Summarizing and extracting relevant information and knowledge from big data can help people analyze what is happening and present the characteristics and trends of things.

1. Big data can provide us with a rich source of data that allows us to understand a phenomenon or problem more comprehensively. For example, when analyzing the traffic situation in a region, we can use traffic flow data, road condition data, weather data, etc. to get a comprehensive understanding of the region's traffic situation and predict future traffic trends.

2. Big data can provide us with in-depth data analysis capabilities. Through data mining, machine learning and other technologies, we can extract useful information and knowledge from big data, and analyze and summarize them. For example, when analyzing a company's sales data, we can use the data to analyze sales trends, customer preferences, and so on, which can help the company better formulate sales strategies.

3. Big data can also help us present the characteristics and trends of things. Through data visualization technology, we can present data in the form of charts, images, and so on, so as to more intuitively understand the distribution and change of data. For example, when analyzing global climate change, we can use the temperature, rainfall and other data to create a global climate change chart, so as to more intuitively understand the trend of global climate change.

Origin of Big Data:

The origin of Big Data can be traced back to the 1960s and 1970s, when the U.S. Department of Defense began collecting and storing large amounts of data to support military decision-making. The volume of this data was so large that it exceeded the limits of computer processing power at the time, so scientists began to explore new data processing and analysis techniques, such as distributed computing and data mining.

With the popularization of the Internet, mobile devices, and the Internet of Things (IoT), the amount of data generated began to explode. Applications such as social media, e-commerce, online video, etc. generate a large amount of user data, which includes users' personal information, behavioral data, location information, and so on.

Enterprises are also beginning to collect and store large amounts of transaction data, customer data, and so on. These data provide important support for business decisions and also provide valuable data resources for scientific research.

In recent years, with the rapid development of artificial intelligence and machine learning, the application value of big data has been more y excavated. Machine learning algorithms can use big data for training and learning, thus realizing automated analysis and processing of data, further improving the efficiency and accuracy of data processing and analysis.