How Web Scraping is Transforming the World with its Applications

for converting them into actionable investment insights.Market Data AggregationWhile a lot of market data is available on the Internet but it is scattered across tens of thousands of websites.You can search and scan the search results but it is too time-consuming and tedious.Web scraping is used to scrape the data from different websites and glean actionable intelligence from these sites in terms of equity research.Extracting Financial StatementAnalysts need financial statements in order to determine the health of a company and advise their clients regarding whether to invest or not to invest in it.However, getting financial statements from several companies for numerous years is not possible in a manual fashion.Web scraping tools are used to extract financial statements from different sites and for different time periods for further analysis and make investment decisions based on the same.InsuranceThere is a growing trend to study alternative data in order to determine the risks etc..on the part of insurance companies to devise their products and policies.But it is not possible for them to leverage this data by manually copying or storing it.Therefore, insurance companies capitalize on web scraping to scrape alternative data and arrive at their decisions regarding insurance products and policies.Web Scraoing Applications in Data SciencePC: WikipediaReal-Time AnalyticsReal-Time analytics simply means that data is analyzed right after data becomes available..It is different from batch-style analytics because batch-style analytics may take hours or delay to process data and produce insights.Compared to that, real-time analytics can produce insights without any delay.Financial institutions use real-time analytics for credit scoring in order to make decisions regarding whether to extend credit or discontinue it.Customer relationship management (CRM) is a notable example of how real-time analytics is made use of in optimizing customer satisfaction and enhancing business results.Real-time analytics is also used at Points of Sale in order to detect any kind of fraud..In retail outlets, real-time analytics comes into play while dealing with individual customers in terms of incentives etc.As each of the examples indicates, real-time analytics depends on processing large quantities of data..Real-time analytics also works in a hassle-free manner if and only if large quantities of data can be processed quite quickly.This is where web scraping comes in handy..Real-time analytics would not be possible if data could not be accessed, extracted and analyzed quickly.Predictive AnalysisPredictive analysis is a process of analyzing existing data in order to work out patterns and predict future outcomes or trends..Predictive analysis cannot accurately forecast the future but it is all about forecasting what the probabilities are.Apart from other fields, predictive analysis has its application in the world of business..Predictive analysis is used in order to study and understand customer behavior, products and various other things to work out the risks and opportunities.However, as it is evident, it is a kind of analysis that takes place on the basis of vast amount of existing data.This is why web scraping has grown in significance because it can extract and make available vast amounts of data which can later be used in predictive analysis..In other words, web scraping is paramount for predictive analysis.Natural Language ProcessingNatural language processing is a process of enabling machines to interpret the natural languages used by humans unlike the computer languages such as Python etc.Sentiment analysis is a notable use case of natural language processing..Data scientists use comments on social media to process and assess how a particular brand is performing.As it is implied, machines will need to have access to large quantities of data for any application of NLP to work.Web scraping is one of the few efficient ways to scrape and make the data related to such social media comments or anything else available in a usable format..Therefore, with the growing significance of NLP, web scraping has also become increasingly important.Machine Learning Training ModelsMachine learning basically implies that we provide data to machines for them to learn and improve on their own without having to use any explicit programming.Web is the ideal source of such data..By training machine learning models, we can get them to carry out different tasks like classification, clustering, attribution etc.However, machine learning models can be trained only if quality data is made available.. More details

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