What Is Web Scraping!!
There are many names by which Web Scraping is also known, depending on how an organization calls it. Screen Scraping, Web Data Extraction or Web Harvesting and many more. It is a technique that required to extract large amounts of data from websites. This data extracted from different websites and repositories and saved on local servers for immediate use or analysis purposes later. Data saved to a database table or in a local file system, according to the structure of the data extracted. Almost all the websites that we see regularly only allow us to see the contents and don’t let us copy or download. Copying the data is a terrible idea and can take days and weeks. Web Scraping is the technique of automating this process so that an intelligent script can help you extract data from different web pages. You choose and save them in a structured format.
A web scraping software loads many web pages one by one and extracts the data according to the specified need. It can be either custom-built software for a specific website or it can also be one. Which when configured based on a set of specified parameters which works on any website. Within a click of a button, the data available on a website saved to your computer.
In the modern era, intelligent bots do web scraping. Unlike the screen scraping process. Which only copies whatever pixels displayed on the screen. these bots extract the underlying HTML code, as well as the data stored in the background.
Important Benefits Of Web Scraping:
1. Scraping The Product Details And Prices
Businesses crawl eCommerce websites for prices, product descriptions, and images to get all the data possible which can boost analytics and predictive modeling. Price comparison in the present years has made it very important for every business to know the rates of its competitors. Unless the rates are competitive, e-commerce websites have to shut their shops. Even travel websites extract prices from airlines’ websites for a long time. Custom web scraping solutions help you get the variable data fields that you will need. In this way, you can extract data and create your data warehouse, for current and future use.
2. One Can’t Hide On The Internet:
This helps in getting the data related to any individual or any company which is later on used for analysis, comparisons, investment decisions, hiring, and other purposes. Many companies scrape job boards for such use cases.
3. Custom Analysis And Curation:
This is only for new websites/channels where the scraped data can help understand public demand and their behavior. It helps new companies, to begin with, activities and products based on pattern discoveries. Which in return gives more organic visits. This way, they can afford to spend less on advertisements.
4. Online Reputation:
Online reputation is very important in today’s date as many businesses depend on word of mouth channels to grow. Scraping from social media sites helps to understand current public opinion and sentiments. Then the company can do small things that have a big social impact. Opinion leaders, trending topics and demographic facts highlighted through web scraping. And these can be later used to make sure that the company can repair its image. Or have a greater online “public-satisfaction score”.
5. Detecting Fraudulent Reviews:
Online reviews influence the new generation online-shoppers decision on what to buy, and where to buy from, be it a pen or a vehicle. Hence, these reviews have a lot of importance. Opinion Spamming refers to “illegal” activities example writing fake reviews on the portals. It is also called shilling — an activity that deceives online buyers. Thus, web scraping can help us crawling the reviews and detect which one to block. Or which one to verify because these reviews generally stand out among the crowd.
6. Customer Sentiment Based On Targeted Advertising:
Scraping not only gives numbers to crunch but also helps a company. This is to understand which advertisement would be more appealing to which internet users. This helps in saving marketing revenue while it also attracts hits that get converted more.
7. Business-Specific Scraping:
Businesses can get more services under a single umbrella to attract more consumers. As an example, if you open an online health portal and scrap and use data related to all doctors, pharmacies, nursing homes and hospitals nearby, then it will attract many people to your website.
8. Content Aggregation:
Media website needs updating on the breaking news as well as other trending information that people access over the internet. The websites that publish a story first get the more number of hits. Web scraping can help check popular forums and also grab trending topics and more.
Evolution of Automated Web Scraping Techniques :
1. HTML Parsing:
2. The DOM Parsing:
The contents, style, and structure of an XML file defined in the DOM, known as Document Object Model. Scrapers need to know the internal working of a web-page and extract scripts running deep inside. When abstracted, generally use DOM parsers. The specific nodes gathered using DOM parsers and XPath like tools help to scrape the web page data. Even if the content generated is dynamic in nature, DOM parsers resolve the issues.
3. Vertical Aggregation:
Organizations with huge computing power, targeting specific verticals, create vertical aggregation platforms. Some of them even run these data harvesting platforms on the cloud. Bots created and monitored for specific verticals and businesses in these platforms. With no human intervention. The pre-existing knowledge base for a vertical helps create bots. And the performance of the bots created is much better.
4. The XPath:
XML Path Language or XPath is known to people as a query language used while extracting data from nodes of XML documents. XML documents follow a tree-like structure and XPATH. It is the easiest way to access specific nodes and extract data from those nodes. XPath used along with DOM parsing to extract data from websites, be it static or dynamic in nature.
5. Text Pattern Matching:
This is a regular expression-matching technique (known as regex in the coding community), using the UNIX grep command. It is generally clubbed with popular programming languages like Perl, Python to name a few.
Several web scraping software and services are available in the market, and it doesn’t need to be a master in all the above-mentioned techniques. There are tools like CURL, HTTrack, Wget, Node.js, and more as well.
Web scraping: Different Approaches:
1. Data as a Service (DaaS):
Outsourcing your web data extraction needs to a web scraping service provider dealing with datasets is the most common way to your business’ hunger for data. When your data provider helps you with the extraction and cleaning of data. You get rid of the need of a dedicated team for tackling data woes reducing a lot of burdens. Both the software as well as the infrastructure needs that data extraction processes need taking care of by them. And since these companies are extracting data for clients. You would never face a problem that they are new to. All you need to do is to provide them with your requirements and then relax as they work on it and hand you your priceless data.
2. In House Web Scraping:
You can opt for an in house data extraction if your company is capable enough. Not only you would need skilled individuals having worked in web-scraping projects and experts in R and Python. But you also would need the infrastructure to be set up so that your team can scrap websites, all day and all night.
Web crawlers often break even with the slightest change in the web-pages that they are targeting and due to this web-scraping. It is never a do and forgets solution. You need a completely dedicated team to be working at solutions all the time. At times, they might expect a big change coming in the way that webpages are storing data, and then they should prepare for it. Both building and maintaining a web-scraping team are complex tasks. And should be undertaken only if your company has enough resources.
3. Vertical Specific Solutions:
Data providers that only cater to a specific industry vertical are of this group. And these Vertical specific data extraction solutions are great if you can find one that can cover your data needs. As your service provider would only be working in a single domain, skilled in that domain. The data sets might vary and the solutions they will provide you will be customizable based on your requirements. They may be able to provide you different packages depending on your organization size and budget as well.
4. DIY Web Scraping Tools:
For them who do not have the budget for an in-house web crawling team and neither take the help of a DaaS provider. They can make use of DIY tools that are easy to learn and use. But, the downside is that you can’t extract too many pages at one go. They are too slow for mass data extraction and might trouble parse sites that use more complex rendering techniques.
How The Web Scraping Works:
Some many different methods and technologies used to build a crawler and extract data from the web. Following is the basic structure of a web scraping setup.
1. The Seed:
It is a tree traversal like procedure, where the crawler first goes through the seed URL or the base URL. And followed by the next URL in the data fetched from the seed URL and on. The seed URL would be hard-coded in at the very beginning. As an example, to extract all the data from the different pages of a website, the seed URL will be serving like an unconditional base.
2. Direction Setting:
Once the data from the seed URL extracted and stored in the temporary memory, the hyperlinks present in the data given to the pointer and then the system should focus on extracting data from those.
The crawler needs to extract and store all the pages that it parses while traversing in a single repository as HTML files. The final step of data extracting and data cleaning occurs in this local repository.
4. Extraction of Data:
The data that you need is now in your repository. But the data is not usable. So you need to teach the crawler to identify data points and extract only the data that you will be requiring.
5. Deduplication and Cleansing of Data:
Noise-less data will extract and duplicate entries deleted by the scraper. Such things built into the intelligence of the scraper to make it more useful and the data coming from it as an output becomes more usable.
If the scraper can structure the unstructured scraped data, you can create a pipeline to feed the result of your scraping mechanism to your business.
Web Data Extraction-Best Practices:
Although a great tool for gaining insights, there are a few legal aspects involved that you need to take care of to evade any trouble.
1. Respect The robots.txt:
Always check the Robots.txt file of the website you plan to scrape. The document has a set of rules that define how bots can interact with the website, and scraping in a manner that goes against these rules can lead to lawsuits and fines.
2. Not To Hit Servers Too:
Do not become a frequent hitter. Web servers end up falling prey to downtime if the load is too high. Bots add load to a website’s server and if the load exceeds a certain point. The server can become slow or crash destroying the great user experience of a website.
3. It Is Better If You Scrape Data During Off-Peak Hours:
To avoid getting caught up in web-traffic and server downtime, you should scrape at night, or at times when you know that the traffic for a website is less.
4. Responsible Use Of The Scraped Data:
Policies should be respected and publishing of data that might have severe consequences to deal with. So, it is always recommended that you use scraped data.
Finding The Correct Sources For Web Scraping:
The aspect of data scraping that frustrates most people, is how to find reliable websites to scrape. A few tips worth noting:
1. Avoid Sites With Too Many Broken Links:
Links are the main thing your web-scraping software is looking for. You would hate broken links to break the streamlined flow of processes.
2. Sites With Dynamic Coding Practices Avoided:
These sites are difficult to scrape as they keep changing. Hence the scraper might break in the middle of a task.
3. Ensure The Freshness And Quality Of The Scraped Data:
Make sure that the sites you scrape known to be reliable and have a fresh set of data.
How to integrate Web Scraping In Your Business?
It doesn’t matter whether you are selling or buying goods, or trying to increase the user base for your magazine. Whether you are a company of fifty or five hundred, chances are, you will need to surf the pool of data if you want to sustain in the competition. If you are a technology-based company with huge revenue and margins. You can even start your team to scrape, clean and structure data.
Yet, here I will be providing more of a generalized approach that applies to all. With the advent of coined flashy words and technological marvels. People often tend to forget the main thing — Business. First, you need to pinpoint which business problem you are trying to solve. It may be the scenario that a competitor is growing much faster than you are and you need to get back in the game. It may be the case where you need access to more trending topics and words to get more organic hits or to sell more magazines. Your problem might be so unique in the industry that no other business has come across.
In the next step, you need to identify, that what kind of data you will be needing to solve the issue. You need to answer questions like- “Do you have a sample of the data that you will need?” or “Which are the websites to scrape and when to scrape to get the greatest benefit.” Then you will need to decide on how to get the job done. Setting up a data scraping team overnight is not at all logical, and it can in no way done in a hurry. It’s always better if you get someone to do it for you, someone like PromptCloud. Having years of experience and have worked with many customers. To solve a variety of problems in the extraction of web data through scraping.
So no matter which path you take to your data, remember –
“War is ninety percent information.”