DATA CRAWLING IN A NUTSHELL

In the internet, everyone is looking for the best experience of information browsing for his or her needs. People are looking and searching for things that are most relevant to their queries, and search engines are one of the most commonly used tools to do that. By using a search engine, people can look up the most relevant results that they seek on the internet. However, how can the search engine show the most relevant queries that they are looking for?

Sometimes, data searching on the internet can be used for some more technical purposes as well. In some cases, software engineers need to look up trending information data to analyze a current trend on the internet. Since the World Wide Web is a vast place, they have to assess and categorize data based on a set of criteria in order to make the data more searchable. Think of it like a librarian’s job, where the librarian arranges the books based on specific themes, alphabetic order, and many more.

In the modern world, this kind of activity is called as web crawling. Directly speaking, web crawling (or web crawling and web spiders by some) is a tool used to index and download a particular set of data from the internet. To use a web crawler, a user needs to assign a list of websites where the crawler can easily “crawl” out information from these websites. After assigning them, the crawler will seek out specific information from these websites before storing them in a database.

A web crawler is called as such due to its function in searching up information on the internet. Compared to the typical information searching on the internet, the tool will “crawl” at any website links that may possess the desired information to look up the most relevant result. Whereas conventional information searching will also display information that is maybe not relevant to the query, results from web crawling will only display the relevant ones. This eases the process of information searching since the web crawler has already looked the only relevant information instead of scanning for every result on the internet.

Since the data collected by web crawling makes it easier for users to look for the relevant information, it needs always to be updated nonetheless. Since users utilize web crawler tool to index the currently trending information on the web, the database has to be renewed gradually. This is important for companies that hugely rely on trending customers’ preference, as this trend can change each day. Continuously using web crawler to sort out relevant customers’ preference will help the companies in their long-term business.

At first glance, web crawling seems to be similar to the data mining activity, although in reality, both are quite different from each other. Data mining refers to an analysis of a large quantity of data to discover some previously unknown patterns and records within the data set. Data mining itself does not involve the data collection and the data preparation process, where this is significantly different from web crawling. Moreover, as opposed to data mining, web crawler tool will handle both the data collection and the data analysis process.

Users can use the web crawler tool for different purposes. Usually, people use this tool to do trend checking and routine visits to several websites that need regular maintenance. In other cases, people can use the tool to compare commodities’ prices on the internet and look up additional data for statistic websites. Whether the costs can be stable or fluctuate themselves at the current moment, web crawling can provide an insight for the users if they want to use the data from the crawling.

One of the most commonly related activity with the web crawler tool is the big data. Shortly speaking, big data is a field that finds ways to analyze, extract, or deal with data sets that are impossible to be done with traditional data processing software. By using web crawler tool, big companies can identify chances, increase customer experience, and maximize their profit income. Since they can determine the current trend within society, companies can assess people’s preference in certain products and services. These results in them being able to prepare and provide the most needed products and services to maximize their profit.

Using web crawler also helps companies to sort out their potential market and all the features of their competitors. Despite its tempting benefits, using web crawler can also spend both time and money for these companies. Software engineers will need both time and funding to persistently assess all of the relevant data from hundreds to thousands of websites. In addition, the trending information might change yet again by the time the engineers are processing and analyzing their collection of data.

Nonetheless, the benefits of web crawling outweigh the downsides of using the tool. To maximize profit and their performance, companies cannot avoid the uses of web crawler to support their business. When they can cleverly analyze their data to make it usable for their business, they can earn extra profit to replace all the spent time and funding during the web crawling process.

Data crawling could also be used to classify  customer’s profile, know your customer and prospective debtor with PROFIND. PROFIND is an ekyc made by AdIns that designed to accelerate customer profiling process.