Building Streaming Data Analytics Solutions on AWS Training

Live Online & Classroom Enterprise Certification Training

Building Streaming Data Analytics Solutions on AWS is a course that teaches how to design and implement real-time data processing applications using AWS services like Amazon Kinesis, AWS Lambda, and Amazon MSK.

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What is Building Streaming Data Analytics Solutions on AWS Certification Training about?

In this course, you will learn to build streaming data analytics solutions using AWS services, including Amazon Kinesis and Amazon Managed Streaming for Apache Kafka (Amazon MSK). Amazon Kinesis is a massively scalable and durable real-time data streaming service. Amazon MSK offers a secure, fully managed, and highly available Apache Kafka service. You will learn how Amazon Kinesis and Amazon MSK integrate with AWS services such as AWS Glue and AWS Lambda. The course addresses the streaming data ingestion, stream storage, and stream processing components of the data analytics pipeline. You will also learn to apply security, performance, and cost management best practices to the operation of Kinesis and Amazon MSK.

What are the objectives of Building Streaming Data Analytics Solutions on AWS Certification Training ?

In this course, you will learn to:

Understand the features and benefits of a modern data architecture. Learn how AWS streaming services fit into a modern data architecture.
Design and implement a streaming data analytics solution
Identify and apply appropriate techniques, such as compression, sharding, and partitioning, to optimize data storage
Select and deploy appropriate options to ingest, transform, and store real-time and near real-time data
Choose the appropriate streams, clusters, topics, scaling approach, and network topology for a particular business use case
Understand how data storage and processing affect the analysis and visualization mechanisms needed to gain actionable business insights
Secure streaming data at rest and in transit
Monitor analytics workloads to identify and remediate problems
Apply cost management best practices

Who is Building Streaming Data Analytics Solutions on AWS Certification Training for?

This course is intended for:

Data engineers and architects
Developers who want to build and manage real-time applications and streaming data analytics solutions

What are the prerequisites for Building Streaming Data Analytics Solutions on AWS Certification Training?

We recommend that attendees of this course have:

At least one year of data analytics experience or direct experience building real-time applications or streaming analytics solutions. We suggest the Streaming Data Solutions on AWS whitepaper for those that need a refresher on streaming concepts.

Completed either Architecting on AWS or Data Analytics Fundamentals
Completed Building Data Lakes on AWS

Available Training Modes

Live Online Training

Classroom Training

1 Days

Course Outline Expand All

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Module 1: Introduction to Streaming Analytics

What is streaming data?

Batch vs. streaming vs. micro-batching

Common use cases: IoT, clickstreams, fraud detection, logs

Overview of AWS services for streaming analytics

Module 2: Ingesting Streaming Data

Key services:

Amazon Kinesis Data Streams

Amazon Kinesis Data Firehose

Amazon MSK (Managed Streaming for Apache Kafka)

Choosing the right ingestion service

Producers and partitioning concepts

Retention, shard management, and scaling

Module 3: Processing Streaming Data

Amazon Kinesis Data Analytics (KDA)

SQL-based and Apache Flink-based stream processing

AWS Lambda for lightweight event processing

Apache Flink on Kinesis: time windowing, watermarking, aggregations

Stateless vs. stateful streaming applications

Handling late or out-of-order data

Module 4: Storing Streaming Data

Writing processed or raw data to:

Amazon S3 (data lake)

Amazon Redshift (analytics)

Amazon OpenSearch Service (real-time search and dashboards)

Amazon DynamoDB (NoSQL storage)

Module 5: Analyzing and Visualizing Streaming Data

Integrating Kinesis with Amazon QuickSight

Using Athena to query streaming data stored in S3

Dashboards and alerts using OpenSearch

Real-time metrics pipelines and visualizations

Module 6: Designing Scalable and Resilient Architectures

Auto-scaling with shards and Lambda concurrency

Fault tolerance: retry strategies, dead-letter queues

Event-driven architecture design patterns

High availability and disaster recovery for streaming apps

Module 7: Security and Monitoring

IAM permissions and encryption

Data protection in transit and at rest

Monitoring with CloudWatch Logs, metrics, alarms

Kinesis-specific metrics (IncomingBytes, IteratorAge, etc.)

Logging and audit with AWS CloudTrail

Module 8: Cost Optimization

Cost drivers for Kinesis, Lambda, Firehose, etc.

Choosing right data retention settings

Data compression and format optimization

Resource scaling to control cost

Module 9: Use Cases and Design Patterns

Real-time log analytics

IoT sensor data pipelines

Fraud detection in financial services

Clickstream analysis for marketing insights

Multi-region stream processing architecture

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Who is the instructor for this training?

The trainer for this Building Streaming Data Analytics Solutions on AWS Training has extensive experience in this domain, including years of experience training & mentoring professionals.

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