Financial data is essential for many enterprise businesses. Corporations can use prices and trends to make better predictions using big data analysis. These corporations can include financial and investment companies, banks, hedge funds and more. Financial companies can use a number of sources to get the data required. This includes social media, newsfeeds, market data providers, and more. The data is then verified and organized to be easily analyzed.

Enterprise web scraping is similar to regular web scraping, however at a larger scale. As discussed, banks are considered enterprise corporations and can benefit significantly from enterprise web scraping. Scraping large amounts of data from multiple online sources can be very complicated, and that is why ParseHub Plus works directly with financial institutions to streamline the big data scraping process.

In this blog post, we will discuss the legality of large-scale web scraping, what financial big data can be used for, where you can scrape financial data, how you can scrape financial data, and finally the pros of working with ParseHub Plus!

Is Web Scraping Legal?

The legality of web scraping is a hot topic and is widely debated. However, when it comes to public information, web scraping is completely legal. As long as the information is shown on the front end, to any user, it is okay to scrape. However, if the data is private, and not meant for public use, it would be illegal to scrape. That is why ParseHub Plus only scrapes legal and public financial data for enterprise clients.

Another topic is the ethics of web scraping. Web scraping and crawling may slow down websites if done at a large scale, however, most websites that host large amounts of data are usually built to withstand high volumes of traffic. A single parse through data would not cause any disruptions in service, especially with a tool that works efficiently, such as ParseHub.

What is Financial Big Data Used For?

There are many ways an enterprise business can use financial big data, here are some:

Predictions and Machine Learning Algorithms

Many corporations rely on artificial intelligence and machine learning to make smart predictions and to increase the efficiency of their systems. These systems can be used for financial outputs but also in ways to improve recommendations to users, such as in a shopping cart.

Investment Research and Portfolio Management

By utilizing large amounts of financial data, corporations can analyze prices and commodities in real-time to make better investment decisions for their clients. By having access to big data, patterns can be predicted more accurately.

Financial Forecasting and Sentiment

Corporations can forecast a market using big data, but also the sentiment in a particular industry as well. Numbers are a great indicator of future markets, but tapping into what is being discussed, such as on social media or on blogs is a great way to predict future trends.

Stock Market Trends and Predictions

Many stock market and equity organizations make use of big data to make better pricing predictions. By scraping online stock price portals, companies can predict where the price is going to make better buying and selling decisions.

Where to Scrape Financial Data?

The whole internet is your oyster when it comes to web scraping. Any data that is public can be scraped, such as the prices of commodities, assets and services. Analyzing these prices can be extremely useful, as long as you know where to scrape from. Stock markets and cryptocurrency data can be scraped for analysis and trends. The news, press, and social media can be scraped for sentiment analysis. Public financial statements and forecasts can also be scraped from a variety of corporations. The number of websites to scrape is endless, and working with ParseHub Plus, you will have more insight on what sources you could scrape from, with direct support for enterprise web scraping clients.

How to Scrape Financial Data?

There are many ways to scrape financial data. You could extract data manually, which is the most time-consuming method and has a high chance of human error. You could create your own code, but when scraping from multiple websites, you would need to create a new script for each one. Also, many custom-coded scrapers get blocked easily by websites that host large amounts of data. These scripts can also easily break when websites get updated, which requires a lot of maintenance.

The best option is to work with a dedicated team, such as ParseHub Plus, which handles all the scraping for you, making it even easier than using the lower tiers of ParseHub. When working with our enterprise team, you will have direct support, from your dedicated managers, which will ensure a consistent flow of web scraped big data. 

ParseHub Plus Scraping Advantages

There are many benefits of working with ParseHub Plus as compared to making your own scraping scripts or using web scraping software. When working with the enterprise version of ParseHub, you will receive consistent 1 on 1 support and daily monitoring of your data. If anything happens to your web scraping, our team will be there to help with same-day support, to ensure your big data efforts are not going to waste.

All data is validated through our custom scripts which ensures quality control and accurate big data. This means you will not need to check data yourself, and your data scientists and algorithms can use the data right out of the gate.

Your team can use the data directly with an API or save it as a CSV for your team to use. Over 10,000 to 50,000 pages can be scraped in a single day for your enterprise corporation and you won’t have to worry about writing code, updating your code, and creating new code for each website you wish to scrape.

Concluding Thoughts

In the end, working with ParseHub Plus, your enterprise business can increase profits, productivity and predictions when it comes to big data. Many enterprise corporations can benefit from having vast amounts of financial data, which can be used for artificial intelligence, prediction models, stock market analysis and much more. Web scraping is 100% legal when done on public information, and when working with ParseHub Plus, you can ensure your data sources are legitimate and accurate. Finally, you will no longer need to create custom web scraping scripts for all the domains you wish to scrape from, as our dedicated team will help you scrape thousands of pages a day. 

If you are interested in scraping large amounts of financial data, visit ParseHub Plus to book a call and get your free data export!

Happy Scraping!