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Python Set Operations Explained: From Theory to Real-Time Applications

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A  set  in Python is an unordered collection of unique elements. It is useful when storing distinct values and performing operations like union, intersection, or difference. Real-Time Example: Removing Duplicate Customer Emails in a Marketing Campaign Imagine you are working on an email marketing campaign for your company. You have a list of customer emails, but some are duplicated. Using a set , you can remove duplicates efficiently before sending emails. Code Example: # List of customer emails (some duplicates) customer_emails = [ "alice@example.com" , "bob@example.com" , "charlie@example.com" , "alice@example.com" , "david@example.com" , "bob@example.com" ] # Convert list to a set to remove duplicates unique_emails = set (customer_emails) # Convert back to a list (if needed) unique_email_list = list (unique_emails) # Print the unique emails print ( "Unique customer emails:" , unique_email_list) Ou...
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6 Exclusive Differences Between Structured and Unstructured data

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Here's a basic interview question for Big data engineers. Why it's basic means many Bachelor degrees now offering courses on Big data, as a beginner, understanding of data is a little tricky. So interviewers stress this point.

Don't worry, I made it simplified. So you get a clear concept. I share here a total of six differences between these. In today's world, we have a lot of data. That data is the unstructured format.

Structured Vs Unstructured data - 6 Top Differences
 

Structured Data

  1. The major data format is text, which can be string or numeric. The date is also supported.
  2. The data model is fixed before inserting the data.
  3. Data is stored in the form of a table, making it easy to search.
  4. Not easy to scale.
  5. Version is maintained as a column in the table.
  6. Transaction management and concurrency are easy to support.

Unstructured data

  • The data format can be anything from text to images, audio to videos.
  • The data model cannot be fixed since the nature of the data can change. Consider a tweet message that could be text followed by images and audio.
  • Data is not stored in the form of a table.
  • Very easy to scale.
  • Versioning is at an entire level.
  • Transaction management and concurrency are difficult to support.

References

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