base data

简明释义

1. 原始数据; 2. 基本数据; 3. 基本资料; 4. 原始资料; 5. 基础数据;

英英释义

例句

1.The research team analyzed the base data to identify trends in consumer behavior.

研究团队分析了基础数据以识别消费者行为的趋势。

2.Before making any predictions, we need to ensure the base data is accurate and up-to-date.

在做出任何预测之前，我们需要确保基础数据是准确和最新的。

3.It is crucial to clean the base data before running any statistical models.

在运行任何统计模型之前，清理基础数据是至关重要的。

4.The base data collected from the survey will form the foundation of our analysis.

从调查中收集的基础数据将构成我们分析的基础。

5.We used historical base data to forecast future sales figures.

我们使用历史基础数据来预测未来的销售数字。

作文

In today's data-driven world, the term base data refers to the foundational information that serves as a primary reference point for analysis and decision-making. This concept is crucial in various fields, including science, business, and technology. The importance of base data cannot be overstated, as it lays the groundwork for any further investigations or conclusions drawn from the data. Without accurate and reliable base data, any subsequent findings may be flawed or misleading.For instance, in scientific research, base data consists of raw measurements and observations collected during experiments. Researchers rely on this information to formulate hypotheses and conduct analyses. If the base data is compromised due to errors in measurement or data collection methods, the validity of the entire study can be jeopardized. Therefore, ensuring the accuracy of base data is a fundamental step in the research process.In the business sector, companies often utilize base data to make informed decisions regarding their operations and strategies. For example, when launching a new product, a company will analyze market trends, customer preferences, and competitor performance, all of which constitute base data. This information helps businesses identify potential opportunities and risks, allowing them to tailor their marketing strategies accordingly. If the base data is inaccurate or outdated, the company may invest resources into a failing product or miss out on a lucrative market segment.Moreover, in the realm of technology, particularly in data analytics and machine learning, base data plays a pivotal role in training algorithms. Machine learning models require vast amounts of base data to learn patterns and make predictions. If the base data used for training is biased or unrepresentative, the model's predictions will also be biased, leading to poor outcomes. Therefore, curating high-quality base data is essential for developing reliable and effective machine learning applications.The significance of base data extends beyond its immediate application; it also influences the credibility of the results derived from it. Stakeholders, whether they are investors, customers, or researchers, place their trust in the findings based on the integrity of the base data. When organizations prioritize the quality of their base data, they not only enhance their decision-making processes but also build a reputation for reliability and accuracy.In conclusion, base data is a critical component across various domains, serving as the backbone for analysis, decision-making, and innovation. Its accuracy and reliability determine the quality of insights gained from it. As we continue to navigate an increasingly complex world filled with data, understanding the importance of base data will empower individuals and organizations to make better-informed choices. By investing time and resources into collecting and maintaining high-quality base data, we can ensure that our decisions are grounded in reality and contribute positively to our respective fields.

在当今这个数据驱动的世界里，短语基础数据指的是作为分析和决策的主要参考点的基础信息。这个概念在科学、商业和技术等各个领域都是至关重要的。基础数据的重要性不容小觑，因为它为任何进一步的调查或从数据中得出的结论奠定了基础。如果没有准确可靠的基础数据，后续的发现可能会存在缺陷或误导。例如，在科学研究中，基础数据由实验过程中收集的原始测量和观察结果组成。研究人员依赖这些信息来形成假设和进行分析。如果基础数据由于测量错误或数据收集方法不当而受到损害，那么整个研究的有效性可能会受到威胁。因此，确保基础数据的准确性是研究过程中的基本步骤。在商业领域，公司通常利用基础数据做出关于其运营和战略的明智决策。例如，在推出新产品时，公司会分析市场趋势、客户偏好和竞争对手表现，这些都构成了基础数据。这些信息帮助企业识别潜在的机会和风险，从而使他们能够相应调整市场营销策略。如果基础数据不准确或过时，公司可能会将资源投入到一项失败的产品上，或者错过一个有利可图的市场细分。此外，在技术领域，特别是在数据分析和机器学习中，基础数据在训练算法中发挥着关键作用。机器学习模型需要大量的基础数据来学习模式并做出预测。如果用于训练的基础数据存在偏见或不具代表性，那么模型的预测也会存在偏见，导致糟糕的结果。因此，策划高质量的基础数据对于开发可靠和有效的机器学习应用至关重要。基础数据的重要性不仅体现在其直接应用上；它还影响从中得出的结果的可信度。利益相关者，无论是投资者、客户还是研究人员，都将他们的信任寄托在基于基础数据的发现上。当组织优先考虑其基础数据的质量时，他们不仅增强了决策过程，还建立了可靠性和准确性的声誉。总之，基础数据是各个领域中的关键组成部分，作为分析、决策和创新的支柱。它的准确性和可靠性决定了从中获得的洞察力的质量。随着我们继续在一个充满复杂数据的世界中航行，理解基础数据的重要性将使个人和组织能够做出更明智的选择。通过投入时间和资源来收集和维护高质量的基础数据，我们可以确保我们的决策扎根于现实，并对各自的领域产生积极的贡献。