How To Find Financial Data Analytics with a Web Scraper and Proxy

Finding reliable and informative finance data is a fast-growing need for people online. In addition to finding raw data, people are looking for smart and helpful interpretations of those data so they can put it to use in their own savings and investment plans. If you’re starting a financial information website, you want to find the most up-to-the-second data in order to provide strong financial data analytics.

Starting your own financial website is easier than ever, but you have to know where to look to get good data and how to process it effectively. The analysis part is actually probably easier than the data collection part. You have to make sure you’re getting it from the right place and getting a ton of data in order to do a good analysis. This is a case where more is more. Since the financial world can change at the drop of a dime, you want to collect data quickly and be able to get more when you need it. For today’s topic, we’ll be going over how and why you can use web scrapers to collect financial data, and how to pair it with the right software to do financial data analytics.

What is Financial Data?

financial data analytics The world of financial data is always expanding these days. You can find stock tickers, financial analysis, and any other kind of indicators about how much money people are making and spending everywhere. If your finance website is tracking overall trends in home pricing, you can find the data you need on websites like Zillow and Redfin for tracking those data points. By gathering all of the housing costs, you can run financial data analytics to make projections about where housing costs are going based on the historical data.

You can also build a website that compiles stock information about certain industries. All publicly traded companies have to make their information available, so it’s easy to find. Pulling information into one convenient place for your users is an invaluable service.

When you find a place to collect your information, you have to figure out how to extract financial data. You can pull it all out manually by copying and pasting into your own document. However, this is extremely time-consuming as a way to start financial data analytics. Instead, you should invest in a web scraper.

Although there are people who can build their own web scrapers with Python (especially for Craigslist proxies), and there are some free options, there are a ton of paid web scraper services that are low-cost and be directed to do whatever you need them to do. Getting a finance data scraper from Scraping Robot is one good option: you can get a custom scraping plan and get all of the data you need quickly. A web scraper conveniently delivers your data in a .CSV or Excel file and saves you a ton of time. If you’re worried about how to learn how to page scrape financial data, the web scraper can get a lot done for you.

How to Scrape the Web for Financial Data

how to extract financial data Web scrapers can get you so much information in a short amount of time, but you have to be careful in how you use a web scraper. Because web scrapers can send requests very quickly, they make websites nervous and get banned for displaying virus-like behavior. You want to make sure your financial data scraper doesn’t compromise your IP address’s ability to get on certain websites.

Financial websites are more sensitive than most websites out there. The site owners are very concerned about getting hacked, so they have a lot of systems in place to watch for attacks. What you might not realize is that your financial data extraction bot can act just like someone who is engaging in a DDoS attack. That’s because bots often make several requests at once, and those requests can be mistaken as attempts to shut down the website. On top of that, lots of requests put a big load on the website’s servers, and that can cause it problems.

Space out requests

You can avoid getting blocked and hurting the website by adding some time in between your requests. Using a lower number of concurrent requests and adding in some additional delays between crawling pages. For instance, crawl five pages and then have a small delay. It will make it harder for websites to detect you, and it will keep their server loads down. Gathering information for financial data analytics is a long process, and you want to make sure you’re not compromised.

Diversify your actions

Many people don’t realize that websites often have sophisticated tools that analyze usage patterns. Robots typically follow the same pattern all of the time, while people vary their patterns. If your scraper engages in a bunch of repetitive tasks, it is very likely that you will get shut down. There is a solution to this. Go with a web scraper that has the ability to vary its patterns. When you set up your finance data scraper to act a little more random, the scraper will act more like a human and less like a bot. You’ll be able to do more financial data analytics with fewer interruptions.

Reduce server load by caching pages

When you’re figuring out where to get financial data, you don’t want to put too much of a load on your servers or on the website’s servers. You can reduce the load for both by caching pages after you scrape them. This is especially necessary when you are crawling a large financial website with your finance data scraper. When the page is cached, your financial data scraper can access it without going back to the website. That means if it has to go back to that page to grab more information, it won’t have to connect with the servers. This will speed up the process and it will help you fly under the radar.

What Are Financial Proxies?

how to scrape the web for financial data When you’re working with a finance data scraper, you will get the best results by pairing them with a finance proxy. A proxy provides you with a proxy IP address that masks your personal device’s IP address. This means that you have some measure of protection against websites looking to save your information. It is also a great way to avoid bans and geoblocking.

Proxies are super effective when paired with a web scraper for financial data analytics because they can get around bans and operate more anonymously. If you want to gather a lot of pricing information to help users figure out what their prices for products and services should be, a proxy will allow you to do finance data scraping in big projects without getting banned.

There are three main types of proxies: dedicated, semi-dedicated, and rotating. Dedicated and semi-dedicated proxies provide you with one proxy IP address as cover, but a semi-dedicated one is shared between a few users. Most people using a web scraper for financial data analytics will probably use a rotating proxy. This kind rotates out IP addresses as often as you need. This is ideal if you want to scrape a lot of information quickly—your rotating proxy will switch out a new IP address as soon as you get banned. This is also a great way to maintain anonymity online because your IP address will always be changing and can’t be tied to your online behavior.

The Best Tools for Financial Data Extraction

how to page scrape financial data When you’re looking for the best finance proxy for financial data analytics, Blazing SEO has you covered on all fronts. From custom plans to pricing variety to every possible protocol, you can find what you need to do your best work.

Data center proxies

Blazing SEO’s data center proxies have served users for years on their proxy needs, especially for web scrapers. There are a ton of plans available, for individuals and enterprise customers. With corporate plans, you can get a rotating proxy for as little as $1.98 per IP address. Since our data center proxies have location all over the world, you can also choose where your IP addresses are located in the world to do specific financial data analytics by city or country.

We also have 24/7 customer service to serve customers around the world. Blazing SEO’s proxy experts are always here to help.

Residential proxies

For financial data analytics, residential proxies are a great idea. These are ethically-sourced proxy IP addresses that look like they originated from ISPs. For this reason, they’re less likely to get banned and you can do more web scraping. Even though residential proxies are more expensive, they save you money because they’re less likely to get banned and can work with a web scraper safely.

Final Thoughts

how to analyze financial data Financial data can make a huge difference in your business and personal decisions. When used correctly, it can be like having your finger on the monetary pulse of a company or industry.  Financial data extraction works best with a financial data scraper and a finance proxy. Although you could do it on your own, you’ll get the best results if you get tools from reliable providers and ask the experts about how to make them work for you. With a changing finance landscape, it’s really important for businesses that provide financial data analytics to be on top of the most recently available information.

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