Web Scraping and API: How They Differ for Analysts

The internet is filled with digital data that can transform ideas, operations, and business. It is a source of information about customer trends, brand perception, and market share in any field with a digital presence. This data helps improve the basic functionality of teams and processes. Today, there are two popular ways to obtain public web data.

One of them is connecting to API interfaces, and the other is web scraping. Both methods allow you to obtain structured data that can be used to analyze ideas and trends. However, the use cases of both methods are contrasting in terms of technical dependencies and advantages. 

The process of website scraping is seen more as a passive role played by bots to extract content from websites. These bots are designed to collect every data point on a web page, such as text, tags, images, video titles, and subtags. The scrapers then save this information as a data file or into a database, structuring these elements. This data can be extracted by installing browser extensions with readily available templates or by contacting a data analysis service provider.

While API requires active participation from both the site and the recipient in automating the data pipeline, API often requires creating a dedicated application targeting a specific part of the site for automatic data extraction, which requires certain technical knowledge and manual effort.

Types of API

An API can be simply defined as a contract for data exchange between two software products, defined by rules and conventions. In other words, it allows two products to communicate, where one application sends requests and the other issues a response with information or actions.

Not all websites allow the use of an API interface. This type of data collection provides an interface for obtaining specific data from applications, such as websites and databases.

APIs work in two ways: one via URL endpoints, and the other via specialized software wrappers. For example, Twitter's REST API allows recipients to access core data such as search and trends.

So, in principle, we can distinguish two types of API - open and internal. Open API is available to the general public for data mining. The most common APIs we might have encountered are Skyscanner for flight search, Yahoo Finance, and URL shorteners.

API for Web Scraping

Data is a valuable asset for organizations, enabling them to run their business smoothly and make progressive data-driven decisions. Fortunately, data collection via API allows overcoming serious obstacles such as establishing connections with dynamic websites and bypassing IP blocking, Captcha, and browser fingerprinting scripts.

You should use API because it is easy to integrate, customize, and also saves time and money. A custom application is created by defining a set of specifications and response structures in XML or JSON format. This data is used for competitor monitoring, lead generation, and product optimization.

Capabilities of Web Scraping

Data analytics has become a huge part of organizational management. And rightly so, because the volume of data is growing exponentially as the world shifts to digital and data consumption surges globally. Website scraping is definitely the most complex way to obtain structured data. You can either be familiar with big data analytics or work with one of the best scraping providers, such as ESK Solutions.

There are all kinds of data on the internet, such as images, product information, customer reviews from irecomend or ostrovok, which can be used for market research. You might be interested to know that Yandex regularly uses data analytics for indexing its content and for marketing purposes. Scraping is based on three main principles. First, an HTTP request is made to the server, data is extracted by parsing the code, and the relevant data is saved in the cloud or locally.

The Role of the Analyst in Data Scraping

Now we understand what scraping does, but how does it function? How exactly does an analyst help put everything in place and give bots direction to work? The analyst provides URLs for data scraping, first compiling a shortlist of sites. Then he modifies the code for the script that defines the elements to collect on the front end.

The analyst can also identify the data source located in the backend of the site using appropriate tags. After identifying the tags with Python libraries, the analyst specifies the data types, such as name or rating, for analysis and storage.

The data analyst also ensures whether the target data is clarified, whether the terms of service are complied with, whether data protection protocols are adhered to, and whether the site is at risk of crashing. The analyst always keeps these considerations in mind, and therefore data scraping is one of the best ways to obtain structured data.

Conclusion

Simply put, scraping is extracting data from a website using data analysis software.

API provides direct access to application data. As a result, API can be a bit expensive. Nevertheless, the main purpose of both is to access web data.

However, in the modern era, companies prefer to use both scraping and API for data extraction. But in most cases, a specialized scraping company takes on solving all your data extraction tasks.