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AWS Data Analytics Training - AWS Data Engineering training

Boost your cloud career with AWS Data Analytics Training at Visualpath. Our AWS Data Engineering training delivers hands-on projects, real-time learning, and expert guidance to help you design and manage scalable AWS data pipelines. Build practical skills, gain industry-recognized expertise, and prepare for global career opportunities in high-demand cloud data roles. Call 91-7032290546 today to enroll.<br>Visit: https://www.visualpath.in/online-aws-data-engineering-course.html<br>WhatsApp: https://wa.me/c/917032290546<br>Blog link: https://visualpathblogs.com/category/aws-data-engineering-with-data-an

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AWS Data Analytics Training - AWS Data Engineering training

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  1. Real-Time Data Engineering with AWS Cloud Tools • Overview of real-time data engineering • Importance in modern data-driven businesses • Leveraging AWS Cloud for scalable solutions • Presenter name & designation • Date & event/organization

  2. Introduction to Real-Time Data Engineering • Definition of real-time data engineering • Key objectives: low-latency, high throughput • Difference between batch and real-time processing • Benefits: faster insights, improved decision-making • Increasing relevance in IoT, streaming analytics, and AI

  3. AWS Cloud Tools for Data Engineering • Amazon Kinesis: real-time streaming and analytics • AWS Lambda: serverless compute for real-time processing • Amazon S3: scalable storage for raw and processed data • Amazon Redshift & Redshift Spectrum: fast data warehousing • AWS Glue: ETL automation and data cataloging

  4. Real-Time Data Ingestion • Collect streaming data using Amazon Kinesis Data Streams • Use AWS IoT Core for device-generated data • Amazon MSK (Managed Kafka) for scalable message streaming • Lambda for event-driven processing • Ensuring reliable and continuous data flow

  5. Data Processing and Transformation • Real-time ETL with AWS Glue and Lambda • Stream processing using Kinesis Data Analytics • Applying filters, aggregations, and enrichments • Integration with Amazon Redshift and S3 for storage • Handling schema evolution and data quality

  6. Real-Time Analytics and Insights • Visualization with Amazon QuickSight • Real-time dashboards for monitoring and alerts • Machine learning inference with SageMaker endpoints • KPI tracking and anomaly detection • Use cases: fraud detection, predictive maintenance, personalization

  7. Security, Scalability, and Reliability • AWS IAM and encryption for secure data access • Auto-scaling of Kinesis, Lambda, and Redshift • Ensuring high availability and fault tolerance • Monitoring and logging with CloudWatch • Cost optimization strategies

  8. Summary & Next Steps • AWS provides end-to-end real-time data engineering tools • Enables faster, data-driven decisions • Scalable, secure, and cost-effective solutions • Key takeaway: real-time insights drive competitive advantage • Next steps: hands-on labs, pilot projects, and certifications

  9. Contact Us Flat no: 205, 2nd Floor, NILGIRI Block, Aditya Enclave, Ameerpet, Hyderabad-16 Mobile No: +91 7032290546 online@visualpath.in

  10. THANK YOU

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