• The importance of streaming data analytics
• The streaming data analytics pipeline
• Streaming concepts

• Streaming data services in AWS
• Amazon Kinesis in analytics solutions
• Demonstration: Explore Amazon Kinesis Data Streams
• Practice Lab: Setting up a streaming delivery pipeline with Amazon Kinesis
• Using Amazon Kinesis Data Analytics
• Introduction to Amazon MSK
• Overview of Spark Streaming

• Exploring Amazon Kinesis using a clickstream workload
• Creating Kinesis data and delivery streams
• Demonstration: Understanding producers and consumers
• Building stream producers
• Building stream consumers
• Building and deploying Flink applications in Kinesis Data Analytics
• Demonstration: Explore Zeppelin notebooks for Kinesis Data Analytics
• Practice Lab: Streaming analytics with Amazon Kinesis Data
  Analytics and Apache Flink

• Optimize Amazon Kinesis to gain actionable business insights
• Security and monitoring best practices

• Use cases for Amazon MSK
• Creating MSK clusters
• Demonstration: Provisioning an MSK Cluster
• Ingesting data into Amazon MSK
• Practice Lab: Introduction to access control with Amazon MSK
• Transforming and processing in Amazon MSK

• Optimizing Amazon MSK
• Demonstration: Scaling up Amazon MSK storage
• Practice Lab: Amazon MSK streaming pipeline and application deployment
• Security and monitoring
• Demonstration: Monitoring an MSK cluster

• Use case review
• Class Exercise: Designing a streaming data analytics workflow

Modern data architectures

A: This training is suitable for data engineers, data architects, and IT professionals who want to leverage streaming data and build real-time analytics solutions on AWS. It is beneficial for those involved in processing and analyzing high-velocity data streams, as well as individuals responsible for architecting scalable and performant streaming data pipelines.

A: The training covers a range of topics, including streaming data concepts, data ingestion using Amazon Kinesis, real-time data processing with AWS Lambda and Amazon Kinesis Data Analytics, data storage and indexing using Amazon Elasticsearch, building analytics dashboards with Amazon QuickSight, and best practices for building scalable and resilient streaming data analytics solutions.

A:

• 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

A: To prepare for the training, it is recommended to have a good understanding of data concepts, including streaming data, data processing, and analytics. Familiarizing yourself with AWS services such as Amazon Kinesis, AWS Lambda, and Amazon Elasticsearch will also be advantageous. Exploring AWS documentation and hands-on exercises related to streaming data analytics can enhance your preparation.

A: To register for the training, click Enroll Now, we will provide you with information on available training schedules, formats (in-person or online), and enrollment procedures.

A: Yes, we offers online training options for Building Streaming Data Analytics Solutions on AWS to provide flexibility for learners.

A: While Building Streaming Data Analytics Solutions on AWS training provides valuable knowledge and skills in building streaming data analytics solutions, it does not directly prepare you for specific AWS certifications. However, it lays a solid foundation for pursuing advanced certifications related to data analytics or AWS architecture.