The Building Streaming Data Analytics Solutions on AWS course is designed to equip learners with the expertise to build real-time analytics solutions using AWS streaming services. This hands-on training focuses on ingesting, processing, analyzing, and visualizing data as it flows in real time, enabling organizations to make timely, data-driven decisions.

The course covers key areas such as:

• Introduction to Data Analytics Use Cases: Exploring real-world applications of data analytics and understanding the value of real-time data.
• Role of Data Pipelines: Understanding how data pipelines enable scalable and reliable analytics workflows.
• Streaming Data Analytics Fundamentals: Learning the significance of real-time analytics and the architecture of a streaming pipeline.
• AWS Streaming Services Overview: Gaining insight into Amazon Kinesis, Amazon MSK (Managed Streaming for Apache Kafka), and how they support streaming use cases.
• Data Ingestion and Transformation: Using Kinesis Data Streams and MSK to ingest and transform data for immediate processing.
• Real-Time Analytics with Kinesis Data Analytics: Implementing Apache Flink and SQL-based applications to perform real-time analytics.
• Advanced Stream Processing with Spark Streaming: Utilizing Apache Spark for complex and scalable analytics solutions on AWS.
• Security, Monitoring, and Optimization: Applying AWS best practices for securing streaming data, monitoring pipelines, and tuning performance.
• Designing Streaming Workflows: Architecting end-to-end solutions to meet business needs and scale with demand.
• Modern Data Architectures: Integrating streaming pipelines into modern, cloud-native data platforms.

By the end of this course, learners will be able to:

• Understand streaming data use cases and the benefits of real-time analytics
• Design and implement scalable data pipelines using AWS services
• Ingest and transform streaming data using Amazon Kinesis and Amazon MSK
• Develop real-time analytics applications using Amazon Kinesis Data Analytics and Apache Flink
• Leverage Spark Streaming for complex real-time data processing
• Secure, monitor, and optimize streaming pipelines for reliability and performance
• Build robust solutions that deliver actionable insights from real-time data
• Integrate streaming pipelines into modern AWS-based data architectures
• Align real-time analytics solutions with organizational data strategies

This course enables participants to build end-to-end streaming analytics solutions that support rapid decision-making and operational intelligence.

Course Prerequisites

To ensure success in this course, participants should meet the following prerequisites:

• Basic understanding of data analytics concepts and real-time data use cases
• Familiarity with data pipelines and their purpose in analytics
• Working knowledge of AWS core services (compute, storage, networking)
• Experience using the AWS Management Console and AWS CLI
• Some exposure to big data technologies (recommended but not mandatory)
• Basic programming proficiency in Python, Java, or Scala
• Understanding of distributed systems and database principles
• Interest in leveraging streaming data to power real-time insights

These prerequisites provide the foundation necessary for success. Learners new to AWS or real-time analytics are encouraged to explore foundational content before diving into this course.

Target Audience

The Building Streaming Data Analytics Solutions on AWS course is ideal for professionals seeking to design and implement real-time analytics systems on AWS, including:

• Data Engineers
• Cloud Solutions Architects
• Data Analysts
• IT Professionals interested in data workflows
• Software Developers building analytics features
• DevOps Engineers managing data infrastructure
• Technical Project Managers leading analytics projects
• System Administrators upgrading analytics toolsets
• Business Intelligence (BI) Professionals utilizing real-time data
• Data Scientists applying streaming data in predictive models
• AWS Certified Professionals pursuing advanced specializations
• Database Administrators transitioning to streaming solutions
• Enterprise Architects working on modern data platforms
• Technical Leads managing cloud-native analytics teams

Why Choose us

⭢ Live Online Training (Duration : 8 Hours)

⭢ Guaranteed to run classes

⭢ Experienced & certified trainers

⭢ Query Handling session

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Learning Objectives

After completing the Building Streaming Data Analytics Solutions on AWS course, learners will be able to:

• Explain real-time data use cases and the role of pipelines in analytics
• Understand the architecture and flow of a streaming analytics pipeline
• Utilize Amazon Kinesis and Amazon MSK for data ingestion and processing
• Implement real-time applications using Apache Flink and Kinesis Data Analytics
• Apply Spark Streaming for advanced analytics workflows on AWS
• Ensure secure, monitored, and optimized streaming solutions
• Design and build real-time streaming analytics systems for various industries
• Incorporate streaming pipelines into modern AWS-based architectures
• Support data-driven decisions with immediate, actionable insights
• Prepare for further AWS certifications and advanced data engineering paths