The entire modern world revolves around data and data analysis. Companies, businesses, and private organizations all use data to identify weak points and extract useful information that will help increase efficiency. However, with so many different types of data, handling so much information isn’t easy.
That’s why organizations use all kinds of techniques to improve their efficiency. One of them is called data parsing. It’s a process of transforming data from one format to another, and it’s got a massive application in web scraping, data extraction, and other practices. Stay with us, and we’ll explain how everything works in more detail.
Definition of Web Scraping
Web scraping is a technique used by companies, businesses, and private users who need to find and extract specific information. It allows users to scan a webpage, an entire website, or multiple websites at the same time, looking for information. It’s a simple software tool that allows you to search for terms based on a keyword. All of the information that fits with the keyword is then extracted in a readable spreadsheet format.
The practice is commonly used to monitor prices and competition, find helpful information, extract specific data, gather user reviews, and so on. It’s a very powerful tool, and with the right calibration, it can help you get a lot of useful information.
How The Process Works
The web scraping process is relatively simple, and you don’t need a lot of previous experience to find and extract information successfully. Once you find the best web scraping tool for your needs, you have to provide the URL of the website you want to scrape and the keywords you want it to search for.
The web scraper will then scan the entirety of the site and extract only the information that matches your request. All of the data is then gathered and turned into a readable spreadsheet format. Web scraping is able to extract huge amounts of data in a matter of seconds. Doing the same thing manually would take days, maybe even weeks, to complete, which is why these tools are so popular today.
What Is Parsing
Many people are asking the question about what parsing is, and the answer is simple. Data parsing is a method used to transform one type of data into another. For example, it can help you scan raw HTML data and turn it into a readable format everyone can understand. The type of data it can work with depends on the programming and the software itself, but most tools can easily turn HTML data into JSON, CSV, or table.
A data parser can help organize the extracted data even better than ever before when paired with a web scraper. That’s an important step of the process, as you want to find as much helpful information as possible. Data parsers can help you improve the overall quality of the data by providing you a better overview of every detail.
Challenges of Data Parsing
Just like any other practice, data parsing comes with a set of unique challenges that have to be overcome to get the most out of extracted data. Here are a few standard challenges you’ll meet on the way.
1. Handling Missing Values
Sometimes, you’ll encounter data with missing values, making it impossible to implement your findings with the rest of the data. After you’ve identified all instances where some data is missing, you can either drop missing values or fill them in manually if it makes sense.
2. Scaling
Not all projects require the same amount of data handling, which means that sometimes you’ll have to scale up your operation to crunch all of the numbers. With some basic coding and a few good ideas, you can prepare the parser for any type of project.
3. Parsing dates
Most data parsers allow you to sort data from and to a specific date. For example, you can use a web scraper to find data between the years 2015 and 2017, and the parser will structure everything for you. More data means more issues for the software.
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Possible Solutions
The most important thing to consider when using data parsers is the correct setup. It might take a few tries until you manage to configure the tool to display the data the way you want. Most available software is relatively easy to set up, but if you need data parsers for large amounts of data, you might have to hire a programmer to set up the environment specifically to your needs.
Conclusion
Data parsing and web crawling paired together offer the best data quality during extraction. With the proper setup and structure, you will be able to generate extremely useful reports that will help you improve your entire operation.
