IDS Case Study: Using Internet Scraping to Increase Profitability

By Keiter Technologies

IDS Case Study: Using Internet Scraping to Increase Profitability

Is There a More Cost-Effective Way to Collect Data?

Data Science can help you achieve your business goals with tailored advice specific to your organization. Learn more about how Keiter Data Solutions solved a similar problem for one of our clients in the below case study.

 

Challenge and Opportunity

A Keiter Technologies client, a technology company that sold aggregated data was seeking a way to collect data at scale in order to lower overhead costs. Instead of manual scraping, they needed an automated system to do it.

 

Our Approach

  • The client was spending approximately $10,000-$20,000 a month on data for its platform.
  • Using AWS Lambda and Python, our team was able to build the client a customized tool that could scrape data from the internet at scale.
  • The tool was more efficient and could collect more data in real-time while integrating it into the client’s API.

Results

The delivered tool works effectively and saves the client hundreds of thousands of dollars in data collection fees.

 

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About the Author


Keiter Technologies

Keiter Technologies

Keiter Technologies focuses on serving businesses with their strategic technology needs through data science, cybersecurity, and IT audit and consulting.

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The information contained within this article is provided for informational purposes only and is current as of the date published. Online readers are advised not to act upon this information without seeking the service of a professional accountant, as this article is not a substitute for obtaining accounting, tax, or financial advice from a professional accountant.

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