aggregate size

简明释义

1. 骨料粒度; 2. 骨料粒径;

英英释义

例句

1.The aggregate size 总大小 of the customer database is crucial for our marketing strategy.

客户数据库的aggregate size 总大小对我们的市场营销策略至关重要。

2.Researchers calculated the aggregate size 总大小 of all particles in the sample to determine its composition.

研究人员计算了样本中所有颗粒的aggregate size 总大小以确定其组成。

3.The report indicated that the aggregate size 总大小 of the dataset has increased significantly over the past year.

报告指出，数据集的aggregate size 总大小在过去一年中显著增加。

4.When analyzing web traffic, it's important to look at the aggregate size 总大小 of data transferred over a specific period.

在分析网络流量时，查看特定时间内传输的数据的aggregate size 总大小是很重要的。

5.In construction, the aggregate size 总大小 of materials determines how they can be used in different applications.

在建筑中，材料的aggregate size 总大小决定了它们在不同应用中的使用方式。

作文

In recent years, the concept of data analytics has gained immense popularity across various fields. One crucial aspect of data analytics is understanding the aggregate size of datasets. The term aggregate size refers to the total amount or volume of data that is collected and summarized from multiple sources. This can include numerical data, text data, and even multimedia content. By analyzing the aggregate size, organizations can gain insights into trends, patterns, and anomalies that may not be visible when looking at individual data points.For instance, in the field of marketing, businesses often gather data from various channels such as social media, email campaigns, and website traffic. The aggregate size of this data provides a comprehensive view of customer behavior and preferences. This information is invaluable for making informed decisions about marketing strategies and product development.Moreover, the aggregate size can also play a significant role in resource allocation. When organizations understand the total volume of data they are dealing with, they can better allocate their resources, whether it be personnel, technological infrastructure, or financial investment. For example, a company that recognizes a large aggregate size of customer feedback data might decide to invest in advanced analytics tools to process and analyze this information efficiently.In addition to business applications, the concept of aggregate size is also relevant in scientific research. Researchers often compile data from various experiments and studies to create a more comprehensive dataset. The aggregate size of this combined data can significantly enhance the validity and reliability of research findings. It allows scientists to draw more robust conclusions and identify correlations that may not be apparent in smaller datasets.However, it is essential to consider the quality of the data when evaluating its aggregate size. A large aggregate size does not necessarily equate to valuable insights. If the data is flawed, biased, or irrelevant, it can lead to misleading conclusions. Therefore, organizations must prioritize data quality alongside quantity when analyzing their aggregate size.Furthermore, as the aggregate size of data continues to grow exponentially, challenges related to data management and analysis become increasingly complex. Companies must develop effective strategies to handle this influx of information, ensuring that they can extract meaningful insights without being overwhelmed by the sheer volume of data.In conclusion, the aggregate size of data is a fundamental concept in data analytics that encompasses the total volume of information collected from various sources. Understanding and leveraging the aggregate size can provide organizations with valuable insights, improve decision-making processes, and enhance resource allocation. However, it is crucial to maintain a focus on data quality to ensure that the insights derived from the aggregate size are accurate and actionable. As we move forward in an increasingly data-driven world, mastering the concept of aggregate size will be vital for success in numerous fields, from business to science and beyond.

近年来，数据分析的概念在各个领域中获得了巨大的普及。数据分析的一个关键方面是理解数据集的aggregate size。术语aggregate size指的是从多个来源收集和汇总的数据的总量或体积。这可以包括数值数据、文本数据，甚至多媒体内容。通过分析aggregate size，组织可以获得趋势、模式和异常的洞察，这些在查看单个数据点时可能不可见。例如，在市场营销领域，企业通常从社交媒体、电子邮件活动和网站流量等各种渠道收集数据。这些数据的aggregate size提供了客户行为和偏好的全面视图。这些信息对于制定有关营销策略和产品开发的明智决策至关重要。此外，aggregate size还可以在资源分配中发挥重要作用。当组织了解他们所处理的数据的总量时，他们可以更好地分配资源，无论是人力、技术基础设施还是财务投资。例如，一家公司如果认识到客户反馈数据的aggregate size很大，可能会决定投资于先进的分析工具，以高效处理和分析这些信息。除了商业应用，aggregate size的概念在科学研究中也很相关。研究人员经常将来自各种实验和研究的数据汇编在一起，以创建更全面的数据集。这些合并数据的aggregate size可以显著增强研究结果的有效性和可靠性。它使科学家能够得出更稳健的结论，并识别在较小数据集中可能不明显的相关性。然而，在评估数据的aggregate size时，考虑数据质量至关重要。庞大的aggregate size并不一定等同于有价值的洞察。如果数据存在缺陷、偏见或不相关，则可能导致误导性结论。因此，组织在分析其aggregate size时，必须优先考虑数据质量与数量。此外，随着数据的aggregate size不断呈指数级增长，与数据管理和分析相关的挑战变得越来越复杂。公司必须制定有效的策略来处理这一信息涌入，确保他们能够提取有意义的洞察，而不会被大量数据所淹没。总之，数据的aggregate size是数据分析中的一个基本概念，涵盖了从各种来源收集的信息的总量。理解和利用aggregate size可以为组织提供有价值的洞察，改善决策过程，并增强资源分配。然而，必须保持对数据质量的关注，以确保从aggregate size中得出的洞察是准确且可操作的。随着我们在一个日益以数据驱动的世界中前进，掌握aggregate size的概念对于商业、科学等众多领域的成功至关重要。