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Beth Hord

In this deep dive into Amazon Kinesis, you will learn the ins and outs of the four main Kinesis branches and explore both the data producers that can feed into Kinesis, and the data consumers that can accept Kinesis streams.

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Teaches how to use Amazon Kinesis Data Streams and Data Firehose, which are commonly used in industry
Taught by Beth Hord, who is recognized for their work in cloud technologies
Develops understanding of data producers and consumers that can be used with Kinesis, which is core knowledge for a data engineer
Examines data streaming, which is highly relevant to building big data solutions

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Amazon Kinesis Deep Dive with these activities:
Review Cloud Computing Concepts
Update your knowledge of core cloud computing concepts to enhance your comprehension of the course materials.
Browse courses on Cloud Computing
Show steps
  • Read articles and blog posts about cloud computing trends.
  • Watch online videos and tutorials on cloud computing basics.
  • Explore cloud provider documentation to understand different services and offerings.
Review Python or Java Basics
Refresh your programming skills in Python or Java to enhance your ability to work with and process data effectively in Kinesis.
Browse courses on Python
Show steps
  • Review basic data structures and algorithms.
  • Practice writing simple code snippets.
  • Complete a coding challenge or exercise.
Kinesis Discussion Forum Participation
Engage with fellow learners and industry professionals to share knowledge, resolve doubts, and expand your understanding of Kinesis.
Browse courses on Community Engagement
Show steps
  • Join an online Kinesis discussion forum.
  • Read through existing discussions and participate in ongoing threads.
  • Ask questions, share insights, and contribute to the community's knowledge base.
  • Attend live Q&A sessions or webinars organized by the forum.
Four other activities
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Hands-on Tutorial on Setting Up Kinesis
Gain practical experience in setting up and configuring Kinesis for data streaming, reinforcing your understanding of its capabilities.
Browse courses on Kinesis
Show steps
  • Follow an online tutorial to set up Kinesis on your local environment.
  • Create a Kinesis stream and configure it with appropriate settings.
  • Test the stream by sending and receiving sample data.
Kinesis Data Producer Exercises
Enhance your understanding of Kinesis data producers by exploring and practicing with different methods of ingesting data.
Browse courses on Data Ingestion
Show steps
  • Experiment with different data producer libraries for Python or Java.
  • Create sample data and use Firehose to ingest it into a Kinesis stream.
  • Set up Kinesis Agent and configure it to send data from on-premises sources.
Kinesis Deployment Plan
Solidify your understanding of Kinesis deployment by creating a comprehensive plan that addresses scalability, resilience, and cost optimization.
Show steps
  • Analyze your data requirements and usage patterns.
  • Design a deployment architecture that meets your performance and availability needs.
  • Estimate the cost of your deployment and identify potential cost-saving strategies.
  • Create a deployment checklist to ensure a smooth and successful implementation.
Develop a Kinesis Data Pipeline
Apply your knowledge by building a complete Kinesis data pipeline, integrating with other AWS services to process and analyze data.
Browse courses on Data Processing
Show steps
  • Design a data pipeline architecture using Kinesis, Lambda, and S3.
  • Implement the pipeline using AWS tools and services.
  • Test and evaluate the pipeline's performance and accuracy.

Career center

Learners who complete Amazon Kinesis Deep Dive will develop knowledge and skills that may be useful to these careers:
Data Engineer
A Data Engineer designs, builds, deploys, and maintains the systems and infrastructure used to store and process data. This course would provide a deep understanding of Amazon Kinesis, which is widely used for streaming data. This understanding is essential for Data Engineers who want to design and implement efficient and scalable data pipelines.
Data Architect
A Data Architect designs and implements the architecture for data management systems, including data storage, processing, and analytics. This course would help Data Architects gain a deep understanding of Amazon Kinesis, which is a key component in modern data architectures for handling streaming data.
Data Scientist
A Data Scientist uses data to extract insights and build predictive models. This course would help Data Scientists understand how to use Amazon Kinesis to stream data into their analytics pipelines, enabling them to work with real-time data and build more accurate and responsive models.
Machine Learning Engineer
A Machine Learning Engineer builds and deploys machine learning models. This course would be particularly valuable for Machine Learning Engineers who want to use Amazon Kinesis to stream data into their machine learning models, allowing them to train and deploy models on real-time data.
Big Data Engineer
A Big Data Engineer designs and manages big data systems and applications. This course would provide a strong foundation in Amazon Kinesis, which is a key technology for processing and analyzing big data streams.
Software Engineer
A Software Engineer designs, develops, and maintains software systems. This course would be useful for Software Engineers who want to build applications that use Amazon Kinesis for streaming data.
Cloud Architect
A Cloud Architect designs and implements cloud computing solutions. This course would provide a deep understanding of Amazon Kinesis, which is a key service in the AWS cloud platform.
DevOps Engineer
A DevOps Engineer automates and manages the software development lifecycle. This course would help DevOps Engineers understand how to use Amazon Kinesis to build and deploy streaming data pipelines.
Data Analyst
A Data Analyst analyzes data to identify trends and make recommendations. This course would provide a foundation in Amazon Kinesis, which can be used to stream data for real-time analysis.
Database Administrator
A Database Administrator manages and maintains databases. This course would help Database Administrators understand how to use Amazon Kinesis for streaming data into and out of databases.
Systems Engineer
A Systems Engineer designs, implements, and maintains computer systems. This course would be useful for Systems Engineers who want to use Amazon Kinesis for streaming data in distributed systems.
Network Engineer
A Network Engineer designs, implements, and maintains computer networks. This course may be useful for Network Engineers who want to use Amazon Kinesis for streaming data over networks.
Security Analyst
A Security Analyst investigates and responds to security incidents. This course may be useful for Security Analysts who want to use Amazon Kinesis for streaming security data.
IT Manager
An IT Manager plans and manages the IT infrastructure and resources of an organization. This course may be useful for IT Managers who want to understand how Amazon Kinesis can be used to improve the efficiency and scalability of their IT systems.
Project Manager
A Project Manager plans and manages projects. This course may be useful for Project Managers who want to understand how Amazon Kinesis can be used to improve the efficiency and scalability of their projects.

Reading list

We've selected five books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Amazon Kinesis Deep Dive.
Provides a theoretical foundation for building data-intensive applications, including topics such as data modeling, fault tolerance, and scalability, which are essential for understanding Amazon Kinesis.
Provides a comprehensive overview of cloud computing with AWS, including a discussion of Amazon Kinesis and other cloud computing technologies. It's a great resource for anyone who wants to learn more about the different approaches to cloud computing with AWS.
Provides a comprehensive overview of data science for business, including a discussion of Amazon Kinesis and other data science technologies. It's a great resource for anyone who wants to learn more about the different approaches to data science for business.
Provides a comprehensive overview of machine learning for beginners, including a discussion of Amazon Kinesis and other machine learning technologies. It's a great resource for anyone who wants to learn more about the different approaches to machine learning for beginners.
Provides a comprehensive overview of artificial intelligence for dummies, including a discussion of Amazon Kinesis and other artificial intelligence technologies. It's a great resource for anyone who wants to learn more about the different approaches to artificial intelligence for dummies.

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