Amazon Web Services (AWS)
Building Streaming Data Analytics Solutions on AWS
Analyse data the moment it arrives.
1 dayIntermediate9 modules
About this course
Analyse data the moment it arrives. You will design streaming pipelines with Amazon Kinesis and Amazon MSK, apply partitioning and compression, and secure, monitor and optimise real-time analytics.
What you'll learn
- 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
Curriculum
9 modules
- Data analytics use cases
- Using the data pipeline for analytics
- 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
Who it's for
Data engineers and developers building real-time data solutions.
Before you start
- At least one year of data analytics experience or direct experience building real-time applications or streaming analytics solutions.
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