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Showing posts with the label Data Extraction

How Important the Big Data is for the Tourism Industry?

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  In today’s post-pandemic experience, big data assists travelers and travel agents in making superior decisions, minimizing the risks, as well as having unforgettable holidays. According to World Tourism Organization the UN, tourism holds 10% of the whole world’s GDP. This also shares similar statistics in the general job market, producing 1 out of each 11 jobs! With a surprising amount of information and data at their removal, tourism boards and travel agents as well as require proper tools to scrape actionable insights in case, they have meaningful effects on this industry. All the data-driven decisions would benefit travelers and local communities also. Different Types of Accessible Travel Data Online Travel Agencies around the world are using big data for improving their service offerings. Data like travelers' nationalities, duration of stay, places they got checked in, traveling intent, etc. could be used to improve services as well as customer relations. Similarly, visitors ...

How to Extract Web Data using Node.js?

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we’ll find out how to utilize Node.js as well as its packages for doing a quick and efficient data extraction for single-page applications. It will help us collect and use important data that isn’t always accessible using APIs. Let’s go through it. Tip: Sharing and Reusing JS Modules using bit.dev Utilize Bit for summarizing components or modules with all the setup and dependencies. Share them using Bit’s cloud, work together with the team as well as utilize them anywhere. What is Web Data Extraction? Web data extraction  is a method used for scraping data from websites with a script. Data scraping is a way of automating the difficult task of copying data from different websites. Generally, web Scraping is performed when the desired websites don’t render the API to fetch data. Some general data scraping scenarios include: Extracting emails from different websites for the sales leads. Extracting news headlines from different news websites. Extracting product data from different e-co...

How Web Scraping is Used in Cryptocurrency Market Analysis?

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The entire cryptocurrency business has been prospected and continues to flourish since the launch of cryptocurrency — Bitcoin in 2009. There have been approximately 4,000 altcoins (different cryptocurrencies to Bitcoin) launched too far. Furthermore, cryptocurrency is known for its high unpredictability. Maintaining an eye on the situation can be tough, especially for inexperienced investors. What is the Role of Web Scraping in Cryptocurrency Trading? Web scraping is most often used in e-commerce and marketing to track prices and generate leads. More investors are beginning to use technology in online banking these days. It streamlines the extraction of data from a variety of sources and stores the information in a structured format for any further study. For a thorough market study, extract historical crypto market data. For a thorough market study, extract historical crypto market data. As a professional trader, keep a close eye on crypto pricing to get a comprehensive view of the en...

How Web Scraping is Used to Extract Data from OTAs?

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Customer satisfaction is the most important factor for any service-oriented business. And if you own a travel company, then you must ensure that your customers have the finest vacation experience. After all, satisfied customers will mean repeat business, and they are the most valuable asset for attracting new clients and increasing revenue. When it comes to vacation planning, flight ticket rates are one of the most important influencing elements, alongside lodgings and activity packages. As a result, network operators need to provide the greatest travel plans to their customers. As companies grow more data-driven, they examine what their competitors are just doing, as well as how airlines and online travel agencies set ticket pricing and use this information to make better decisions. Scraping flights and tickets data  from various platforms such as OTAs, airlines, and competitors is an effective method to enhance your decision. And this could be done using web scraping. Advantages ...

Scraping Google Jobs Listings Data

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Job data is amongst the most desired data online. In case, you are preparing some research  projects or want a new position as well as need brand-new postings as per your interests and  skillsets, you may utilize a Google Jobs API from 3i Data Scraping as per your requirements as  well as extract SERP results from the Google Jobs searches. About Google Jobs Google Jobs is the search feature, which collects job listings from different resources and it  was started in 2017 as a way of giving people in need of employment in an easier manner to observe which jobs are accessible without getting multiple websites. It provides detailed information on job positions as well as an extensive range of employment objectives. This is launched in many regions, including the United Kingdom and the United States. You will obtain many opportunities in case, you make Google Jobs a part of the search method. Initially, you are given the options like category, titles, company types, date...

How to Extract Product Data from H&M with Google Chrome?

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  Data You Can Scrape from H&M Product’s Name Pricing Total Reviews Product’s Description Product’s Details The screenshot provided below indicates various data fields, which we scrape at 3i Data Scraping: Requests Google’s Chrome Browser:  You would require to download the Chrome browser and the extension requires the Chrome 49+ version. Web Scraping for Chrome Extension:  Web Scraper extension could be downloaded from Chrome’s Web Store. Once downloaded the extension, you would get a spider icon included in the browser’s toolbar. Finding the URLs H&M helps you to search products that you could screen depending on the parameters including product types, sizes, colors, etc. The web scraper assists you to scrape data from H&M as per the requirements. You could choose the filters for data you require and copy corresponding URLs. In Web Scraper toolbars, click on the Sitemap option, choose the option named “Edit metadata’ to paste the new URLs (as per the filter)...