Web data scrapping is becoming more and more important as data analysis becomes more powerful these days. But the power of data manipulation is not fair to everyone. But it takes a lot of effort to get the ability to handle the data.
Many people want to know how to learn how to deal with data well. Data-related capabilities range from collection and analysis to application development.
If you want to become a data professional, you will of course have to enroll in a graduate school or take a separate professional education. But one of the most common questions we have is whether a typical marketer, business majors, and managers should learn a programming language like Python to handle data.
If you are considering web data collection and general analysis, our answer is clearly 'No, you do not have to'.
Especially recently, there are web data scraping tools optimized for light users like Listly.io, and various commercial services such as Diffbot, Import.io, and Octoparse.
If data is not your primary task, we recommend using commercial services. The functions are getting stronger day by day. If you are thinking about more complex tasks or future careers, it's good to learn Python. However, the most popular tool for data utilization is MS Excel.
Even if you learn more about professional programming later in the year, data-driven practice with Excel will be a good starting point. Rather than challenge yourself from scratch, it is recommended to look for the right tool for your task.