duplicates

简明释义

英[/ˈduː.plɪ.kəts/]美[/ˈduː.plɪ.kəts/]

n. 副本，[印刷]复制品（duplicate 的复数形式）；多重记录；倍增

v. 复制（duplicate 的三单形式）

英英释义

单词用法

同义词

反义词

例句

1.Otherwise, the numbers will be misleading since duplicates are not archived.

否则，得到的数字会令人产生误解，因为重复的邮件是不归档的。

2.The last nub method ensures that no duplicates exist in the list.

最后的nub方法能确保该列表中不存在重复值。

3.When a process duplicates itself, the kernel makes a copy of all open file descriptors.

当某个进程复制它自身时，内核生成所有打开的文件描述符的副本。

4.If duplicates are found, the example client reports them like this.

如果发现重复的WSDL，示例客户端会进行如下报告。

5.These sets should not contain duplicates.

这些集合中不应包含相同项。

6.The "dirty data" for the example includes 40% suspect duplicates.

本例的“脏数据”包含40%的可疑副本。

7.Please make sure to remove any duplicates 重复项 from the list before submitting it.

请确保在提交之前从列表中删除任何重复项。

8.The database is full of duplicates 重复数据, making it difficult to analyze the information accurately.

数据库中充满了重复数据，这使得准确分析信息变得困难。

9.We need to find a way to identify duplicates 重复项 in our inventory system.

我们需要找到一种方法来识别库存系统中的重复项。

10.The report highlighted several duplicates 重复记录 that needed to be addressed.

报告强调了几个需要处理的重复记录。

11.She spent hours cleaning up the spreadsheet to eliminate duplicates 重复项.

她花了几个小时清理电子表格以消除重复项。

作文

In today's digital age, the issue of data management has become increasingly important. One common problem that many individuals and organizations face is the presence of duplicates in their databases. These duplicates can lead to confusion, inefficiencies, and even financial losses. Understanding the nature of duplicates and how to manage them is essential for anyone who works with data. Duplicates, in this context, refer to instances where the same data appears more than once within a dataset. This can occur for various reasons, such as human error during data entry, system malfunctions, or the merging of datasets from different sources. For example, if a company collects customer information through multiple channels, it is likely that some customers will be entered into the system more than once, resulting in duplicates. The presence of duplicates can have several negative consequences. First and foremost, they can distort analytical insights. When data analysts attempt to derive conclusions from datasets that contain duplicates, the results may be skewed, leading to poor decision-making. Additionally, duplicates can complicate customer relationship management, as businesses may struggle to get a clear picture of their interactions with clients. Another significant issue related to duplicates is the impact on operational efficiency. When employees have to sift through a database filled with duplicates, it can waste valuable time and resources. This inefficiency can hinder productivity and affect overall business performance. To mitigate the risks associated with duplicates, organizations must implement effective data management strategies. One approach is to establish clear data entry protocols to minimize the chances of human error. Training staff on the importance of accurate data entry can also help reduce the occurrence of duplicates. Furthermore, using software tools designed to identify and eliminate duplicates can greatly enhance data integrity. Many modern database management systems come equipped with features that automatically detect duplicates and provide options for merging or deleting them. Regular audits of data can also be beneficial in identifying duplicates before they become a larger issue. In addition to these preventative measures, organizations should also create a culture of data stewardship. Encouraging employees to take ownership of the data they handle can foster accountability and diligence in maintaining data quality. By prioritizing data accuracy and integrity, organizations can significantly reduce the prevalence of duplicates. In conclusion, the presence of duplicates in data can lead to various challenges, including distorted analytics, reduced efficiency, and impaired customer relationships. However, by implementing effective data management practices and fostering a culture of accountability, organizations can effectively manage and minimize the impact of duplicates. As we continue to navigate an increasingly data-driven world, understanding and addressing the issue of duplicates will be vital for success.

在当今数字时代，数据管理问题变得越来越重要。许多个人和组织面临的一个常见问题是数据库中存在的重复项。这些重复项可能导致混淆、效率低下，甚至财务损失。理解重复项的性质以及如何管理它们对于任何与数据打交道的人来说都是必不可少的。在这个背景下，重复项指的是同一数据在数据集中出现多次的情况。这种情况可能由于各种原因发生，例如数据输入过程中的人为错误、系统故障或来自不同来源的数据集合并。例如，如果一家公司通过多个渠道收集客户信息，那么一些客户很可能会多次输入系统，从而导致重复项的出现。重复项的存在可能带来几种负面后果。首先，它们可能扭曲分析洞察。当数据分析师试图从包含重复项的数据集中得出结论时，结果可能会偏差，从而导致错误的决策。此外，重复项可能会使客户关系管理变得复杂，因为企业可能难以清楚地了解与客户的互动。与重复项相关的另一个重大问题是对运营效率的影响。当员工不得不在充满重复项的数据库中筛选信息时，这可能会浪费宝贵的时间和资源。这种低效率可能会妨碍生产力并影响整体商业表现。为了减轻与重复项相关的风险，组织必须实施有效的数据管理策略。一种方法是建立明确的数据输入协议，以尽量减少人为错误的可能性。对员工进行准确数据输入重要性的培训也有助于减少重复项的发生。此外，使用旨在识别和消除重复项的软件工具可以大大增强数据完整性。许多现代数据库管理系统都配备了自动检测重复项的功能，并提供合并或删除它们的选项。定期审计数据也可以帮助在重复项成为更大问题之前识别它们。除了这些预防措施外，组织还应建立数据管理文化。鼓励员工对他们处理的数据负责，可以培养责任感和维护数据质量的勤勉。通过优先考虑数据的准确性和完整性，组织可以显著减少重复项的发生。总之，数据中存在的重复项可能导致各种挑战，包括扭曲的分析、降低的效率和受损的客户关系。然而，通过实施有效的数据管理实践和培养责任文化，组织可以有效管理和最小化重复项的影响。随着我们继续在一个越来越依赖数据的世界中航行，理解和解决重复项问题将是成功的关键。