Data Parsing vs Data Scraping: Which Do I Need?

Scraping Robot
September 24, 2021

If your business relies on data scraping, you’ve probably come across the term “data parsing”. The term can be confusing, especially since it’s sometimes used interchangeably with data scraping. While the two processes are interrelated, they are not the same.

Table of Contents

Data scraping is the process of extracting data from another program or website. Data parsing, meanwhile, is the process of converting data into a readable format so that you can begin to use it.

Businesses can create their own data parsing tools, or they can buy one ready-made — Scraping Robot is a great example of a ready-to-use tool that does both scraping and parsing. Want to learn more about data parsing? This article will get into the difference between data parsing and data scraping and will define parsing data. We’ll also look at the pros and cons of building your own data parsing tool.

If you’re looking for certain information, use the table of contents to jump ahead to a section.

What Is Data Parsing?

what is data parsing

W‌hat does it mean to parse data? You can think of data parsing as the step that comes immediately after data scraping. Once you have received data, your data parser takes that data and transfers it into a format that your network can use.

In a way, a data parser is like a translation tool. It allows you to parse information that’s in various formats and translate it into a format that your systems can work with. It does this by breaking data down into its component parts so that it can be easily reconfigured and reformatted.

You may be familiar with grammatical parsing. If you can think back to high school English classes, you may remember having to parse sentences by breaking them down into their component parts. You did this by identifying verbs, nouns, adjectives, and so forth.

Similarly, a data parsing tool identifies the important components of a string of data.

In many cases, you’ll be taking in scraped data in raw HTML format. You’ll need to parse that data so that your teams can put it to use. Of course, this is a very broad explanation of what is actually a complex process.

What Exactly Does a Data Parser Do?

what does parsing data mean

A good data parser can read a string of raw HTML data and decide what parts of that information are valuable. The parser can then isolate that information and convert it into a usable format.

In other words, a data parser doesn’t simply convert from one format to another — it collects valuable data and transfers it into a format that fits with the rest of your network.

Do I Need a Data Parser or a Data Scraper?

Data parsing and scraping

You need to have both a data parser and a data scraper. The two work together to make it so you can effectively collect and use data. The data scraper extracts data, and the data parser puts that information into a useable format.

If you’re building your own tool, you will need to build in both capabilities. If you’re buying a ready-made tool, look for one like the Scraping Robot that already has the means to do both.

The Pros and Cons of Building Your Own Data Parser

plus and minus of Data parsing

Many businesses ask themselves whether it makes more sense to build their own data parser or to buy a ready-made one.

That’s a complicated question — and there really isn’t any one correct answer. The truth is that it depends on many different factors, including your business model, your budget, and your employees. This is a highly individual decision.

Still, it’s a good idea to look at the pros and cons of each possibility.

The Pros of Building Your Own Parser

One of the biggest pros to building your own parser is that you can customize it to meet your exact needs. You’ll also be able to decide when to update your machine and how often it needs to be maintained and adjusted.

Building your own machine is generally lower-cost than buying a ready-made machine, so you’ll be able to meet the requirements of a lower budget if you go that route.

However, every solution has a downside — and building a parser is no exception.

The Cons of Building Your Own Parser

‌Your in-house technical team may not have the know-how to build the parser. This means that the process could be quite time-consuming. It may involve extensive training sessions or even making a series of new hires. You will also need to train your team to maintain the parser — and you’ll need to dedicate a certain number of hours to maintenance.

If you do spend a lot of time training your team or hiring new staff, building a parser could end up being quite expensive for your business. You will also need to make sure that your non-technical staff works closely with your IT team to make sure that the data parser has the right specifications.

This can end up costing you even more in terms of labor since it means that more of your staff will be spending time on this project instead of focusing on their normal work.

You may also need to buy a new, dedicated server that’s capable of parsing data rapidly.

Building your own parser might be a good idea if you already have the staff and the equipment to handle this kind of undertaking. If you don’t, this project could end up eating up a lot of time and money — especially if you need to hire new staff or spend a significant amount of time training your existing staff.

The Pros and Cons of Buying a Ready-Made Data Parser

define parsing data

Many businesses choose to buy a data parser since this eliminates the need to build up technical capabilities in-house.

The Pros of Buying a Data Parser

Unlike when you build a data parser, buying a ready-made robot can save you money on labor and equipment. That’s because when you buy the product ready-made, you won’t need to spend time and money training your staff or hiring new employees to help build and maintain your tool.

You also won’t need to spend money on new equipment, like a costly server. The company you work with will take care of all of that. They’ll even carry out regular maintenance of your data parser.

There is a heap of benefits from investing in a tool that parses your data for you.

You’ll have the benefit of working with people who know exactly what they’re doing and who have extensive experience working on exactly this issue. This means that you can count on a team to resolve bugs and wrinkles quickly instead of those problems turning into a nagging, time-consuming source of stress for you and your team.

It also means that you can expect your data parser to work reliably and easily, instead of periodically crashing or having problems. There’s a lot of upside to working with an experienced team.

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. Having an effective, reliable data parser means that it will be easier for your whole team to start using it comfortably.

The Cons of Buying a Data Parser

No solution is perfect, and there are some downsides to buying a data parser.

You can expect it to be more expensive than building a parser. However, shopping around to find a high-quality, budget-friendly solution can make a big difference to your bottom line.

You may not able to customize it quite as much. You won’t be able to decide exactly when it needs maintenance or what features would make it perfectly adapted to your needs.

However, this is also something that depends on which company you decide to work with. If you choose a firm with both experience and flexibility, you can still get a product that is well-tailored to your set of needs.

Final Thoughts

Data parsing

Data scraping and parsing are complex activities which take both time and investment to carry out efficiently.

For some businesses, it might make sense to take care of the whole process in-house. But for many enterprises, it makes far more sense — both on a budgetary level and in terms of HR considerations — to hire a dedicated team to build a data scraping and parsing tool.

The Sprious Scraping Robot offers users a fully customizable experience for an affordable price. Just tell the team at Sprious what kind of data you need to extract and how often you’ll need it.

For example, you may want to collect data from a leading eCommerce business or different social media sites. The possibilities are endless.

Scraping Robot can be configured to extract precisely the kind of data you’re interested in — whenever you need it. The robot also parses metadata for you. It’s a hassle-free solution that can get you quick results.

Get in touch today to learn more about what the Scraping Robot can do for you and your business.

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