The Single Best Solution To Big Data Challenges: Web Scraping Proxies

More data is available to us today than ever before and, every day, the amount is exponentially increasing. This has led to the existence of what we refer to as big data i.e. data sets so massive and varied that it is difficult or even impossible to collect and manage them with standard relational databases. From giving accurate insights that foster better decision-making to uncovering new opportunities, this kind of data has become an invaluable resource for businesses in today’s highly digitalized marketplace.

Considering just the sheer size of big data, there are several unique challenges that arise when attempting to collect, store and analyze it. To maximize the benefits of big data, executives must be aware of these challenges and, more importantly, be conscious of ways to overcome them.

In this article, we present you with one of the best solutions to several big data challenges you might be facing – web scraping proxies. We start by running through the basics of some big data problems. If you are already familiar with these concepts, feel free to use the table of contents to jump ahead.

Top 4 Challenges With Big Data

top challenges of big data

Big data analytics come with numerous challenges. But overcoming them is well worth the effort as up to 61% of companies reliant on big data analytics say the heightened understanding of customer behavior improved their revenue. Here are a few prominent challenges you should be aware of:

1. A huge volume of information

Across all industries, over 2 quintillion bytes of data are produced every single day. It is no surprise, then, that the primary challenge of big data analysis is often assimilating the sheer volume of data available. This is especially true for small businesses that don’t have the infrastructure to handle this level of analysis.

2. Big data collection challenges 

As mentioned earlier, part of the challenge with big data is the fact that it is too extensive to be successfully collected and interpreted by conventional tools. In addition, knowing exactly what variables to look for and collect can be even more of a challenge. Big data is often like a huge proverbial haystack from which companies have to find the needle of what is relevant to them.

3. Big data implementation challenges 

Once relevant data has been collected, parsed, and interpreted, it needs to be correctly implemented to make a meaningful impact. That means using insights gained from big data to make impactful changes to your company’s services, products, marketing campaigns, etc.

4. Big data security challenges 

Big data privacy and security challenges are some of the most bothersome issues you’ll have to continually face if your company depends on data. Clients trust your company with sensitive information such as their addresses and payment details. A leak of such information can be lethal to both your brand’s reputation and the safety of the clients in question. There is also the issue of keeping your data safe from competitors. Ensuring security can be particularly problematic if your company’s data is stored on a cloud or some other remote storage system.

Tackling the Challenges of Big Data Through Web Scraping

tackling big data challenges with web scraping

When it comes to overcoming the challenges presented by collecting and parsing big data, web scraping is the single best solution available. Web scraping is an autonomous process used to extract relevant data from websites and web pages. Here’s how it can help you overcome the challenges above:

  • Collecting massive chunks of data automatically

Companies with insufficient infrastructure to support big data may succumb to the temptation of employing a team of data analysts whose job is to process big data manually. However, the gathering and organization of big data are frequently beyond the remit of even the most skilled team of human analysts.

In contrast, web scrapers can handle massive volumes of data. By automatically collecting relevant information and organizing it into a neat CSV or Excel file, they allow you to save loads of time and energy. Web scrapers can even directly funnel the data into analytic software, further easing the process of big data analysis.

  • Improving security

Web scrapers make it possible for you to securely and privately access enormous sets of data. This enables you to build trust with your customers, protect your brand’s reputation and decrease the risk of competitors finding out what data sets are fuelling your company’s decision-making.

  • Facilitating proper implementation

Web scraping undertakes the challenge of accruing and organizing big data. By so doing, it gives you and your team more free time to tackle the challenges of big data analytics and integrate the results into your company’s plans.

While web scrapers are the single best solution to many big data challenges, they have problems of their own. Thankfully, there is also a single best solution to these problems – proxies.

How Proxies Can Help You Solve Big Data Problems

solving big data issues with proxies

A proxy is a tool that allows you to circumvent many of the inherent challenges web scrapers encounter. When used correctly, it enables you to bypass website restrictions and eliminates digital barriers so that you can access crucial big data samples.

Many websites are very sensitive to the bot-like behavior of web scrapers and tend to ban them because of it. That’s because the behavior closely resembles that of malware designed to collect sensitive information for nefarious purposes. Also, some websites don’t want their data to be accessed and exploited by competitors.

When websites ban a web scraper from accessing them, they usually do it through a unique code referred to as an IP address. This code helps the websites identify and locate devices. Proxies – or, more accurately, proxy IP addresses – serve as intermediaries used in place of a device’s original IP address to communicate indirectly with websites. As such, after a ban, you can use a proxy to hide your real IP address and communicate indirectly with websites you want to scrape.

Additionally, by hiding your IP address, proxies heighten anonymity and provide extra protection against hackers. This helps to further secure any big data you are gathering.

Choosing The Best Web Scraping Proxies for Big Data Issues

the best proxy for big data problems

There are several kinds of proxies and certain types are better for scraping than others. Understanding the differences between them will help you make the right choice to successfully tackle your big data challenges:

Static vs rotating proxies

Static proxies, as their name implies, maintain a single IP address for the entire duration that you have them. There are two types. One is dedicated to you and only you. The other must be shared among a few users. In both cases, you have access to only one IP address. And when it comes to web scraping, this is just as bad as using your own IP address because you’ll hit a roadblock as soon as the address gets banned.

Rotating proxies, on the other hand, get a change in IP address at regular intervals. In the case of a ban, the IP address is automatically rotated allowing the process to continue uninterrupted. As such, they are great for web scraping. Learn more about these kinds of proxies here.

Datacenter and residential proxies

Datacenter proxies are produced and stored in data centers. Because they are not associated with physical residences and Internet Service Providers (ISPs), it is very easy for websites to tell that they are not normal users. As such, they tend to get detected and banned quickly. Some websites even totally prohibit the use of these IP addresses making it impossible for you to access such websites with a datacenter proxy. However, for websites that do permit their use, they are a cost-effective option. But you will need hundreds, if not thousands, of them to collect big data.

Unlike datacenter proxies, residential proxies are attached to specific locations and ISPs. Because of these features, they simulate regular human user behavior. They more easily slip under the radar and are less likely to be banned.  As such, they are more valuable for big data collection than their datacenter counterparts.

Overcoming Big Data Challenges With Blazing SEO

how to overcome challenges with big data

Blazing SEO offers proxies that run at speeds of 1GBS, unlimited bandwidth, and the choice of up to 26 different IP address locations. With complete end-to-end control of our hardware, we are in a position to rapidly detect and solve any issues that might affect our proxies. That’s why we can guarantee a 99% uptime and confidently promise you that our proxies won’t go down on you when you need them the most.

With us, you can rest assured that you are getting only the highest quality proxies to help you tackle any big data challenges you might be facing head-on. And, whether you choose to use residential or datacenter proxies to help you solve your big data problems, we have what you need. If you have any questions, get in touch with us. We are here for you 24/7.

In Conclusion

challenges of big data analytics

Big data challenges are as many and as varied as the sample sizes they offer. With several inherent benefits, web scraping is an extremely valuable tool for tackling many of these challenges. But, because web scraping is often detected and prevented by the anti-bot settings of most websites, proxies are a necessary complementary tool.

The information contained within this article, including information posted by official staff, guest-submitted material, message board postings, or other third-party material is presented solely for the purposes of education and furtherance of the knowledge of the reader. All trademarks used in this publication are hereby acknowledged as the property of their respective owners.

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