Data extraction helps us make sense of the abundance of data generated every day. While many people often use the term interchangeably with web scraping, there is the need to stress that there is a huge difference between both concepts.
For instance, while web scraping is used to extract data from multiple sources on the internet, data extraction is more direct.
It is used to turn unstructured data or even the semi-structured ones into data that has structure and can be put to use immediately.
You may then think of it as the aspect of web scraping that involves manipulating web data to make sense of what has been extracted.
Without this process, all you would be left with is unstructured data that can’t be put into any meaningful use.
This means that before you start looking for how to extract data from a website, you will need first to understand what data extraction is and why it has become so important today.
Why Data Extraction Is Important Today
First, we need to establish that web scraping has remained important over these many years because it allows businesses of all sizes to have access to any data contained on the internet.
It serves as the automatic way to harvest data from multiple sources at once. This means that while you can manually visit a website, browse its content and copy what you want to paste on your computer, you could employ web scraping to make the process a lot faster.
Choosing web scraping over manual extraction will also provide you with data collected in real-time, making it more accurate and valid.
But the data extracted often comes in an HTML language which is not something you can readily understand or use to create business intelligence.
Data extraction was therefore introduced to the process to turn these unstructured HTML files into meaningful data that can be used to make important business decisions
And this is what makes data extraction very important in today’s business world because, with it, all brands would be left with loads of data that cannot be interpreted or used.
Recent Developments of Data Extraction
Data extraction itself is a process that has seen continuous development and improvements over these many years.
Most web pages often have their data in HTML formats. Data extraction has always centered around finding better ways to turn unstructured data into data with structure and meaning.
The latest improvement in data extraction includes the invention of tools such as web scraper APIs, which work around the many problems of web scraping.
For instance, with a web scraper, you no longer need to dance around the web browsing through unnecessary data. This often leads to a waste of time and energy amongst other resources,
It is not very common to see people use web scraper APIs to interact with specific platforms and extract specific data.
This makes the data less ambiguous and easier to process and manipulate, which is how you get structured data quickly.
What Are The Benefits of Data Extraction?
The following are some benefits and importance of using data extraction:
1. Competition Monitoring
In trying to grow a brand, people have to keep an eye on their competition to see what they are doing right and how to outperform them.
Web data extraction provides the best option to gather data about a brand’s competition from any part of the world.
The data can be immediately analyzed to observe what the brand needs to know to perform better.
2. Brand Protection
Another important benefit of web scraping and data extraction is that it allows the brand to protect itself against infringers and pirates.
These are two groups that observe different digital and intellectual assets online to steal them to impersonate or profit off them.
Brands that do not monitor their assets properly often lose them to the scoundrels who use them to manufacture counterfeit products.
These pose significant problems for both buyers and brands. To prevent this, brands usually use web data extraction to continually monitor and safeguard their assets across different spaces on the web.
3. Dynamic Pricing
Businesses must develop different business intelligence strategies to dominate their market and play global.
And one way to do this is to use dynamic pricing strategies which involve selling at flexible prices.
These prices respond to demand and increase a brand’s profit margin while protecting its customer base.
In dynamic pricing, a product can sell higher at different times and sell lower when demand or rush is low.
The products can also sell differently in different markets. But it needs to be done with sufficient data, or everything could go wrong.
Extracting data is usually how a brand can know the best way to implement a dynamic pricing strategy.
What Are Some Difficulties of Data Extraction?
Web data extraction also comes with several challenges, including the following:
1. Size of The Operation
Depending on the type of data you want to go for, you may either be dealing with too much data too often or data that keeps changing.
In either case, when you have to deal with a large-scale operation, the work can become very overwhelming.
2. Availability of Resources
This can also be a vast problem as data extraction often requires certain resources and tools.
For instance, you will need to have some technical know-how to turn HTML files into readable formats.
You will also need finances to run projects that involve data extraction continually—the inability to provide these resources that often impede the process.
There is also the issue of maintaining the tools you use for data extraction, as neglect will make them only serve for a very short period.
You will also need to maintain a large storage base if you intend to keep collecting data regularly.
And lastly, you will need to maintain the quality of the data you extract to ensure you are getting the best results and making the best decisions.
If the data is on the web, then, technically, it is scrapable, but not every scraped data can be put to use or applied profitably.
Data extraction allows you to take the unstructured data you scrape and turn it into something meaningful and insightful. However, if you wish to learn more about how to extract data from a website then this link explains it even in greater detail.
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