Hi Maveryx,
A solution to last week’s challenge can be found here.
Don't forget that we are running a campaign inviting all of you to contribute to our upcoming 2024 Weekly Challenges! Your ideas and participation are crucial in shaping an engaging and innovative year ahead. Visit our blog post to review the guidelines and submit your challenge to earn our brand-new accolade, the Weekly Challenge Contributor Badge! 
A special thanks to Mark Thompson (@Watermark) for submitting this challenge some time ago. Your contribution is greatly appreciated, Mark! It is a fantastic opportunity for our users to test and enhance their RegEx tool skills.
Your company recently adopted a new customer relationship management (CRM) tool but overlooked a crucial detail: how to link company records in the new CRM to the companies in the legacy financial system. The common link between these systems is the company’s URL, but the website data entered by the sales team in the CRM is inconsistent and often incorrect.
As the person responsible for solving this issue, your tasks are to:
- Match each company in the legacy financial system with its corresponding record in the new CRM.
- Analyze the CRM data to identify how many entries contain “dirty data,” meaning entries with subdirectories in the URL.
- Determine the number of distinct websites (base URL) that matched during the data integration process.
- Identify companies within the US that have multiple opportunities in the CRM (more than one). (Hint: Use the domain URL.)
- Identify companies with multiple opportunities (more than one) outside of the US.
Hint: To identify the countries, look for two-character top-level domain (TLD) codes in the URLs. Assume that any other code (for example, .com, .net, or .org) is associated with a US-based company.
If you want to learn how to use regular expressions to parse your data, you can review the following lessons in Academy:
Good luck!
