aggregations

简明释义

英[ˌæɡrɪˈɡeɪʃənz]美[ˌæɡrɪˈɡeɪʃənz]

n. 聚集；聚合（aggregation的复数形式）

英英释义

单词用法

同义词

反义词

例句

1.One example use is aggregations, where a set of EPCs is associated with another EPC.

一种用途是聚合，也就是将一组EPC与另一个EPC关联起来。

2.A processor core then picks up the uncompressed, filtered data block and performs fundamental database operations such as sorts, joins, and aggregations.

处理器内核随后选出未压缩的、过滤后的数据块，执行基本的数据库操作，如排序、联接和聚合。

3.If a measure has more than one aggregation function in its list of aggregations, then the measure is an asymmetric measure.

如果一个度量在它的聚合列表中有多个聚合函数，那么这个度量就是非对称的度量。

4.Visualizations of metrics provide alternate views of specific dimensions, either of single dimensions or aggregations of several dimensions.

指标的可视化为特定的维提供替代视图，包括单一维和多个维的聚合。

5.For complex business analysis applications requiring sophisticated correlations, aggregations, and joins, this is rarely acceptable.

对于需要高级关联、聚合和连接的复杂业务分析应用程序，这样做很难被接受。

6.Metals are also large aggregations.

金属也是一个大的集合。

7.The financial analyst focused on aggregations of quarterly earnings to forecast future performance.

金融分析师专注于季度收益的聚合以预测未来表现。

8.We used aggregations of survey responses to draw conclusions about employee satisfaction.

我们使用调查回应的聚合来得出关于员工满意度的结论。

9.In the report, we included aggregations of sales data from different regions to identify trends.

在报告中，我们包含了来自不同地区的销售数据的聚合以识别趋势。

10.The data analysis revealed several interesting aggregations of customer behavior patterns.

数据分析揭示了客户行为模式的几个有趣的聚合。

11.The research paper discussed various aggregations of social media metrics to measure engagement.

研究论文讨论了各种社交媒体指标的聚合以衡量参与度。

作文

In today's world, data plays a crucial role in decision-making processes across various industries. One of the key concepts that has emerged in the field of data analysis is the idea of aggregations（聚合）. Aggregations refer to the process of combining multiple data points into a single summary measure. This can be particularly useful when dealing with large datasets, as it allows analysts to identify trends and patterns that would otherwise be difficult to discern. For instance, in the realm of business, companies often use aggregations（聚合） to analyze sales data. By aggregating sales figures from different regions, they can gain insights into overall performance and make informed strategic decisions. Moreover, aggregations（聚合） are not limited to numerical data. They can also apply to qualitative information. For example, social media platforms often aggregate user-generated content to provide users with a curated experience. By considering various posts, comments, and likes, these platforms can deliver personalized content that resonates with individual users. This process of aggregation（聚合） helps enhance user engagement and satisfaction.In the field of research, aggregations（聚合） play a vital role in synthesizing information from multiple studies. Researchers often conduct meta-analyses, where they aggregate results from various experiments to draw more robust conclusions. This approach not only increases the reliability of findings but also provides a broader understanding of the subject matter. For instance, in medical research, aggregating data from clinical trials can help determine the effectiveness of a new drug across diverse populations.However, while aggregations（聚合） offer significant advantages, there are also challenges associated with this process. One of the main concerns is the potential loss of important details when data is aggregated. For example, if a company only looks at overall sales figures without considering regional variations, it may overlook specific markets that are underperforming or thriving. Therefore, it is essential for analysts to strike a balance between aggregations（聚合） and detailed analysis to ensure that critical insights are not lost.Additionally, the methodology used for aggregations（聚合） can greatly influence the outcomes. Different aggregation techniques, such as mean, median, or mode, can yield varying results. Choosing the appropriate method depends on the nature of the data and the specific questions being addressed. Analysts must be well-versed in these techniques to ensure accurate interpretations of the aggregated data.In conclusion, aggregations（聚合） are an essential aspect of data analysis that enables organizations and researchers to derive meaningful insights from complex datasets. By effectively aggregating data, one can uncover trends, enhance decision-making, and improve overall understanding of various phenomena. However, it is crucial to be mindful of the potential pitfalls associated with aggregations（聚合） to maximize their benefits. As we continue to navigate an increasingly data-driven world, mastering the art of aggregation（聚合） will undoubtedly remain a valuable skill for professionals in every field.

在当今世界，数据在各个行业的决策过程中发挥着至关重要的作用。在数据分析领域，一个关键概念是aggregations（聚合）的想法。Aggregations指的是将多个数据点合并为一个单一的摘要度量的过程。当处理大型数据集时，这尤其有用，因为它使分析师能够识别出难以辨别的趋势和模式。例如，在商业领域，公司通常使用aggregations（聚合）来分析销售数据。通过聚合来自不同地区的销售数字，他们可以获得整体表现的洞察，并做出明智的战略决策。此外，aggregations（聚合）不仅限于数值数据。它们也适用于定性信息。例如，社交媒体平台通常聚合用户生成的内容，以提供用户精心策划的体验。通过考虑各种帖子、评论和点赞，这些平台可以向用户提供与个人相关的个性化内容。这个aggregation（聚合）过程有助于增强用户参与感和满意度。在研究领域，aggregations（聚合）在综合来自多个研究的信息方面发挥着重要作用。研究人员通常进行荟萃分析，在此过程中，他们聚合来自各种实验的结果，以得出更可靠的结论。这种方法不仅增加了发现的可靠性，还提供了对主题的更广泛理解。例如，在医学研究中，聚合来自临床试验的数据可以帮助确定新药在不同人群中的有效性。然而，尽管aggregations（聚合）提供了显著的优势，但这一过程也存在挑战。主要的担忧之一是，当数据被聚合时，可能会丢失重要的细节。例如，如果一家公司仅查看整体销售数字，而不考虑地区差异，它可能会忽视特定市场的低迷或繁荣。因此，分析师必须在aggregations（聚合）和详细分析之间取得平衡，以确保关键洞察不会丢失。此外，用于aggregations（聚合）的方法论可以极大地影响结果。不同的聚合技术，如均值、中位数或众数，可能会产生不同的结果。选择适当的方法取决于数据的性质和所要解决的具体问题。分析师必须熟练掌握这些技术，以确保对聚合数据的准确解读。总之，aggregations（聚合）是数据分析的重要方面，使组织和研究人员能够从复杂的数据集中提取有意义的洞察。通过有效聚合数据，可以揭示趋势、增强决策能力并改善对各种现象的整体理解。然而，必须注意与aggregations（聚合）相关的潜在陷阱，以最大化其好处。随着我们继续在一个日益数据驱动的世界中航行，掌握aggregation（聚合）的艺术无疑将继续成为各个领域专业人士的一项宝贵技能。