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Extracting Data With Frequent Changes In Website Format | PromptCloud
 

Extracting Data With Frequent Changes In Website Format

Extracting Data With Frequent Changes In Website Format

Data Extraction has become an invaluable component of business intelligence given the power of free data scattered across the web. While there’s no doubt about how useful web data can be for organizations in improving efficiency, identifying customer sentiment and gaining competitive intelligence, the fact remains that extracting data from the web comes with its own challenges. One of the biggest hurdles is the dynamic nature of web. Websites undergo design and structural changes quite frequently and this could create a huge issue in terms of maintenance while using automated data extraction techniques.  

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How often do websites get updated?

You’d be surprised to know how frequently websites get updated. While it’s almost impossible to evaluate the overall frequency of changes in websites’ design, it can range anywhere between 2 months to 2 years. Some of these changes are very subtle and a normal user can hardly identify them. Some changes are cosmetic and some are meant to improve the security and stability. Not all changes can affect the web crawling setup, but it’s always recommended to keep a tab on changes going on in the target websites. This is why web scraping service providers use programs to monitor changes on the target sites.

How are changes monitored

Any changes on the target sites that could create a loss of data can be identified by using a custom program that monitors the incoming data. To make sure no issues go unnoticed, web crawling providers follow a double layer monitoring system that includes an automated program checking the extracted data in real time and frequent manual checks.

Automated checks

An automated program is set up to monitor the incoming data in real time. This program will mainly look for irregularities in the extracted records to find possible changes in the website. Here are some red flags that the monitoring program will look for:

1. Rapid change in the volume

A sudden change in the data volumes suggests some sort of change in the website source code. This could be the change of a class name previously used for a data field or other structural changes that requires updating the web crawler. The program would immediately send notifications to the team working on the project and changes can be made promptly.

2. Unnatural content in a field

If a data field that is supposed to have text content suddenly starts getting numerical values or special characters, this could be counted as an issue caused by a change in the target website. The monitoring program is set up to identify such irregularities and send notifications.

3. Missing fields

Missing fields can also be an indicator of the target website having been updated. Too many missing fields usually occur when the website makes changes to its pagination structure.

In-house data extraction vs Outsourcing

Web crawling is indeed a niche specialty that demands an extensive tech stack, skilled labour and end-to-end maintenance. Given the challenges involved in ensuring a smooth data extraction process, it could be a distraction and headache for organizations when done in-house. A better option would be to depend on a Data-as-a-Service provider to take complete ownership of the data aggregation process.

Relying on a DaaS provider would also save you from the burden of creating a team of technically sound domain experts and high end technical resources that are crucial for running a web crawling setup. Not to mention, outsourcing would help you allocate more time to apply the data to your business and derive insights, saving significant man-hours and associated costs.

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