What Is Data Parsing?

Oxylabs - Jun 16 '22 - - Dev Community

Here’s a question to all the fellow developers: have you ever come across the data parsing term? We bet it rings a bell. Either way, to put it simply, it’s a process when one data format is transformed into another, more readable data format.

For those who aren't much familiar with the term or are curious to learn more, we prepared an article in which we investigate data parsing in programming and discuss which way is more beneficial – building an in-house data parser yourself or buying a ready-to-use tool that’ll do the job for you.

And, if you’d rather watch a video instead of reading the whole thing, we’ve got your back:

What is data parsing?

So, let’s get into it. As we already mentioned, data parsing is a method where one string of data gets converted into a different type of data. Say you receive your data in raw HTML – a parser will take the said HTML and transform it into a more user-friendly data format that you can easily read and interpret.

What does a parser do?

A well-made parser will distinguish which information of the HTML string is needed, and in accordance with the parser’s pre-written code and rules, it will pick out the necessary information and convert it into JSON, CSV, or a table, for example.

We’d also like to mention that a parser itself is not tied to a data format. It’s a tool that converts one data format into another; how it converts it and into what depends on how the parser was built.

Parsers are used for many technologies, including:

  • Java and other programming languages

  • HTML and XML

  • Interactive data language and object definition language

  • SQL and other database languages

  • Modeling languages

  • Scripting languages

  • HTTP and other internet protocols

To build or to buy?

Now, when it comes to the business side of things, an excellent question to ask yourself is, “Should my tech team build their own parser, or should we simply outsource?”

As a rule of thumb, it’s usually cheaper to build your own rather than to buy a premade tool. However, this isn’t an easy question to answer, and a lot more things should be taken into consideration when deciding to build or buy.

Let’s look into the possibilities and outcomes of both options.

Building a data parser

Let’s say you decide to build your own parser. There are a few distinct benefits of making this decision:

  • A parser can be anything you like. It can be tailor-made for any work (parsing) you require.

  • It’s usually cheaper to build your own parser.

  • You’re in control of whatever decisions need to be made when updating and maintaining your parser.

But, like with anything, there’s always a downside to building your own parser:

  • You’ll need to hire and train a whole in-house team to build the parser.

  • Maintaining the parser is necessary – meaning it’ll cost you more effort and time.

  • Finally, you’ll need to buy and build a server that will be fast enough to parse your data at the speed you need.

Being in control isn’t necessarily easy or beneficial – you’ll need to work closely with your team to make the right decisions. Only this way can you create something good – by spending a lot of your time planning and testing.

We’re not saying you shouldn’t do this – after all, building your own has its benefits. But before you proceed, keep in mind that it takes a lot of your resources and time especially if you need to develop a sophisticated parser for parsing large volumes. That will require more maintenance and human resources, and valuable human resources because building one will require a highly-skilled developer team.

Buying a data parser

So what about buying a tool that parses your data for you? Let’s start with the benefits:

  • You won’t need to spend any money on human resources, as everything will be done for you, including maintaining the parser and the servers.

  • Any issues that arise will be solved a lot faster, as the people you buy your tools from have extensive know-how and are familiarized with their technology.

  • You’ll save a lot on human resources and your own time, as the decision-making on how to build the best parser will come from outsourcing.

Of course, there are a few downsides to buying a parser as well:

  • It will be slightly more expensive.

  • You won’t have too much control over it.

Now that you know all the benefits and downsides of each option, one thing that’s left is to choose. It all comes down to what sort of parser you’ll need. An expert developer can make an easy parser probably within a week. But if it’s a complex one, it can take months – that’s a lot of time and resources.

It also falls on whether you’re a big business that has a lot of time and resources on their hands to build and maintain a parser. Or you’re a smaller business that needs to get things done to be able to grow within the market. All that said, both options can be great; it just depends on your individual situation.

Wrapping up

As a final note, we’d like to advise you to consider whether you’re building a very sophisticated parser or not. If you are parsing large volumes of data, you will need good developers on your team to develop and maintain the parser. But, if you need a less complicated, smaller parser or have a team of experienced engineers, probably best to build your own.

Also, be mindful if you are a large company with a lot of resources, or a smaller one, that needs the right tools to keep things growing.

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