How To Use Proxies For Advanced Data Analytics
There is a staggering amount of data available in the world today. Advanced data analytics allows businesses to leverage this data in a way that goes far beyond the scope of traditional business intelligence with the ultimate aim of gaining deeper insights that fuel better decision-making.
But, before any of the advanced analytic techniques can be applied, relevant data must be collected. In this article, we talk about how proxies can power this crucial process of data collection and facilitate advanced data analytics. To begin, we discuss the basics of what advanced analytics are and how they help businesses grow. Feel free to use the table of contents to skip ahead if you are already familiar with these concepts.
What Are Advanced Data Analytics?
Advanced data analytics refers to a wide range of sophisticated methods that are used to examine data and obtain future-oriented insights to support decision-making. In general, the term encompasses all analytical techniques that go beyond the scope of traditional business intelligence (BI) with forecasting and predictive goals. This includes techniques such as machine learning, forecasting, semantic analysis, sentiment analysis, and neural network – the list continues to grow as new techniques are continually being invented in the field of data analytics. Below we describe some of the most common ones:
1. Predictive analytics
Using techniques such as machine learning and data mining, predictive analysis can help businesses predict future outcomes based on historical data. This allows businesses to go farther than simply reacting to what has happened in the past, to making plans that help tackle highly likely future risks head-on.
2. Prescriptive analytics
Combining elements of traditional BI and predictive analysis, this technique aims to find the best solutions to specific business problems. After predictive analysis answers the question, “What will happen in the future?”, prescriptive analysis goes further to answer the question, “What do we do about it?”
3. Machine learning
Machine learning is a type of Artificial Intelligence wherein machines are made to detect patterns and inferences in data. They then use these patterns and inferences to automatically produce precise models that can analyze larger chunks of data more accurately. And all of this with little to no human intervention.
4. Sentiment analysis
Also known as opinion mining, this process examines pieces of text such as social media comments and product reviews to determine the sentiments behind them. It can be used to assess a brand’s reputation, gauge public opinion about a particular product or service and so much more. Learn more about sentiment analysis in this blog post.
How Does Advanced Data Analytics Help Businesses?
Advanced data analytics can be applied to various businesses in various ways. Its benefits and uses for you will depend on your particular business model. But, in general, here are some ways these innovative techniques can help boost your business:
1. Identifying business opportunities
Advanced data analytics enables businesses to easily identify new and profitable opportunities. For instance, the precision afforded by machine learning may help uncover untapped and overlooked customer segments with high potential. It may also help discover shifts in customer purchasing behavior, highlighting what products need to be focused on or updated.
While most sales and marketing experts are adept at discerning short-term trends from data, they are often less proficient at looking further down the road and predicting obstacles that may plague a business in the long term. With analytic techniques, such obstacles are easier to identify.
2. Improved customer acquisition and retention
As mentioned above, techniques such as sentiment analysis can be used to discover the opinions of customers and improve their experiences with your brand. Also, analyzing data such as customer web browsing habits can help you gain insights you can use to more effectively target and tailor your services to them.
3. Streamlining human resource processes
Human resource data is often only used for basic reporting. But, this kind of data is an extremely valuable resource specifically when put through advanced analytic techniques. When it comes to staff management, data analytics can inform decisions on promotions, improve performance evaluations, increase employee retention and contribute to professional development.
How to Conduct Advanced Data Analytics
We’ve talked about the “what” and “why” of advanced data analytics. Now, we move on to the “how”. As demonstrated above, no single method or technique encompasses the entirety of advanced data analytics. Instead, various techniques are used together to conduct this process. We cannot cover that large scope of information in this article. Instead, we focus on the first and, arguably, most important step of the process – data collection. Before you can analyze data, you must first collect and organize it in a way that facilitates analysis. This is where the need for one of the most essential advanced data analytics tools – i.e. a web scraper – comes in .
What Is Web Scraping and How Does It Help Advanced Analytics?
Web scraping is the automatic scanning of web pages and extraction of a specific type of data from them. Conducted by bots referred to as web scrapers, the process removes all of the hassle associated with manual data collection. The fact that the process is automated allows speed and removes the possibility of human error. What’s more, a good web scraper will not give you unstructured data. It will neatly organize all of the data collected in a file for further analysis. It can even directly funnel this information into another software.
The bottom line is that web scrapers can make a crucial step of advanced big data analytics much faster, and save you massive amounts of time. But, to work efficiently, web scrapers must be combined with another tool – proxies.
Why You Need a Web Scraping Proxy for Advanced Big Data Analytics
When web scrapers scan and extract data from a web page, they send requests to the website very quickly and in a way that makes it obvious that they are not human users. As such, websites tend to mistake web scrapers for malware and ban them. This is where the need for proxies comes in.
Proxies help devices disguise their IP address. An IP address is a unique set of numbers and letters assigned to a device that allows web applications to identify and locate it. It is through IP addresses that websites ban devices, preventing them from gaining access to info on the site. A proxy provides an alternate IP address through which a device can connect to the internet. When using a proxy, the device’s IP address remains hidden and all communications done between the device and a website are done via the proxy IP address.
As such, proxies provide a solution to the problem of bans during web scraping. With a proxy, you can switch up your IP address and seamlessly continue your web scraping project even after a ban. That depends, however, on the type of proxy that you use. Some proxy types are better than others for web scraping. Here are some of the best ones:
1. Rotating proxies
When you consider terms and conditions of use, a proxy can be classified as dedicated, semi-dedicated, or rotating. Dedicated proxies are those dedicated to a single user. Because only one person is given access to these IP addresses, they are a relatively expensive option. But, for the same reason, they are typically faster and safer to use.
Semi-dedicated proxies are shared by a few users at once. They are a more cost-effective option than dedicated proxies. But, because they are shared, they are generally slower and less secure. With a good service provider, however, these risks are minimized.
Both dedicated and semi-dedicated proxies give users access to a single IP address. Rotating proxies, on the other hand, are set up to automatically change IP addresses at regular intervals. Because of this constant change in IP addresses, they offer the highest level of anonymity. They are also one of the best proxy types for data scraping. That’s because bans are inevitable with the number of requests web scrapers send. But, with a rotating proxy, when one proxy IP address gets banned, it is automatically switched to another, allowing the process to continue seamlessly and quickly.
2. Residential proxies
Based on its place of origin, a proxy can be classified either as a residential or a datacenter proxy. Residential proxy IP addresses come from Internet Service Providers (ISPs) who give them to homeowners when they purchase devices such as modems. They are, therefore, linked to physical addresses. Because of these features, they are less likely to be detected and banned by websites since they resemble everyday users. As such, residential proxy IPs are optimal for web scraping. They allow much higher volumes of data to be scraped with fewer bans. The main disadvantage of these types of proxies is that, because they are difficult to obtain, they are relatively expensive.
Datacenter proxies, on the other hand, are created and managed by data centers. As such, they are cheaper and more readily available than residential proxies. However, because they are not linked to physical addresses or associated with ISPs, it is easier for sites to detect them as proxies and ban them. Some sites – Twitter and Instagram, for example – have gone as far as completely prohibiting their use. So you cannot gain access to such sites with a datacenter proxy.
These drawbacks make them sub-optimal for data scraping. Although you can use datacenter proxies to scrape websites that allow their use, you will need hundreds to thousands of them to effectively navigate bans and complete a web scraping project. Learn more in this blog post.
3. Rotating residential proxies
The two categories described above are not mutually exclusive. As such, a proxy can be rotating and residential, dedicated and residential, data center and rotating, etc. The most ideal kind of proxy for web scraping is a rotating residential proxy. The residential nature means such a proxy is hard to detect and the rotating feature means that when it is detected, another IP address replaces it and the process can go on smoothly. Find out more in this post.
The Best Proxies for Collecting Big Data and Advanced Analytics
To scrape data efficiently, you need proxies that are fast, safe, and guaranteed to not go down on you when you need them the most. Blazing SEO offers you all this and more. Whether you decide to go with datacenter or residential proxies to collect data for advanced analysis, we offer a wide variety of proxies and protocols for you to choose from. Our services are tailored towards giving you the best possible web scraping experience with all our proxies operating at a speed of 1GBS with unlimited bandwidth. With our bulk pricing options, you can spend less and buy more, saving up to 20% on enterprise-level orders. Best of all, our customer service agents are available to answer any questions you might have and render any assistance you may need 24/7.
Advanced data analytics help improve the accuracy and increase the likelihood of success of business operations and decisions. They allow businesses to identify profitable opportunities and risks, properly target potential customers, and predict future outcomes. As such, they make the potential for growth and profitability limitless. Web scraping proxies power the first and most crucial step of this process, allowing you to obtain relevant data quickly, efficiently, and safely.
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