Interactive Lesson: Data Architecture Challenge

Data Fundamentals – Architecture Challenge

🎯 Data Architecture Challenge

Test your Data Fundamentals knowledge in a real-world scenario

1
Data Types
2
Data Classification
3
Storage Solution
4
ETL vs ELT
5
Ingestion Method
6
Integration

🏢 Welcome to TechMart Analytics!

You’ve just joined TechMart as an Analytics Engineer. The company is modernizing its data infrastructure to support real-time analytics, machine learning, and business intelligence. Your first task is to design the data architecture for their new platform. Make strategic decisions at each stage!

📊 Challenge 1: Design the Customer Table

TechMart needs a new customer table. Choose the correct data type for each column:

CREATE TABLE customers (
  customer_id ___________,
  email ___________,
  account_balance ___________,
  is_premium ___________,
  signup_date ___________
);

Select the best data types:

🗂️ Challenge 2: Classify the Data Sources

TechMart collects various types of data. Drag each data source to its correct category:

📊 Structured Data

📄 Semi-Structured Data

📸 Unstructured Data

Available Data Sources:

Sales transactions database
JSON API responses
Customer support emails
Product inventory table
XML configuration files
Product review videos

🏗️ Challenge 3: Choose the Storage Architecture

TechMart needs to store structured sales data for BI reporting AND raw data for machine learning. What’s the best solution?

Data Warehouse Only
Store everything in a structured data warehouse like Snowflake
Data Lake Only
Store everything in a data lake like AWS S3
Data Lakehouse
Implement a lakehouse architecture combining both capabilities
Separate Systems
Use a warehouse for BI and a separate lake for ML

🔄 Challenge 4: Design the Data Pipeline

TechMart processes 10TB of daily transaction data using cloud infrastructure. They need flexible transformations that analysts can modify. Which approach is best?

ETL (Extract, Transform, Load)
Transform data before loading into the warehouse
ELT (Extract, Load, Transform)
Load raw data first, then transform in the warehouse
Consider these factors:
  • • Large data volume (10TB daily)
  • • Cloud-based infrastructure
  • • Need for flexible transformations
  • • Analysts need to modify logic frequently

⚡ Challenge 5: Select Ingestion Methods

Match each TechMart use case with the appropriate data ingestion method:

Real-time fraud detection on transactions
Daily sales reports for executives
Live inventory updates for e-commerce site
Monthly financial reconciliation

🔌 Challenge 6: Design the Integration Strategy

TechMart needs to integrate with external services. Choose the best approach for each scenario:

Scenario 1: Get updated product prices from suppliers every hour
Use REST API with scheduled polling
Set up webhooks for instant updates
Scenario 2: Receive instant notifications when customers complete purchases
Use REST API with frequent polling
Implement webhooks for real-time events

🎉 Congratulations!

You’ve completed the Data Architecture Challenge

0/6

Challenges Completed Successfully