Web scraping, also known as web data extraction, is the process of collecting structured web data in an automated fashion. As data volumes continue growing exponentially, web scraping has become an essential skill for data engineers.
Data engineers build and maintain data pipelines that acquire data from various sources, transform and cleanse it, and load it into databases and data warehouses. While many pipelines connect to internal databases or REST APIs, the open web contains a treasure trove of valuable data. Web scraping enables data engineers to efficiently collect this data.
Why Web Scraping is Useful for Data Engineers
Here are some examples of why web scraping is an important data engineering skill:
Web scraping helps data engineers acquire external data sources, enrich existing analytics, and identify new business opportunities.
Web Scraping Challenges
However, web scraping brings unique development and maintenance challenges:
Web Scraping Best Practices
Here are some tips for reliable, scalable web scraping:
With the right precautions, web scraping can supply data engineers with fertile, up-to-date data to drive impactful analytics. While challenging, web data extraction is an invaluable skill for unlocking unique datasets.