Data science has become a big part of today’s world. Many big tech companies have data scientists on their teams to help develop their products and services.
Data science allows companies to constantly create innovative products that we consumers will spend money on and is worth millions and even billions.
Technology like virtual assistants like Alexa, Siri and Google have changed the way consumers live.
We’ll discuss what web scraping is and how it can improve data science.
What is web scraping?
Web scraping refers to the extraction of data from a website. This information is collected and then exported into a format that is more useful for the user. Be it a spreadsheet or an API.
But in most cases, web scraping is not a simple task. Websites come in many shapes and forms, as a result, web scrapers vary in functionality and features.
There are many things you can do with the extracted data from web scraping like:
Competitor research: Get an insight on how your competitors are pricing their products or find what keywords they are targeting.
Industry insights: You can scrape articles, stocks, prices to understand how well a particular industry is performing.
Generate leads: Many web scrapers will scrape online directories to find businesses that are in their target market and create a list to reach out
Gather data for research: some big data websites and libraries have data you need for your research, you can scrape these websites and export them to have them on file
Financial data: you can scrape financial data like stocks, income statements, balance sheets and stock news.
If you would like to learn more about what is web scraping, you can click here.
What is data science?
Data science refers to the use of methods, processes and systems to extract knowledge and data from both structured and unstructured data.
Computer scientist William S. Cleveland combined both computer science and data mining to make statistics more tactical. This allowed humans to use the power of computers to collect valuable data that can be used for research.
Many tasks need to be done in data science to be conducted properly like collecting, analyzing, storing data, A/B testing and many more.
Read more on what is data science?
Is web scraping part of data science?
Web scraping helps data scientists collect online data more efficiently and is an important skill data scientists need. Since data science includes collecting online data, many data scientists will use some sort of web scraper to help them. Web scraping can be both manual and automated, but automated web scrapers will get the job done faster and more effectively.
There’s a lot of data that is publicly available that can be used for data science purposes. Big data websites and libraries like DAta.gov Data Description and Amazon Public data sets allow you to extract data that can be related to your topic.
You can scrape e-commerce websites to gather data on product development. Websites like Amazon, Walmart and eBay can be scraped to find product data.
You can extract data from any website that can be related to your research. For example, say you want to research what makes a perfect product. You can scrape product reviews and then organize your data to see what users like and dislike about certain products.
Some companies and software engineers will create their web scrapers from scratch. That’s how important web scraping is for data science.
Web scraping is a crucial part of data science. It was one of the many tools you will need to collect online data efficiently and effectively. Since one of the first steps to analyze data is to collect it, web scraping can make the first job done easier.
While there are many web scraping tools available, we think you’ll enjoy ParseHub! Not only is it free to use, but has many suites of features we think you’ll enjoy like:
- Easy to use
- Powerful and scalable
- Cloud-based scraping
- Export options
- Many more features
- Great customer support
- Many more
You can download ParseHub for free to get started right away.
How will you use web scraping for data science?