AWS Data Engineering - AWS Data Engineering Training Institute.pptx
- 1. Introduction to Big Data Engineering on AWS This presentation explores big data engineering on AWS, covering the lifecycle, core services, and real-world applications. We'll examine how cloud solutions streamline data processing from ingestion to analytics, highlighting AWS's role in scaling big data workloads. +91-7032290546
- 2. Core AWS Services for Big Data Amazon S3 Scalable and durable object storage for data lakes. Amazon EMR Managed Hadoop framework for big data processing. AWS Glue Serverless data integration and ETL service. Amazon Redshift Petabyte-scale cloud data warehousing. Amazon Kinesis Real-time data streaming and processing. +91-7032290546
- 3. Data Ingestion Strategies Batch Ingestion • AWS Glue for ETL pipelines into S3. • Efficiently loading large datasets. Real-time Ingestion • Kinesis Data Streams for continuous data flow. • Low-latency processing for immediate insights. Diverse Data Sources • Integrating external APIs and databases. • Handling semi-structured (JSON, XML) and unstructured data. Monitoring & Logging • CloudWatch for ingestion health. • Ensuring data integrity and audit trails. +91-7032290546
- 4. Data Storage and Lake Architecture Building a robust data lake is crucial. Amazon S3 forms the foundation for scalable storage. AWS Lake Formation centralizes security and access control, ensuring data governance. Efficient partitioning and cataloging via Glue Data Catalog optimize query performance and cost. +91-7032290546
- 5. Data Processing and ETL AWS Glue Serverless ETL for data transformation. Automated schema detection. EMR & Spark Parallel processing for large-scale data. Customizable compute environments. Step Functions Orchestrate complex ETL workflows. State management and error handling. +91-7032290546
- 6. Data Warehousing and Analytics Amazon Redshift • Columnar storage for analytical queries. • Scalable clusters for diverse workloads. Querying & BI • Redshift Spectrum for S3 data. • Athena for serverless query on data lakes. • QuickSight for interactive dashboards. ML-Powered Analytics • Redshift ML for in-database machine learning. • Predictive analytics without data movement. Optimization • Workload management for performance. • Cost efficiency through elastic scaling. +91-7032290546
- 7. Real-Time Data Streaming IoT IoT Data Sensor data for immediate insights. Logs Application Logs Real-time monitoring and anomaly detection. Fraud Fraud Detection Instantaneous transaction analysis. Kinesis Data Streams vs. Firehose: Choose streams for custom processing, Firehose for simple delivery. Use Kinesis with Lambda for real-time ETL. +91-7032290546
- 8. Best Practices & Career Outlook Key Practices • Strategic tool selection for each data stage. • Focus on scalability, security, and cost-efficiency. • Prioritize data governance and compliance. Career Growth • AWS Data Engineer certification enhances expertise. • Roles in data architecture, MLOps, and analytics. • Continuous learning is vital in this evolving field. +91-7032290546
- 9. +91-7032290546 GCP Data Engineer 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 Contact