predicated data

简明释义

预计数据

英英释义

例句

1.The marketing strategy was developed using predicated data from previous campaigns.

该营销策略是基于之前活动的前提数据制定的。

2.Investors should be cautious when making decisions based on predicated data that may not reflect current market conditions.

投资者在根据可能不反映当前市场状况的前提数据做出决策时应保持谨慎。

3.To ensure accurate forecasting, we need to update our predicated data regularly.

为了确保准确的预测，我们需要定期更新我们的前提数据。

4.Our project timeline is dependent on the accuracy of the predicated data we have collected.

我们的项目时间表依赖于我们收集的前提数据的准确性。

5.The analysis was based on predicated data, which means it relied on specific assumptions about future trends.

该分析基于前提数据，这意味着它依赖于对未来趋势的特定假设。

作文

In the modern world, data plays a crucial role in decision-making processes across various sectors. One concept that has emerged as significant in the field of data analysis is predicated data. This term refers to information that is based on certain assumptions or conditions. Understanding predicated data is essential for individuals and organizations alike, as it allows them to make informed decisions based on reliable forecasts and analyses.To illustrate the importance of predicated data, consider the example of a retail company planning its inventory for the upcoming holiday season. The management team may analyze historical sales data to predict future demand. However, this analysis is often predicated on various factors such as economic conditions, consumer trends, and even weather patterns. If the company assumes that the previous year’s sales will directly correlate with this year’s performance without considering these influencing factors, they may end up overstocking or understocking their products.Moreover, predicated data can be utilized in the field of healthcare. For instance, medical researchers often rely on predicated data when conducting clinical trials. They formulate hypotheses based on existing research and then gather data to either support or refute these assumptions. By doing so, they can better understand the efficacy of new treatments or drugs. If the data collected is not accurately predicated on sound scientific principles, the results could lead to misguided conclusions, potentially harming patients and wasting resources.In the realm of technology, predicated data is also significant. For example, machine learning algorithms often function based on data that has been predicated on certain parameters. These algorithms learn from historical data to make predictions about future events. If the initial data fed into the system is flawed or based on incorrect assumptions, the predictions made by the algorithm will likely be inaccurate. Therefore, ensuring the integrity of predicated data is paramount in developing effective AI systems.Furthermore, businesses use predicated data for strategic planning. When entering new markets, companies often rely on market research that predicts consumer behavior based on demographic data, purchasing trends, and cultural factors. If these predictions are not grounded in reality, the business strategies developed may fail. For instance, a tech company might assume that a particular gadget will be popular in a new region based solely on its success in another area without considering local preferences and needs.In conclusion, predicated data is an essential concept in today’s data-driven society. Whether in retail, healthcare, technology, or business strategy, the ability to base decisions on well-founded predictions can significantly impact outcomes. As we continue to rely more heavily on data, understanding the nuances of predicated data will become increasingly important. Organizations must ensure that their data is not only accurate but also predicated on realistic assumptions to navigate the complexities of their respective fields successfully.

在现代社会，数据在各个领域的决策过程中发挥着至关重要的作用。一个在数据分析领域中显得尤为重要的概念是predicated data。这个术语指的是基于某些假设或条件的信息。理解predicated data对于个人和组织来说至关重要，因为它使他们能够基于可靠的预测和分析做出明智的决策。为了说明predicated data的重要性，考虑一个零售公司为即将到来的假日季节计划库存的例子。管理团队可能会分析历史销售数据以预测未来需求。然而，这种分析通常是基于各种因素，比如经济条件、消费者趋势，甚至天气模式。如果公司假设去年的销售将直接与今年的表现相关，而不考虑这些影响因素，他们可能会导致产品过剩或不足。此外，在医疗保健领域，predicated data也很重要。例如，医学研究人员在进行临床试验时通常依赖于predicated data。他们根据现有研究制定假设，然后收集数据来支持或反驳这些假设。通过这样做，他们可以更好地理解新治疗方法或药物的有效性。如果收集到的数据没有基于合理的科学原则，则结果可能会导致误导性的结论，可能会对患者造成伤害并浪费资源。在技术领域，predicated data同样重要。例如，机器学习算法通常基于某些参数的predicated data进行工作。这些算法从历史数据中学习，以预测未来事件。如果输入系统的初始数据存在缺陷或基于错误的假设，则算法所做的预测可能不准确。因此，确保predicated data的完整性在开发有效的人工智能系统中至关重要。此外，企业还利用predicated data进行战略规划。当进入新市场时，公司通常依赖于预测消费者行为的市场研究，这些研究基于人口统计数据、购买趋势和文化因素。如果这些预测没有扎根于现实，制定的商业战略可能会失败。例如，一家科技公司可能仅基于其在另一个地区的成功假设某个小工具在新地区会受到欢迎，而没有考虑当地的偏好和需求。总之，predicated data是当今数据驱动社会中的一个重要概念。无论是在零售、医疗保健、技术还是商业战略中，基于良好预测做出决策的能力都能显著影响结果。随着我们越来越依赖数据，理解predicated data的细微差别将变得愈加重要。组织必须确保他们的数据不仅准确，而且基于现实的假设，以成功应对各自领域的复杂性。