Understanding Structured vs Unstructured Data

edu Kanea > Lessons > Understanding Structured vs Unstructured Data

Objective: Differentiate between structured and unstructured data and explore their applications in telecom, particularly for MTN Ghana.

• Structured Data: Data organized in a fixed format, typically stored in databases or spreadsheets with clear rows and columns. It is easily searchable and used for quantitative analysis.
  • Characteristics: Predefined fields, numerical or categorical values (e.g., numbers, dates).
  • Telecom Examples:
    • Customer records (e.g., names, phone numbers, subscription plans).
    • Call logs (e.g., call duration, time, destination number).
    • Billing data (e.g., monthly charges, payment history).
  • MTN-Specific Example: MTN Ghana’s customer database stores structured data like subscriber IDs, data usage (e.g., 2GB/month), and payment dates, used for billing or churn prediction.
  • AI Application: Structured data feeds machine learning models to predict customer churn based on usage patterns or to optimize billing processes.
• Unstructured Data: Data without a predefined format, often text, audio, or images, requiring advanced processing (e.g., natural language processing or image recognition).
  • Characteristics: Free-form, complex to analyze (e.g., text, audio recordings).
  • Telecom Examples:
    • Call center transcripts (e.g., customer complaints about network issues).
    • Social media posts (e.g., tweets about MTN’s service quality).
    • Emails or chat logs from customer support interactions.
  • MTN-Specific Example: MTN Ghana analyzes unstructured data from Zigi chatbot conversations to identify common customer issues (e.g., “slow internet” complaints).
  • AI Application: Unstructured data is used for sentiment analysis (e.g., detecting customer frustration) or topic modeling to improve services.
• Telecom Relevance: Structured data drives operational efficiency (e.g., billing automation), while unstructured data enhances customer insights (e.g., sentiment analysis for better service). MTN Ghana can combine both to personalize offers and improve network reliability.