The importance of data in this digital age grows every day. More businesses rely on data to make important decisions that could impact the company’s functioning. These days it’s almost impossible for a business to become successful without data. Even the most fundamental aspects, such as creating your business plan, rely on data. Not to mention the data needed for market research, cost analysis, pricing intelligence, and much more.
The problem is that most data collected from the web is not readable. When tools collect data, they do so in HTML or code snippets, which will not make sense. That is where data parsers come into play.
This article looks at what parsing is, how it is used, and some of the challenges you may encounter. We’ll also touch on tools you can use with a data parser, such as proxies from providers like Smartproxy.
What Is Data Parsing?
Data parsing is the process of converting data from one format into another. Most of the data that is collected or extracted from online sources appear in a format that cannot be read. A data parser can take that data and change it into another format so that it can be used. Traditional data parsing is where data is collected from websites in a code or HTML format and is then converted to readable text.
Data parsing is a critical process in collecting data because the raw data is not very useful without a parser to convert it. It is also essential to know that a parser does not collect data itself. This is a different process done by scrapers. The parser also can’t read, understand or analyze the collected and converted data. This is why it is used with other tools such as web scrapers and a proxy parser for best results.
Types of Data Parsing
When it comes to the different data parsing techniques, there are two that are used. These are the top-down and bottom-up techniques. The reason for the two different techniques is that they deliver slightly different results. When using these tools, we also recommend using a proxy parser to ensure that you collect and parse data from behind the safety of a proxy. This will also reduce the chances of bans, which means you can collect and parse more data.
Let’s look at the difference between these two parsing types.
Top-Down Parsing
This process starts at the top of the parsing tree and works its way down. The top-down technique focuses on the main topic first and then works towards the smaller problems. The top-down technique will display more information, some of which may be repetitive depending on the data source.
Bottom-Up Parsing
Bottom-up parsing starts at the bottom of the parsing tree and works to the top going from right to left. This technique also focuses on the smaller problems first and then fills in the bigger part of the context. As such, this technique is faster than top-down parsing, but you may only get the core parts of the data rather than everything.
Uses of Data Parsing
Although the term data parsing is often used when referring to web scraping, the reality is that it’s used a lot more. Yes, parsing forms a critical part of web scraping, but it also forms an essential part of many other online processes. Here are a few more technologies where data parsing is also used.
- Used with the scripting language of games, web apps, plugins, and extensions.
- Used with modeling languages used by system analysts and developers.
- Used with HTML from web pages and application creation.
- Used with interactive data language.
- Used with SQL programming languages for content management.
- Used with HTTPS and Internet Protocols responsible for data communication across the internet.
Challenges of Data Parsers
As with other forms of technology, parsers face their own challenges. One of the parsers’ biggest challenges is how quickly programming languages, web layouts, and other online aspects change. These constant changes can cause parsers to break and return parsing errors. As such, the parser must be updated and adjusted frequently.
These updates and changes are simple for coders to implement, but they do take time. Many businesses do not have the resources to appoint individuals to constantly monitor the parsers, and even Junior Programmers might find this task beneath their skill level if they wish to progress. This is where an already-built parser has an advantage as most of them come with support and frequent updates.
Final Thoughts
Data parsing is an essential process, not only when collecting data by using a web scraper and proxy parser, but in many other uses of the web. Without parsing tools, we would not be able to see and read the content on the web without being able to read and translate complex code. Parsers are responsible for taking the code and transforming it into a format that we can understand.
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