AWS Cloud Practitioner — 20 Most Expected Questions (With Answers)

AWS Cloud Practitioner — 20 Most Expected Questions (With Answers)

1. What is Cloud Computing? Internet-based computing.
2. What is EC2? Virtual server.
3. What is S3 durability? 99.999999999%.
4. What is an Availability Zone? Physical data center.
5. What is the root account? Primary admin account.
6. What is IAM? Identity management system.
7. What is VPC? Virtual private network.
8. What is Lambda? Serverless compute.
9. What is RDS? Managed database service.
10. What is CloudFront? Content delivery network.
11. What is Multi-AZ? Failover for RDS.
12. What is Route 53? DNS service.
13. What is Auto Scaling? Adds/removes EC2s automatically.
14. What is ELB? Distributes traffic.
15. What is Elastic Beanstalk? Simple app deployment.
16. What is KMS? Key management service.
17. What is SNS? Notification service.
18. What is SQS? Message queue.
19. What is Glacier? Long-term storage.
20. What is CloudTrail? Audit logs.

These questions help you prepare for AWS Cloud Practitioner exam with confidence.

What Is Databricks? Complete Beginner Guide (2026)

Databricks is a cloud-based unified analytics platform designed for big data processing, machine learning, and collaborative data engineering. It simplifies large-scale data workflows by combining Apache Spark with powerful cloud compute resources, making it one of the most commonly used platforms in enterprise data engineering.

What Makes Databricks Special?

Databricks eliminates the complexity of manually managing clusters and infrastructure. Teams can focus entirely on analytics while the platform handles compute, storage, pipelines, and automation.

Key Advantages

• Fast distributed data processing using Apache Spark
• Supports Python, SQL, Scala, and R
• Auto-scaling and auto-termination
• Collaboration-friendly notebooks
• MLflow integration for machine learning lifecycle

Core Components of Databricks

1. Workspace

An interactive environment where you create notebooks, dashboards, and workflows.

2. Clusters

The compute machines that run your notebooks, jobs, and data pipelines.

3. Data

A centralized interface to browse files, tables, and Delta Lake datasets.

4. Jobs

Automation feature used to schedule notebooks and workflows.

Popular Uses of Databricks

• Building ETL pipelines
• Real-time streaming analytics
• AI & machine learning model training
• Customer behavior insights
• Data warehousing using Lakehouse

Conclusion

Databricks is a powerful platform that simplifies data engineering, analytics, and machine learning workflows. Whether you are a beginner or an experienced data professional, learning Databricks in 2026 gives you a competitive advantage in the data industry.