batch data processing

简明释义

成批数据处理

英英释义

例句

1.The company uses batch data processing to analyze large sets of sales data at the end of each month.

公司在每个月底使用批量数据处理来分析大量销售数据。

2.The IT team implemented batch data processing to reduce the load on the database during business hours.

IT团队实施了批量数据处理，以减少工作时间内数据库的负载。

3.Using batch data processing, we can automate the generation of monthly reports.

通过使用批量数据处理，我们可以自动生成月度报告。

4.The system is designed for batch data processing, allowing it to process thousands of transactions at once.

该系统设计用于批量数据处理，能够一次处理数千笔交易。

5.With batch data processing, we can efficiently handle user registrations during peak times.

通过批量数据处理，我们可以高效地处理高峰时期的用户注册。

作文

In today's digital age, organizations are inundated with vast amounts of data. To effectively manage and analyze this information, many companies turn to various data processing techniques. One such technique is batch data processing, which involves processing large volumes of data in groups or 'batches' rather than individually. This method can significantly enhance efficiency and reduce the time required for data handling. 批处理数据处理是一种将大量数据分组或“批量”处理的技术，而不是逐个处理。 The primary advantage of batch data processing lies in its ability to handle extensive datasets without overwhelming the system's resources. For instance, when a company needs to process customer transactions at the end of the day, it can collect all the transaction data throughout the day and process it in one go during off-peak hours. This not only optimizes resource usage but also ensures that the system remains responsive for other critical tasks during peak hours. 批处理数据处理的主要优点在于能够处理大量数据而不使系统资源过载。 Another significant benefit of batch data processing is its cost-effectiveness. By processing data in batches, organizations can minimize operational costs associated with continuous data processing. Continuous processing often requires more sophisticated hardware and software solutions, which can be expensive. In contrast, batch data processing allows companies to utilize simpler systems while still achieving their data processing goals. 批处理数据处理的另一个重要好处是其成本效益。 Moreover, batch data processing is particularly useful for applications where real-time processing is not crucial. For example, payroll systems typically operate on a monthly basis, where employee hours are collected and processed together at the end of the month. This approach simplifies the processing requirements and allows for easier error correction since all data is reviewed collectively. 批处理数据处理特别适用于实时处理不是关键的应用程序。 However, batch data processing is not without its challenges. One major drawback is the latency involved in processing data. Since data is only processed at specific intervals, there can be delays in obtaining critical information. For industries that rely on real-time data, such as finance or e-commerce, this can pose significant issues. Organizations must carefully assess their data processing needs to determine if batch data processing is suitable for their operations. 批处理数据处理并非没有挑战。 In conclusion, batch data processing is a valuable technique for managing large datasets efficiently and cost-effectively. By processing data in batches, organizations can optimize their resources, reduce costs, and simplify their operations. However, it is essential to consider the potential drawbacks, such as processing latency, when determining the best approach for data management. As technology continues to evolve, the role of batch data processing will likely remain significant in the landscape of data analytics and management. 批处理数据处理是一种有效管理大型数据集的宝贵技术。 Ultimately, understanding the intricacies of batch data processing and its implications can help businesses make informed decisions about their data strategies. By leveraging this method appropriately, organizations can harness the power of their data while maintaining operational efficiency. 批处理数据处理的复杂性及其影响可以帮助企业就其数据策略做出明智的决策。

在当今数字时代，组织面临着大量数据的涌入。为了有效地管理和分析这些信息，许多公司转向各种数据处理技术。其中一种技术是批处理数据处理，它涉及将大量数据分组或“批量”处理，而不是逐个处理。这种方法可以显著提高效率，减少数据处理所需的时间。批处理数据处理是一种将大量数据分组或“批量”处理的技术，而不是逐个处理。批处理数据处理的主要优点在于能够处理大量数据而不使系统资源过载。例如，当一家公司需要在一天结束时处理客户交易时，它可以在一天内收集所有交易数据，并在非高峰时段一次性处理。这不仅优化了资源使用，还确保系统在高峰时段能够保持对其他关键任务的响应能力。批处理数据处理的主要优点在于能够处理大量数据而不使系统资源过载。此外，批处理数据处理具有成本效益。通过批量处理数据，组织可以最小化与持续数据处理相关的运营成本。持续处理通常需要更复杂的硬件和软件解决方案，这可能很昂贵。相比之下，批处理数据处理允许公司利用更简单的系统，同时仍能实现其数据处理目标。批处理数据处理的另一个重要好处是其成本效益。此外，批处理数据处理特别适用于实时处理不是关键的应用程序。例如，工资系统通常按月运行，在月底时收集员工工时并一起处理。这种方法简化了处理要求，并且由于所有数据都是集体审查的，因此更容易纠正错误。批处理数据处理特别适用于实时处理不是关键的应用程序。然而，批处理数据处理并非没有挑战。一个主要缺点是处理数据的延迟。由于数据仅在特定间隔内处理，因此获取关键信息可能会有延迟。对于依赖实时数据的行业，如金融或电子商务，这可能会带来重大问题。组织必须仔细评估其数据处理需求，以确定批处理数据处理是否适合其运营。批处理数据处理并非没有挑战。总之，批处理数据处理是一种有效且具有成本效益的管理大型数据集的技术。通过批量处理数据，组织可以优化其资源、降低成本并简化其运营。然而，在确定最佳的数据管理方法时，考虑潜在的缺点，例如处理延迟，是至关重要的。随着技术的不断发展，批处理数据处理在数据分析和管理领域中的作用可能仍将显著。最终，理解批处理数据处理的复杂性及其影响可以帮助企业就其数据策略做出明智的决策。通过适当地利用这种方法，组织可以利用其数据的力量，同时保持运营效率。批处理数据处理的复杂性及其影响可以帮助企业就其数据策略做出明智的决策。