Full analysis of cross-border e-commerce big data collection and processing technology
In the context of the rapid development of cross-border e-commerce, data collection and processing are particularly important. This article will comprehensively analyze these technologies from multiple aspects such as big data collection and preprocessing, self-programmed crawler scripts, enterprise information collection, product information collection, and API collection.
1. Big data collection technology
Big data is massive data obtained through multiple channels, including RFID data, sensor data, social network interaction data, etc. This data can be structured, semi-structured or unstructured. Big data collection is mainly divided into two levels:
- Intelligent sensing layer: Realizes intelligent identification and management of data, including data sensing system, network communication and intelligent identification, etc.
- Basic support layer: Provides virtual servers and related databases to solve data storage, processing and reliability issues.
2. Big data preprocessing technology
Big data preprocessing mainly completes data analysis, extraction and cleaning. Clean the collected data to remove worthless or erroneous data and extract valid data for later analysis.
3. Collection of own programming crawler scripts
Self-programmed crawler scripts are a technology for automatically capturing data, especially suitable for highly repetitive monitoring work. Users can download and configure the corresponding crawler program and set up Excel tables to store the captured data. After running the program, users need to ensure that the Excel file is closed to avoid data capture errors. This method is suitable for large-scale competitor product data collection.
4. Collection of cross-border e-commerce enterprise information
Enterprise information collection covers industrial and commercial certification information and company information. Specifically include:
- Industrial and commercial certification information: business license, business address, certifier and other information.
- Company information: basic information, R&D and design, processing and manufacturing capabilities, foreign trade export capabilities and display information, etc. This information not only shows the strength of the company, but is also an important basis for buyers to select suppliers.
5. Collection of cross-border e-commerce product information
Product information collection is an important part of store infrastructure construction, which mainly includes the arrangement of basic information and product pictures. This information can help increase the visibility and competitiveness of products on the platform, and improve the efficiency of users’ purchasing decisions.
6. API collection method of data collection
By calling the API provided by the website, efficient data collection can be achieved. Use open authentication protocols such as OAuth to obtain user data. API collection not only helps solve the problem of data targeting, but also retrieves relevant data in a clear data structure (such as JSON or XML format), which is very convenient for subsequent processing.
7. Web crawler method for cross-border e-commerce data collection
Web crawlers are divided into general and focused crawlers according to different needs. General crawlers crawl web page information through links, while focused crawlers focus on information on topic-related web pages. This selective crawling method can improve the efficiency of data collection and reduce resource consumption.
Through the integration and analysis of the above aspects, cross-border e-commerce companies can be more efficient and comprehensive in data collection and processing, thereby improving their market competitiveness and decision-making support capabilities.