Data is everywhere. From online shopping to digital payments, the amount of information we create every second is massive. But how do companies actually use this data to make better decisions? The answer lies in big data analytics in cloud computing.
What Do These Terms Mean?
Big Data: Datasets that are too large or complex for normal systems. Examples: millions of transactions per hour, social media clicks, or sensor data from machines.
Cloud Computing: Renting storage and computing power online instead of buying costly hardware. You only pay for what you use.
Together, they form big data analytics in cloud computing – the process of analysing very large datasets on cloud platforms to extract useful insights.
Why Cloud Is a Game-Changer:
- Scalability: Handle sudden spikes in traffic or data.
- Speed: Build and test analytics pipelines quickly.
- Cost control: Pay-as-you-go makes it affordable.
- Rich tools: Access AI, machine learning, and real-time dashboards.
- Global reach: Low latency for users across regions.
Four Types of Big Data Analytics:
- Descriptive – What happened?
- Diagnostic – Why did it happen?
- Predictive – What might happen?
- Prescriptive – What should we do next?
Real-World Applications:
- Banking: Fraud detection
- Retail: Personalised product recommendations
- Healthcare: Faster diagnosis
- Manufacturing: Predictive maintenance
- Smart Cities: Traffic and safety analytics
For developers and students, learning how big data works on the cloud can open up exciting career opportunities in data engineering, analytics, and AI.
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