AWS Data Analytics Training - AWS Data Engineering training

1. AWS Data Engineering: Tools, Techniques, and Trends +91-7032290546

2. Understanding AWS Data Engineering • AWS Data Engineering focuses on building data pipelines using cloud-native tools. • It enables the movement, transformation, and storage of large datasets. • Empowers organizations to scale their data infrastructure with ease. +91-7032290546

3. Core AWS Services for Data Engineers • AWS Glue – simplifies ETL operations with minimal configuration. • Amazon Redshift – optimized for large-scale analytics workloads. • Amazon Kinesis – processes streaming data in real-time. +91-7032290546

4. Ingestion Patterns and Best Practices • Stream data from IoT or apps using Kinesis Data Streams. • Move data between sources using AWS Glue Connectors. • Batch ingest using AWS DataSync or S3 Transfer Acceleration. • Trigger workflows with event-driven architectures via EventBridge. +91-7032290546

5. Managing Data Storage Efficiently • Use S3 bucket lifecycle rules to manage data cost-effectively. • Partition datasets for faster access and lower query costs. • Organize data with logical prefixes and metadata tagging. +91-7032290546

6. Data Processing at Scale • Glue supports dynamic ETL with Spark under the hood. • EMR clusters enable big data frameworks like Hadoop and Hive. • Lambda helps process micro-batches without provisioning servers. • DataBrew enables no-code transformations for business users. +91-7032290546

7. Analytics & Visualization Tools • Use Amazon Athena for ad-hoc queries directly on S3. • QuickSight transforms raw data into interactive visual dashboards. • Combine Redshift with BI tools for real-time reporting. • Integrate analytics with ML predictions using SageMaker Pipelines. +91-7032290546

8. Industry Trends Shaping Data Engineering • Move from monolithic to modular, serverless architectures. • Rise of real-time and low-latency data processing. • Increased focus on data governance and compliance. • Greater integration with AI/ML and predictive analytics. +91-7032290546

9. Key Takeaways & Recommendations • Leverage AWS-native tools for efficient, scalable pipelines. • Combine batch and stream processing based on use case. • Prioritize security, observability, and cost optimization. • Stay updated with evolving tools and architecture patterns. +91-7032290546

10. Contact AWS Data Engineering Address:- Flat no: 205, 2nd Floor, Nilgiri Block, Aditya Enclave, Ameerpet, Hyderabad-1  Ph. No: +91-7032290546 Visit:www.visualpath.in E-Mail: online@visualpath.in +91-7032290546

11. THANK YOUVisit: www.visualpath.in +91-7032290546