集的数据需要以更快的速度处理。面对着数据的需求已经由传感器、智能电表和RFID标签。（斯尼德斯，C.，Matzat，U.，和Reips，U.D.，2012）。
论文代写：信息技术研究报告
Several data sets are so complicated and huge that their processing becomes difficult. As the name specifies, big data refers to large amounts of data. Huge and diversified information is included in it. It is not possible to process such huge data sets by using generalized instruments or procedures. In order to process such data sets, it is crucial to utilize specific data processing applications and instruments. Hence, big data is a term used for those data sets which are containing large and complicated amounts of information. (Reichman, O.J., Jones, M.B., Schildhauer, M.P., 2011).
Big data includes such data sets which are complex and large. There are a number of elements that increase the size of the data. These elements majorly include the unstructured data streaming, gathering of large amounts of machine-to-machine and sensor data, data of transactions which is being stored over the years, etc. previously huge amounts of data were difficult to store. However, with the passage of time, other issues have emerged as the storage costs have been decreased. These problems include determining the ways of appropriate use of analytics for making relevant data useful and meaningful, and finding out ways to determine relevance of increased data volumes. (Joe, H., 2008).
Another characteristic of big data is its velocity. At present, data is being generated at an accelerated pace and hence, it requires quick processing. Velocity basically refers to speed. The data collection and processing speed has increased which is a challenge for majority of the companies. The data which is being gathered needs to be processed at a faster pace. The requirement to deal with torrents of data has been generated by sensors, smart metering and RFID tags. (Snijders, C., Matzat, U., & Reips, U.D., 2012).