data stream

data stream：/ˈdeɪtə striːm/

音标翻译：数据流。

速记技巧：可以尝试使用一些速记方法来帮助记忆，比如将“data”看作是“device”（设备），“stream”看作是“stream”（流），那么整个单词就可以理解为“设备在流动数据”。此外，还可以通过联想记忆法来帮助记忆，比如将“data”和“dust”（灰尘）联系起来，想象数据就像灰尘一样在流动。

希望这些信息对您有所帮助！

Data stream:

英文词源: "data" 意为 "information" 或 "informational material"；"stream" 意为 "flow" 或 "current", 因此 "data stream" 意为 "information flow" 或 "information current"。

变化形式: 无特殊变化。

相关单词:

1. Data flow: 意为 "information flow" 或 "flow of informational material", 与 data stream 同源。

2. Streamline: 意为 "to make smooth and streamlined", 用于形容物体或流程的简化、流畅。

3. Current: 意为 "flowing current", 与 data stream 同源，形容流动的状态。

4. Flux: 意为 "flowing or changing", 与 data stream 同源，形容变化的状态。

5. Information stream: 意为 "stream of information", 与 data stream 同源，强调信息的流动。

6. Data analytics: 意为 "analysis of informational data", 与 data stream 相关，用于处理和分析数据流。

7. Data visualization: 意为 "visual representation of informational data", 与 data stream 相关，用于数据可视化的技术。

8. Stream of consciousness: 意为 "stream of thoughts and feelings", 与 data stream 相关，用于描述信息的流动和人的意识状态。

9. Data integration: 意为 "integration of informational data", 与 data stream 相关，用于数据整合和数据融合的技术。

10. Data mining: 意为 "mining of informational data for patterns and trends", 与 data stream 相关，用于数据挖掘的技术。

常用短语：

1. data stream processing

2. real-time data analysis

3. streaming analytics

4. continuous data stream

5. data stream mining

6. streaming data science

7. data stream modeling

例句：

1. The company is dedicated to data stream processing and real-time data analysis.

2. Streaming analytics is essential for optimizing business operations in the digital era.

3. Continuous data streams provide valuable insights for decision-making.

4. Data stream mining helps companies identify trends and patterns in vast amounts of data.

5. Data stream modeling is critical for monitoring and predicting future trends in the market.

英文小作文：

Data Streams: The New Frontier of Analytics

In today"s digital age, data streams have become an integral part of our daily lives. From social media to real-time sensor data, information is constantly flowing at an unprecedented rate. This presents a unique challenge for data analysts, as they must now deal with vast amounts of real-time data in a timely and effective manner. Data stream processing, real-time data analysis, streaming analytics, continuous data streams, data stream mining, streaming data science, and data stream modeling are all essential tools in the modern data scientist"s toolbox. These techniques allow for the identification of trends, patterns, and insights that were previously unavailable in traditional batch processing systems. From optimizing business operations to detecting fraudulent activities, data streams have the potential to transform the way we approach analysis and decision-making. As technology continues to advance, we can expect to see more and more applications of data streams in the coming years. Data streams are not just a trend, they are the new frontier of analytics, where speed, accuracy, and innovation converge to create a more informed and sustainable world.