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What Is Data Scraping? How To Automatically Pull Data From A Website?

What Is Data Scraping Web Scraping Techniques, How To Automatically Pull Data From A Website

If you are looking to get all complete guidelines about web scraping, then this is for you.

In this article, we will discuss “what is data scraping?”. We will also cover all of the vital concepts from Web scraping techniques to putting data from a website to Excel along with its tools and applications.

Read it till the end and become an expert about all the fundamental elements in data scraping.

What is Data Scraping?

Data Scraping or web scraping refers to a computer program technique that extracts essential data/ information from another program or codebase’s output (human-readable).

The scraping method mainly uses to automatically take out the required data from websites through web applications.

How to automatically pull data from a website?

The procedure practice in web scraping is not much complicated and understandable.

Web Data scrapers are intelligent bots. These bots work skillfully; they pull out the HTML codes from Web pages and put them into a specific format.

The main points in website scraping are as follow:

  • A portable code called scraper bot is employed to obtain the required information.
  • Foremost, sent a GET request to the targeted website by employing an HTTP code.
  • After the website processes the request, the scrapers get permission to read and take out the website’s HTML data.
  • The scraper restores the data into a particular layout when data completely takes out from the site.

Web Scraping Techniques

We know that web scraping is beneficial and a kind of necessity for boosting businesses.

Here we will find out the techniques employed in web scraping. The Scraping can perform manually and automatically. Let’s discuss both possibilities.

1. Manual Web Scraping

The simple data copy-paste procedure lies in manual Web scraping. In this, the required data is browsed from the Internet and then put in a specific format.

However, It is workable against the website’s defense, but this type of scraping has significant disadvantages.

Firstly, it is a time-consuming and much expensive process. Secondly, it is hard to apply it in massive data scraping.

2. Automated Web Scraping

Automated data scraping carries out with different tools and techniques. Undoubtedly, the automatic process of Scraping is much economical and time-efficient. 

The techniques used in the automated process are as follows:


It is considered one of the dominant computing languages. This language utilizes data scraping. In addition to node selection, the XPATH also enables the computing of XML or HTML files.

It primarily employs in scraping hard and heavy scraping websites in much less time.

b) HTML Parsing or Syntactic Analysis

The main motive of HTML (Hypertext Markup Language) parsing is to scrap the data of an HTML page. Among all other methods, it is a fast way to extract data. For this purpose, the use of HTML codes pulls relevant information.

 c) Pattern Matching

The usage of programming languages such as Python and Perl with the UNIX grep command is involved in the text pattern matching method.

d) Document Object Model Parsing

Document Object Model or DOM parsing uses for attaining an intense or detailed structural view of the website pages.

It also gives information nodes before scraping. The DOM involves copying of web data and putting it in a  specific format for analysis.

How to scrape data from a website to Excel?

Let’s discuss the possible methods to scrape data from a website to Excel in detail.

1. Excel Web Queries

Excel web queries utilize to fetch data into Excel worksheets from web pages. It is a direct data extracting method from websites.

This method works when it seems complicated to maintain the connection of ODBC(Open Database Connectivity).

The steps involve in Excel web queries are as follows:

  • To place a query, first, open a blank worksheet.
  • Go to data and then choose the external data option from the Web.
  • The next page, “New Web Query,” will emerge on screen.
  • Here in the address bar, enter the URL of the required website.
  • There is a yellow color arrow on the open page for selecting data on the table’s side.
  • After clicking the yellow button, shift to the green button(importing data).
  • Now, for the data importing, click the green button and select the required data tables first.
  • Select the location of the data to put it in that locale.
  • Click the ok button for completion, and the data will export to the given direction.
  • It may take some time to complete its work.

2. Excel VBA

Following the necessary step involves web scraping via Excel VBA.

  1. Hover the cursor on the insert button and click it; now select the module to set a new one.
  2. For proceeding of VBA scraping, write down the sub-procedure code:

Sub VBA_WebScraping()

End Sub

  1. The tool selection is the next step to activate the Internet browser in Excel. For this, go to the reference list,  choose the option ‘Microsoft Internet Controls’ and then click the ok button.

To Interact with the internet explorer

  1. Select the variable with DIM as ‘Internet Explorer’ to write the code for web scraping.

Sub VBA_WebScraping()

Dim Browser As InternetExplorer

End Aub

  1. After the variable is set as Internet Explorer, the Browser will open whenever the code runs.

Sub VBA_WebScraping()

Dim Browser As InternetExplorer

Set Browser = New InternetExplorer

End Sub

  1. Now, for Browser’s visibility write code as:

Sub VBA_WebScraping()

Dim Browser As InternetExplorer

Set Browser = New InternetExplorer

Browser.Visible = True

End Sub

  1. Enter the website name in the code.

Sub VBA_WebScraping()

Dim Browser As InternetExplorer

Set Browser = New InternetExplorer

Browser.Visible = True

Browser.Navigate (“website name”)

End Sub

  1. Unlock Do While loop for choosing variables and select Ready state to initiate it.

Sub VBA_WebScraping()

Dim Browser As InternetExplorer

Set Browser = New InternetExplorer

Browser.Visible = True

Browser.Navigate (“website name”)

Do While Browser.ReadyState <> READYSTATE_COMPLETE: Loop

End Sub

  1. With the message box by using “LOCATION NAME,” check the extracted data from the website.

Sub VBA_WebScraping()

Dim Browser As InternetExplorer

Set Browser = New InternetExplorer

Browser.Visible = True

Browser.Navigate (“website name”)

Do While Browser.ReadyState <> READYSTATE_COMPLETE: Loop

MsgBox Browser.LocationName

End Sub

  1. Lastly, press the F9 key to collect data.

Automated Data Scraping with Tools

With automated data scraping tools, it becomes effortless to extract useful data on Excel. The best thing about these time-saver bots is that they eliminate the difficulty of learning about complicated programming and other technicalities.

These tools conveniently scrape the information and arrange it in Excel format.

Below, we have also written down some standard scraping tools to select according to your requirements.

Commonly Used Web Scraping Tools

Basic knowledge of Python is necessary to understand the vast field of Scraping. You can get it by browsing relevant libraries and tools.

There are several tools vastly used for data scraping, which are not tricky to use. However, we will discuss here some most widely used tools along with their specifications.

  1. Beautiful Soup
  2. ProWebScraper
  3. Parsehub
  4. Octaparse
  5. OutWitHub
  6. ScrapeHero Cloud

Let’s discuss these Web Scraping Tools in more depth:

1. Beautiful Soup

Beautiful Soup is a widely utilized tool for scraping data. For precise usage, it is essential to have clear basic concepts of Python and HTML.

To take out and collect data from HTML and XML files, BeautifulSoup is reasonable. Although it is not loaded with several features _simple for completing nominal tasks.

2. ProWebScraper

Through tools like ProWebScraper, there is no necessity of understanding the complex concepts and insides of web scraping.

The PWS has a user-friendly interface (point and click), which renders it a widely operated tool. Also, it allows for getting accurate data without any substantial effort.                                        

3. Parsehub

Parsehub is based on machine learning technology, enabling it to readout even more complicated files.

It is a durable web scraping tool supporting JavaScript, AJAX, cookies, sessions, and redirects.

It can provide the data files in  JSON, CSV, Google Sheets, and through API. Further, Parsehub is functional for Linux,  Windows, Mac, and Firefox extensions.

The free Parsehub tool version has limitations, while a paid subscription allows sufficient operations.

Not only this, but it lets the user enhance their working experience with certain advanced features. These include infinite scrolling pages, navigation, pagination, pop-ups, and data visualization (Tableau).

4. Octoparse

Otaparse works in a very feasible way so that it is convenient to run. The tool’s interface is relatively simple _ one-click selection. Its available data formats are TXT, CSV, HTML, and XLSX.

The unpaid version has fewer available features, but the paid version comprises additional elements for extracting heavy data indexes in larger quality.

Octoparse can scrape data from both dynamic and static websites. It supports AJAX, JavaScript, cookies, websites.

5. OutWitHub

OutWitHub is a remarkable tool to scrape data shortly but on a smaller scale. It is a web-based extension, downloadable from the Firefox add-ons store.

This tool allows data to export in formats like JSON, XLSX, SQL, HTML, CSV. It performs the scraping functions automatically from web pages.

The best thing about OutWitHub is that there is no necessity to learn programming or Python because of its specifically advanced but lenient features.

6. ScrapeHero Cloud

It is a  web browser-based scraping framework and simple to use. With this, there is no need to learn about complex scraping processes. Also, ScrapeHero Cloud all in one type, so the user does not require to download other software and tools.

It provides APIs for extracting data from websites like Amazon, Google, and Walmart. The cloud offers different paid plans for access to its master services. 

Before signing up, it also lends a free trial to its users for their satisfaction. The data can send out into JSON, CSV, and Excel formats.

Why scrape Website Data?

Undoubtedly, web scraping is an important method that helps in the growth and development of industries.

For instance, there is a constraint to analyzing huge data fractions for a new business setup or boosting an existing one.

It is time depleting and arduous to collect and download all the essential data manually. Here, web scraping comes into view, through which the data pull out automatically and organize in a proper format.

Applications of Data Scraping

Some most common and vital uses of Web scraping are as follows:

  1. Rates Scraping
  2. Risk Management
  3. Feedback Review
  4. Content Scraping
  5. Competitive Analysis

Let’s jump right into them in more details:

1. Rates Scraping

MAP observation is a necessary part of any considerable industrial setup. Companies have to keep observing retailers that either they are acknowledging their given prices or not.

It is not manageable to collect this data manually. However, this problem is resolved with the automated data scraping technique that takes minimum effort and time.

Moreover, it allows companies to learn about their competitor rates. It is a very effective way of formulating distinctive strategies.

2. Risk Management

The scraping techniques also employ in businesses for risk management. Companies to deal with new employees and customers manipulate risk management strategies.

To combat any emergency, companies usually always carry out cross-checking of their staff members and clients. However, this reviewing can not be done manually, as there are many data elements to scan.

Thus, web scrapers are used to collect and pull out data for background checks. These tools possess these extract data automatically.

3. Feedback Review

Sometimes, there is a need to keep track of customer’s feedback on different products and services. Here, it is not possible to search numerous websites for data compilation.

But with the time conserving data scraping strategy, it is possible without any concern in a short time.

4. Content Scraping

The critical factor for a successful business is promotion via content marketing. However, the compilation of such vast content manually is time-consuming.

For this purpose, the backing of bot scrapers is considerable. In such a scraping methodology, relevant content collects from websites to give rise to engaging sales-boosting content.

5. Competitive Analysis

In this dynamic competitive world, competitive analysis is a vital facet to level up the delivering services.

It is tough to gather up all the data precisely for comparison. However, this problem has also been solved by data scraping.

Data scrapers all the information accurately in a too understandable way for comparison. It is unquestionably a time-efficient and reliable manner to achieve the desired data.


We have provided you with all the basic concepts about web data scraping you were looking for as a beginner. This information will help you out to become an expert data scraper.

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Written by Fariha Arif

Fariha Arif is a passionate blog writer and loves to write diversified content. She prefers to read novels, browsing the Internet, and traveling in her spare time.

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