Building Streaming Data Analytics Solutions on AWS

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.

This course is intended for Data engineers, architects and Developers who want to build and manage real-time applications and streaming data analytics solutions.

1 Days

Live Class

Certificate on completion

15,000

Choose a date

You will learn about the following

  • 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

What experience you need

  • 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

Who should take this course

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

Module 0: Overview of Data Analytics and the Data Pipeline

  • Data analytics use cases
  • Using the data pipeline for analytics

Module 1: Using Streaming Services in the Data Analytics Pipeline

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

Module 2: Introduction to AWS Streaming Services

  • 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

Module 3: Using Amazon Kinesis for Real-time Data Analytics

  • 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

Module 4: Securing, Monitoring, and Optimizing Amazon Kinesis

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

Module 5: Using Amazon MSK in Streaming Data Analytics Solutions

  • 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

Module 6: Securing, Monitoring, and Optimizing 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

Module 7: Designing Streaming Data Analytics Solutions

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

Module 8: Developing Modern Data Architectures on AWS

  • Modern data architectures

Talk to a Learning Advisor

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Popular AWS Courses

FAQs

To enroll in this course, choose the starting date and make an online payment. Once your payment is confirmed, our team will reach out to you.

You may reach out at the contact number listed on our official website or write us at info@cloudwizardconsulting.com

Wire Transfer, Credit Card, Debit Card, UPI & Purchase Order.

There is no minimum number of candidates required, we are happy to train 1 to 1 . With regards to the maximum number, we can accomodate 30 learners in one batch.

  1. Training Delivered by an Amazon Authorized Instructor.
  2. AWS Content E-Kit
  3. Hands-on-labs for 30 days
  4. Class attendance certificate

You will get the access to course content & lab on first day of your training session.

The course Completion Certificate will be issued to your email id within 2 weeks of completing your course.

A one-day course could be delivered over two half day sessions (4 hours a day), or a three-day course could be delivered over five days (4 hours a day)

MOBILE LAYOUT

Building Streaming Data Analytics Solutions on AWS

1 Days

Live Class

Certificate on completion

15,000

(Taxes Extra)

Choose a date

In this Building Streaming Data Analytics Solutions on AWS 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

Attendees of this Building Streaming Data Analytics Solutions course are advised to have the following: 

  • 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

The following group of individuals are likely to benefit

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

Module 0: Overview of Data Analytics and the Data Pipeline

  • Data analytics use cases
  • Using the data pipeline for analytics

Module 1: Using Streaming Services in the Data Analytics Pipeline

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

Module 2: Introduction to AWS Streaming Services

  • 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

Module 3: Using Amazon Kinesis for Real-time Data Analytics

  • 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

Module 4: Securing, Monitoring, and Optimizing Amazon Kinesis

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

Module 5: Using Amazon MSK in Streaming Data Analytics Solutions

  • 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

Module 6: Securing, Monitoring, and Optimizing 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

Module 7: Designing Streaming Data Analytics Solutions

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

Module 8: Developing Modern Data Architectures on AWS

  • Modern data architectures

Talk to a Learning Advisor

Please enable JavaScript in your browser to complete this form.

Tablet View

Popular AWS Courses

FAQs

To enroll in this course, choose the starting date and make an online payment. Once your payment is confirmed, our team will reach out to you.

You may reach out at the contact number listed on our official website or write us at info@cloudwizardconsulting.com

Wire Transfer, Credit Card, Debit Card, UPI & Purchase Order.

There is no minimum number of candidates required, we are happy to train 1 to 1 . With regards to the maximum number, we can accomodate 30 learners in one batch.

  1. Training Delivered by an Amazon Authorized Instructor.
  2. AWS Content E-Kit
  3. Hands-on-labs for 30 days
  4. Class attendance certificate

You will get the access to course content & lab on first day of your training session.

The course Completion Certificate will be issued to your email id within 2 weeks of completing your course.

A one-day course could be delivered over two half day sessions (4 hours a day), or a three-day course could be delivered over five days (4 hours a day)

Building Streaming Data Analytics Solutions on AWS

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.

This course is intended for Data engineers, architects and Developers who want to build and manage real-time applications and streaming data analytics solutions.

1 Days

Live Class

Certificate on completion

15,000

Choose a date

Objectives

In this Building Streaming Data Analytics Solutions on AWS 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

Prerequisites

Attendees of this Building Streaming Data Analytics Solutions course are advised to have the following: 

  • 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

Intended Audience

The following group of individuals are likely to benefit

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

Module 0: Overview of Data Analytics and the Data Pipeline

  • Data analytics use cases
  • Using the data pipeline for analytics

Module 1: Using Streaming Services in the Data Analytics Pipeline

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

Module 2: Introduction to AWS Streaming Services

  • 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

Module 3: Using Amazon Kinesis for Real-time Data Analytics

  • 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

Module 4: Securing, Monitoring, and Optimizing Amazon Kinesis

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

Module 5: Using Amazon MSK in Streaming Data Analytics Solutions

  • 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

Module 6: Securing, Monitoring, and Optimizing 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

Module 7: Designing Streaming Data Analytics Solutions

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

Module 8: Developing Modern Data Architectures on AWS

  • Modern data architectures

Talk to a Learning Advisor

Please enable JavaScript in your browser to complete this form.

FAQs

Yes, we are an AWS Advanced Tier Training Partner

Anyone who wants to start a profession in AWS cloud is fit to enroll in this course. No prior knowledge of coding or other technical skills is required.

To enroll in this course, choose the starting date and make an online payment. Once your payment is confirmed, our team will reach out to you.

You may reach out at the contact number listed on our official website or write to us at info@cloudwizard.wpenginepowered.com.

Wire Transfer, Credit Card, Debit Card, UPI & Purchase Order

There is no minimum number of candidates required, we are happy to train 1 to 1 should you wish. With regard to the maximum number, we can accommodate 30 learners in one batch.

1. Training delivered by an Amazon Authorised Instructor
2. AWS Content E-Kit
3. Hands-on labs- 30 days
4. Class attendance certificate

You will get the access to course content & lab on first day of your training session.

The course completion certificate will be issued to your email id within 2 weeks of completing your course.

A one-day course could be delivered over two half day sessions (4 hours a day), or a three-day course could be delivered over five days (4 hours a day).

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