CompTIA Tech+ (FC0-U71)Data and Database FundamentalsHard
A small business currently stores customer orders in a single flat CSV file, where every order repeats the full customer name, address, and phone number in each row. As the business grows, staff notice widespread duplicate data and update errors. Which type of solution would best resolve this issue?
- AConverting to a relational database with separate related tables
- BSorting the CSV file alphabetically by customer name
- CAdding more columns to the CSV file
- DCompressing the CSV file to reduce its size
Show answer & explanationAnswer & explanation
Correct answer: A. Converting to a relational database with separate related tables
A relational database separates data into related tables (e.g., Customers and Orders linked by a key), eliminating repeated customer data and the update anomalies that occur in a flat file. Adding columns, sorting, or compressing the CSV does not address the underlying redundancy problem inherent to flat files.
Why the other options are wrong
- B. Sorting only changes the order of rows, not the redundant structure.
- C. Adding columns increases the file's complexity without fixing redundancy.
- D. Compression reduces file size but does not fix data redundancy or update issues.
Flat File vs Relational Database
A flat file stores all data in a single table-like structure, often causing repeated data, while a relational database splits data into separate related tables to reduce redundancy and improve integrity.
- Flat files (like CSV) have no built-in relationships between data
- Relational databases link tables via keys to avoid duplication
- Normalization is the process of restructuring data to reduce redundancy
Memory trick: One giant spreadsheet repeats itself; a relational database splits and links.