To ensure a successful learning experience in the Building Streaming Data Analytics Solutions on AWS course, participants should meet the following minimum prerequisites:
- Basic understanding of data analytics concepts and the significance of real-time data processing.
- Familiarity with the concept of a data pipeline and its role in data analytics.
- Working knowledge of AWS core services, particularly those related to compute, storage, and networking.
- Experience with AWS management console and AWS CLI (Command Line Interface).
- Some familiarity with big data technologies and services available on AWS is recommended but not mandatory.
- Basic proficiency in a programming language such as Python, Java, or Scala, as the course may involve writing code snippets or scripts.
- Understanding of distributed systems and database concepts.
- Enthusiasm to learn about streaming data and real-time analytics solutions.
Please note that these prerequisites are meant to provide a foundation for the course material. The course is designed to guide you through more advanced concepts, building on the knowledge you bring.
Target Audience for Building Streaming Data Analytics Solutions on AWS
"Building Streaming Data Analytics Solutions on AWS" is a course designed for IT professionals looking to harness the power of AWS for real-time data analytics.
- Data Engineers
- Cloud Solutions Architects
- Data Analysts
- IT Professionals interested in data analytics
- Software Developers with a focus on analytics applications
- DevOps Engineers working with data-intensive workflows
- Technical Project Managers overseeing analytics projects
- System Administrators aiming to upgrade their analytics toolsets
- Business Intelligence (BI) Professionals seeking to leverage streaming data
- Data Scientists requiring real-time data for predictive modeling
- AWS Certified Professionals aiming to specialize in streaming data solutions
- Database Administrators expanding their skills to cloud-based streaming analytics
- Enterprise Architects designing modern data architectures on AWS
- Technical Leads managing teams building analytics solutions on cloud platforms
Learning Objectives - What you will Learn in this Building Streaming Data Analytics Solutions on AWS?
Introduction to Learning Outcomes:
Gain proficiency in AWS streaming data services for real-time analytics. Learn how to build, secure, monitor, and optimize streaming solutions to extract actionable insights.
Learning Objectives and Outcomes:
- Understand different data analytics use cases and the role of data pipelines.
- Learn the significance of streaming data analytics and the components of a streaming data analytics pipeline.
- Acquire knowledge of AWS streaming services, including Amazon Kinesis and Amazon Managed Streaming for Apache Kafka (Amazon MSK).
- Set up and manage Amazon Kinesis Data Streams for real-time data ingestion and processing.
- Develop the skills to create and deploy applications using Amazon Kinesis Data Analytics and Apache Flink.
- Explore and utilize Spark Streaming for complex analytics workflows on AWS.
- Implement security best practices and monitoring for Amazon Kinesis and Amazon MSK to ensure data integrity and system health.
- Optimize the performance of Amazon Kinesis and Amazon MSK to handle large-scale streaming data efficiently.
- Design robust streaming data analytics solutions tailored to specific business use cases.
- Understand modern data architectures on AWS, enabling the integration of streaming data solutions into a broader data strategy.
Intermediate
