Web Data Integration (WDI)


What is Web Data Integration?

Web data is aggregated from different websites, making it difficult to manage and transform in a single location. Web data integration aggregates, transforms, and manages web data sourced from different websites in a unified framework. It enables businesses to get an accurate and unified view of web data.

Web integration goes beyond traditional web scraping to provide hidden insights to businesses and analysts that are not easily readable by human end users. Web data integration is the process of acquiring and transforming data from multiple websites into one cohesive workflow.

Many businesses have turned to web data integration for more sophisticated solutions to data quality and unpacking the potential of the web data life cycle. Ultimately, this process includes data extraction, transformation, standardization, API integration, and data mapping.

With an estimated 175 zettabytes of data predicted to be created by the year 2025, understanding the data lifecycle is becoming increasingly important for financial experts each year. Likewise, as businesses work to understand data, data experts are working to create new ways for people and businesses to harness this data influx.

Methods such as web scraping have created a revolution in the data industry; however, with 2.5 quintillion data points created daily, experts need to find alternative ways to harness the power of this data. This is where web data integration comes into play.


Web scraping and beyond

Web scraping, or web data extraction, is the process of utilizing software to access and extract data from web pages using the Hypertext Transfer Protocol.

Hypertext Transfer Protocol, HTTPS, is an application-layer protocol that transmits hypermedia documents, such as HTML, displaying web pages for end-users.

Web pages contain a wealth of information in text form; however, they are not easily accessible in their original form, often HTML, and require extraneous steps to unlock insights and find success upon analysis.

Similar to web scraping, web data integration’s ultimate objective is to retrieve data. However, their linkage lies in the fact that web scraping has evolved into a more extensive process: web data integration. Consequently, this data integration process amplifies the web scraping process to also include:

  • Data cleansing
  • Data normalization
  • Performing calculations
  • Unlocking hidden data
  • Custom reporting and analyzation
  • Integration capabilities

Ultimately, web data integration combines the above objectives into one interactive process with five major steps.


3 benefits of web data integration

1. Increased accessibilit

The API capability and integration within the larger web data integration process provide quick connections and more accessibility. For example, structured and normalized datasets available through APIs can provide investors with up-to-date insights during funding periods and throughout the investment evaluation stage.

2. Enhanced insights

Manual web scraping can often miss data and therefore doesn’t provide a full picture for analysis. The iterative and enhanced features of the web data integration process allow for retrieving hidden data in HTML files that aren’t necessarily readable or accessible to human end users.

3. Improved data quality

The identifying and preparation stages of the web data integration process are centered around achieving data quality. For instance, data quality can be gained during the identify stage simply due to the targeted approach of selecting the appropriate sources for enhanced insights.


Web data integration source types

The web data integration process requires extensive data pulled from the world wide web. Though, this data is not all the same. Web data can be extracted from many databases and can originate from many sources. Here are just a few of the different source types utilized during the data extraction process.

  • HTML data tables
  • Web sites
  • Web applications
  • Public data catalogs
  • Government catalogs
  • Semantic web (SPARQL)
  • Online encyclopedias
  • Public PDFs
  • Structured HTML data


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