Data – we hear this word a lot, but do we really get the importance of data collection and analysis? At its most basic, data contains different facts and statistics that have been translated into a form that computers can process. This might seem simple, but data is effectively transforming our world and ways of working.
Data is at the foundation of virtually every business decision made. In the business world, data is used to get a deeper understanding of market trends, improve the consumer database, and develop marketing strategies. By using data effectively, companies are able to streamline the process of getting a product built and delivering it to the customer. However, to obtain useful data, companies need different techniques and extraction tools like scraper API.
In this post, we cover the importance of data and its analysis, together with briefly explaining web scraping and crawling and their differences. So, let’s get started:
Why Use Data Extraction and Indexing Processes
The modern business industry is a data-driven environment. Data is crucial for businesses to make decisions based on facts, market trends, and statistical numbers. Every day, we generate nearly 2.5 quintillion bytes of data, and this mind-boggling number is only going to continue to get higher. Considering this continuous increase, the acquisition and use of such an enormous amount of data without computational help are nearly impossible. Incomplete or poor-quality data obtained from websites often leads to less effective decision-making and wasted resources.
This is where web scraping and crawling come into play. Both processes are used to capture an abundant supply of market data for comparison, verification, and analysis based on the given company’s requirements and objectives. They provide businesses with accurate and useful information to manage service effectiveness and ensure the best use of resources.
Web scraping, also called web data extraction or web harvesting, refers to the process wherein data is extracted from several websites of data sources at the same time. This technique is used to extract an enormous amount of data from online sources and store it in a local or cloud-based data warehouse in Excel, XML, or SQL formats.
Though scraping is often done in an automated way, there are many cases where it can be done manually. The bots used in this process are called web scrapers, which may differ based on many parameters, including self-built or pre-built scrapers, web scraper API, and cloud or local web scrapers. Some popular web scraping tools are Webscraper.io, ProWebScraper, etc. However, if you’re searching for a fully-fledged efficient web scraping tool, check more info here.
Also called web indexing, web crawling refers to the process of reading and storing all of the content on the website for archiving or indexing purposes. It is a general process of building a set of web pages by starting with an initial set of links and recursively traversing the corresponding pages to find additional URLs. This makes it an integral part of data extraction and works smoothly with web scraping to help companies get all data they need at every turn.
Web crawling involves an internet bot – also called spiders or crawlers – that crawls the web and collects data and pages to index or create collections. Since they only have seed URLs, web crawlers are not site-specific and need no prior knowledge of a webpage before crawling. Popular search engines like Google, Bing, and Yahoo do web crawling and use this information for page indexing.
Differences between Web Scraping and Web Crawling
Web scraping differs from web crawling as it extracts and duplicates data from any web page it accesses, whereas a web crawler navigates and reads a page for indexing. For more differences between these two processes, read the following section:
|Web Scraping||Web Crawling|
|It is used for extracting specific data or elements from web pages.||It is used to index web pages.|
|It is suitable for both small and large amounts of data.||It is mainly used in large-scale projects.|
|It does not need to visit all pages of a website for information.||It visits all pages of a website for information.|
|Application areas include retail, marketing, real estate, equity search, and machine learning.||Search engines use web crawlers to give search results to the users.|
|Data deduplication is not mainly a part of web scraping.||Data deduplication is a major part of web crawling.|
|Scrapers need a crawl agent and a parser for parsing the response.||Crawlers need only crawl agents.|
|Creating a scraper is cost-effective and less time-consuming.||Crawling bots are more functionally versatile and expensive to build.|
It is now clear that web scraping and crawling are essential to a business, whether it is for revenue growth or customer acquisition. Companies often rely on these processes to acquire correct and useful data from online resources. While web scraping hones in on specific data set snippets, web crawling also involves the identification of new pages to scrape for creating a large collection of data.