Cloud Databases & Data Pipelines

Imagine your app is growing fast

Every second, it generates data:

• User signups
• Transactions
• Logs

Now you face two challenges
Where to store this data?
How to process it efficiently?

If data is not organized properly, it becomes useless

So you use:

• Cloud Databases → Store data
• Data Pipelines → Move & process data

Now everything is structured, fast, and useful

What are Cloud Databases?

A Data Pipeline is a system that:
Moves data from one place to another
Processes and transforms it

Pipeline Stages (ETL)

1. Extract → Collect data from sources
2. Transform → Clean & process data
3. Load → Store in database or warehouse

GCP Tools for Data Pipelines

Pipeline Stages (ETL)

1. Extract → Collect data from sources
2. Transform → Clean & process data
3. Load → Store in database or warehouse

GCP Tools for Data Pipelines

Technical Example (Simple Query Flow)

Example of processed data analysis

Real-Life Examples

1. E-commerce Analytics

• Store orders → Process → Analyze sales

2. Real-Time Notifications

• Use Pub/Sub for instant updates

3. Banking Systems

• Process transactions securely

4. Social Media Apps

• Analyze user activity