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AWS Data Engineering involves the use of Amazon Web Services (AWS) tools and services to design, build, and manage data processing systems. Data engineering on AWS encompasses tasks such as data collection, storage, transformation, and analysis. It leverages services like AWS Glue for ETL (Extract, Transform, Load), Amazon S3 for scalable storage, AWS Redshift for data warehousing, and various analytics services like Amazon Athena and Amazon EMR. Amazon Simple Storage Service (S3) is a popular and widely used object storage service provided by Amazon Web Services (AWS). It is designed to store and retrieve any amount of data from anywhere on the web. Here are some key concepts and features to help you understand AWS S3 for cloud-based storage

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1. Objects:

S3 is object-based storage, which means it stores data as objects rather than in a traditional file hierarchy.

An object in S3 consists of data, a key (unique within a bucket), and metadata.

Objects can range in size from 0 bytes to 5 terabytes.

2. Buckets:

A bucket is a container for objects stored in S3.

Each bucket must have a globally unique name across all of AWS S3.

You can think of a bucket as a top-level folder in which you store your objects.

3. Regions:

S3 buckets are located in specific AWS regions, and the data in a bucket is stored redundantly across multiple facilities in that region.

You should choose the region closest to your users to reduce latency.

4. Access Control:

S3 provides fine-grained access control over your buckets and objects using bucket policies, Access Control Lists (ACLs), and IAM (Identity and Access Management) roles.

You can control who can access your data and what actions they can perform.

5. Storage Classes:

S3 offers different storage classes to optimize costs and performance, including Standard, Intelligent-Tiring, Standard-IA (Infrequent Access), One Zone-IA, Glacier, and Glacier Deep Archive.

You can choose the appropriate storage class based on your data access patterns and durability requirements.                                             AWS Data Engineering

6. Versioning:

Versioning allows you to preserve, retrieve, and restore every version of every object stored in a bucket.

This helps protect against accidental deletion or overwrites.

7. Lifecycle Policies:

You can define lifecycle policies to automatically transition objects between storage classes or delete them when they are no longer needed.

8. Transfer Acceleration:

S3 Transfer Acceleration allows fast, easy, and secure transfers of files to and from S3 using Amazon Cloud Front’s globally distributed edge locations.

9. Event Notifications:

You can configure event notifications to trigger AWS Lambda functions, SQS (Simple Queue Service) messages, or SNS (Simple Notification Service) notifications when certain events occur, such as object creation or deletion.

10. Security:

S3 provides encryption for data at rest and in transit.

You can use Server-Side Encryption (SSE) or Client-Side Encryption to protect your data.

11. Logging and Monitoring:

S3 provides access logs that can be used for auditing and monitoring.

Cloud Watch metrics can be configured to monitor S3 bucket metrics.

12. Multipart Upload:

For large objects, you can upload parts in parallel, which can improve upload performance.                                         Data Engineer Training in Hyderabad

13. Data Transfer Acceleration:

Transfer Acceleration uses Amazon Cloud Front’s globally distributed edge locations to accelerate transfers to and from S3.

14. Data Replication:

S3 supports cross-region replication (CRR) and same-region replication (SRR) to replicate objects between buckets for redundancy or compliance purposes.

15. Resigned URLs:

You can generate resigned URLs to grant time-limited access to your S3 objects, which can be useful for temporary, controlled access.

16. S3 Select and Glacier Select:

S3 Select allows you to retrieve only a subset of data from an object, which can reduce the amount of data transferred.

Glacier Select extends this capability to objects in Glacier storage.

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17. AWS S3 Transfer Manager:

The AWS SDKs and CLI provide a transfer manager to simplify the process of uploading and downloading large amounts of data to and from S3.

18. AWS S3 Transfer Acceleration:

S3 Transfer Acceleration uses Amazon Cloud Front’s globally distributed edge locations to accelerate uploads to and downloads from your S3 bucket.

19. S3 Select and Glacier Select:

S3 Select enables you to retrieve only a subset of data from an object, which can significantly reduce the amount of data transferred.

Glacier Select extends this capability to objects stored in Glacier.

20. Data Replication:

S3 supports cross-region replication (CRR) and same-region replication (SRR) to replicate objects between buckets for redundancy or compliance purposes.

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