There are many web crawlers available today and they all differ in their usability. It can be selected according to our needs. There is a large data crawling market with different types of crawlers popping up every day. As easy as it may seem at the highest levels, it is equally difficult to create an efficient crawler. Say no to plagiarism. Get a tailor-made essay on "Why Violent Video Games Shouldn't Be Banned"? Get an Original Essay Scanning data is not a simple process, with data present in multiple formats, numerous codes, and multiple languages. This makes playing qualitative web crawling a complicated process. But the following ways can simplify the process: Well-defined architecture. A well-defined architecture helps a web crawler run smoothly. With web crawlers following the Gearman model of supervisor crawlers and worker crawlers, we can speed up the page crawling process. To prevent any loss of recovered data, it is crucial to have a reliable web scanning system. A backup storage support system for all supervising crawlers without depending on a single data management point and crawls the web efficiently. Intelligent recrawling. With different clients looking for data, web crawling is used in many ways. For updating lists across categories and genres, different websites have different frequencies. Scraping data by sending a crawler to these sites will be a waste of time. So it is important to have an intelligent crawler that can analyze the frequencies with which pages are updated. Efficient algorithms LIFO (Last In First Out) and FIFO (First In First Out) are the different methodologies used to traverse data on pages and websites. Both work well, but it becomes a problem when the data being scanned is larger or deeper than expected. This makes it important to optimize crawling in data crawlers. By prioritizing crawled pages based on page rank, refresh rate, reviews, etc. Your web crawling system can be improved by increasing page crawl time and dividing data crawlers equally so that there are no bottlenecks in the process. Scalability. You need to test the scalability of your data scanning system before launching it. You need to incorporate two key features: storage and extensibility into your data scanning system. A modular architectural design of the web crawler will make the crawler modifiable to adapt to any changes in the data. Language independent. A web crawler must be language neutral and should be able to extract data in all languages. A more multilingual approach can help users request data in any language and make intelligent business decisions based on the information provided by the data scanning system.