Scraping alternating data is the process of analyzing external data to make business decisions. According to the statistics of Rivery, the world generates 2.5 quintillion bytes per day. When people are exposed to a such wide range of data, why should they rely on conventional data within a restricted boundary to perform data analysis? Keep
Scraping alternating data is the process of analyzing external data to make business decisions. According to the statistics of Rivery, the world generates 2.5 quintillion bytes per day. When people are exposed to a such wide range of data, why should they rely on conventional data within a restricted boundary to perform data analysis? Keep reading this article to understand the process of scraping alternative data.
Investment is a big step people take expecting a profit. Putting money into a company without proper analysis can lead you into trouble or end up causing you to become a victim of fraudulence. People usually make use of traditional data sources like transactional data and other financial data to make investment decisions. But, these are not the only sources. People of this age have the opportunity to access data all over the web. This article speaks about how scraping alternative data from multiple sources can help investors with investment insights.
Alternative data refers to external data that helps the investment process. Investors who are in search of a standard financial firm to invest their money will undergo a detailed study of the company. Apart from internal data gathered from company filings and websites, some external data bring more value to the analysis. External data from sources like press releases, the Security and Exchange Commission, and other statistical surveys are considered alternative data that provides additional data on the company’s performance to decide whether to invest in the company or not.
From data generated online, here are a few types of data you can use as alternative data for evaluating financial firms. Alternative data providers are sources that provide raw data, which are collected and processed by scraping solutions to obtain unique and timely insights.
Collecting credit and debit card transactions help investors with retail revenue tracking. Investors can look for the credit card transactions of a particular company to build investor insight.
Another popular source to collect information is social media. Social media is a place where people pour out their feelings toward a product through comments or reactions with emojis to show their interest in the product. Scraping data from social media like Twitter helps investors to perform a sentiment analysis on their views by categorizing their responses as good or bad.
The geolocation data that tracks the physical location of the transaction helps the user to analyze where the investments work. Some attempts of the financial sectors can positively benefit the people of a certain area. The regular foot-tracking process also helps investors make decisions based on geographical locations.
The website also serves as alternative data, like web traffic, website clicks, and reviews. Web traffic of the company site lets users know the popularity of the company, how common people use the site, and for what. Then comes the factor called reviews. You may have come across many survey or review sites that collect people or customer reviews. From this, people can understand the opinions of previous users and make investment decisions from them.
After knowing what sorts of data will help investors make decisions, here comes the next question. How do you get the alternative data and make use of it? Collecting such data from data providers is not an easy task, like browsing a website and gathering information manually. Analyzing alternative data sets requires the working of thousands or even millions of datasets. Bringing such data together from multiple resources needs a technique called scraping.
Scraping alternative data is the process of pulling or extracting tons of data as data sets or raw data. This raw data will be put into further processing steps to convert them into valuable insight.
Scraping is all about collecting data from varied sources. And when it comes to alternative data, the scraping range is wider, so people have the option of collecting data across the world. People can manually collect information by accessing each site. As this scraping deals with data from huge and varied sources, it is not possible to collect data manually from each source. People will eventually prefer automating the scraping process. This scraping automation can be done by various means.
When scraping alternative data, people may face certain challenges as follows.
IP blocks – When normal web users try accessing sites from the same IP address, the Internet Service Provider or the website finds suspicious traffic on their sites. This helps them easily track the IP address from their web traffic and block them from their sites.
Geo-Restrictions – You can face geographical restrictions while accessing websites from some countries. Some servers do not want people of a certain location to access them. Sometimes countries also block sites within their own boundary.
Low Speed – When the data is huge, the accessing speed of the data is reduced. Downloading tons of data or big data sets can take time and require efficient software as well.
Using proxies for scraping is the one remedy to handle all the above-stated challenges. Proxies with their basic nature of hiding the client’s IP address can easily solve all these challenges.
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Web scraping tools, proxies, and third-party service providers are possible scraping solutions users can rely on. If you have trouble finding a trustworthy financial firm to make your investment decisions, analyzing the financial statements of the company may help you predict the worthiness of the financial firm. Apart from this traditional data source, depending on the alternative data from external data providers, using scraping tools or proxies can amplify the speed and capacity of your scraping activities.