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This is an introductory course on Amazon Kinesis Analytics, which helps you query streaming data or build entire streaming applications using SQL.

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This is an introductory course on Amazon Kinesis Analytics, which helps you query streaming data or build entire streaming applications using SQL.

This is an introductory course on Amazon Kinesis Analytics, which helps you query streaming data or build entire streaming applications using SQL. In this course, we discuss how the service collects, processes and analyzes streaming data in real-time. We also discuss how to use and monitor Amazon Kinesis Analytics and explore use cases.

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What's inside

Syllabus

Introduction to Amazon Kinesis Analytics

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Taught by AWS, which is recognized for its work in Cloud Computing
Explores SQL, which is an industry standard for data analytics
Develops foundational skills in querying streaming data using SQL
Builds skills in working with Amazon Kinesis Analytics

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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 Introduction to Amazon Kinesis Analytics with these activities:
Review SQL
Strengthen foundational skills in SQL that are necessary for this course
Browse courses on SQL
Show steps
  • Review online tutorials on SQL basics
  • Practice writing queries on sample datasets
Seek guidance from experts in Amazon Kinesis Analytics
Accelerate your learning by connecting with experienced professionals who can provide guidance
Show steps
  • Identify potential mentors through online platforms or industry events
  • Reach out to mentors and request guidance
  • Build a relationship and schedule regular meetings
Explore Amazon Kinesis Analytics documentation
Familiarize yourself with the key concepts and functionalities of Amazon Kinesis Analytics
Show steps
  • Read the Amazon Kinesis Analytics developer guide
  • Follow along with the Amazon Kinesis Analytics tutorials
Four other activities
Expand to see all activities and additional details
Show all seven activities
Build a simple streaming application using Amazon Kinesis Analytics
Apply your understanding of Amazon Kinesis Analytics by building a practical application
Show steps
  • Create an Amazon Kinesis Analytics application
  • Configure the data sources and processing logic
  • Deploy and test the application
Participate in online forums and provide assistance to others using Amazon Kinesis Analytics
Enhance your understanding of Amazon Kinesis Analytics by helping others and engaging in discussions
Show steps
  • Join online forums or communities related to Amazon Kinesis Analytics
  • Monitor discussions and identify opportunities to provide assistance
  • Share your knowledge and help others solve problems
Write a blog post or article about Amazon Kinesis Analytics
Solidify your understanding of Amazon Kinesis Analytics by sharing your knowledge with others
Show steps
  • Choose a specific topic related to Amazon Kinesis Analytics
  • Research and gather information from reliable sources
  • Write and edit your blog post or article
  • Publish and promote your content
Contribute to open-source projects related to Amazon Kinesis Analytics
Gain hands-on experience and contribute to the Amazon Kinesis Analytics community
Show steps
  • Identify open-source projects related to Amazon Kinesis Analytics
  • Review the project documentation and identify areas for contribution
  • Submit pull requests with your contributions

Career center

Learners who complete Introduction to Amazon Kinesis Analytics will develop knowledge and skills that may be useful to these careers:
Data Scientist
A Data Scientist is responsible for using data to solve business problems. The Amazon Kinesis Analytics course may be useful for this role, as it provides an introduction to streaming data processing and analysis. This course can help Data Scientists learn how to use Amazon Kinesis Analytics to analyze streaming data in real-time. This can be useful for Data Scientists who are working with streaming data or who are interested in building streaming data applications.
Business Analyst
A Business Analyst is responsible for analyzing business processes and identifying opportunities for improvement. The Amazon Kinesis Analytics course may be useful for this role, as it provides an introduction to streaming data processing and analysis. This course can help Business Analysts learn how to use Amazon Kinesis Analytics to analyze streaming data in real-time. This can be useful for Business Analysts who are working with streaming data or who are interested in analyzing streaming data in real-time.
Data Architect
A Data Architect is responsible for designing and managing data systems. The Amazon Kinesis Analytics course may be useful for this role, as it provides an introduction to streaming data processing and analysis. This course can help Data Architects learn how to use Amazon Kinesis Analytics to design and manage streaming data systems. This can be useful for Data Architects who are working with streaming data or who are interested in designing and managing streaming data systems.
Software Engineer
A Software Engineer is responsible for designing, building, and maintaining software applications. The Amazon Kinesis Analytics course may be useful for this role, as it provides an introduction to streaming data processing and analysis. This course can help Software Engineers learn how to use Amazon Kinesis Analytics to build streaming data applications. This can be useful for Software Engineers who are working with streaming data or who are interested in building streaming data applications.
Data Analyst
A Data Analyst is responsible for collecting, cleaning, and analyzing data to help businesses make informed decisions. The Amazon Kinesis Analytics course may be useful for this role, as it provides an introduction to streaming data processing and analysis. This course can help Data Analysts learn how to use Amazon Kinesis Analytics to collect, process, and analyze streaming data in real-time. This can be useful for Data Analysts who are working with streaming data or who are interested in building streaming data applications.
Database Administrator
A Database Administrator is responsible for managing and maintaining databases. The Amazon Kinesis Analytics course may be useful for this role, as it provides an introduction to streaming data processing and analysis. This course can help Database Administrators learn how to use Amazon Kinesis Analytics to manage and maintain streaming data. This can be useful for Database Administrators who are working with streaming data or who are interested in managing and maintaining streaming data.
Marketing Analyst
A Marketing Analyst is responsible for analyzing marketing data to identify opportunities for improvement. The Amazon Kinesis Analytics course may be useful for this role, as it provides an introduction to streaming data processing and analysis. This course can help Marketing Analysts learn how to use Amazon Kinesis Analytics to analyze streaming data in real-time. This can be useful for Marketing Analysts who are working with streaming data or who are interested in analyzing streaming data in real-time.
Risk Analyst
A Risk Analyst is responsible for identifying and assessing risks. The Amazon Kinesis Analytics course may be useful for this role, as it provides an introduction to streaming data processing and analysis. This course can help Risk Analysts learn how to use Amazon Kinesis Analytics to analyze streaming data in real-time. This can be useful for Risk Analysts who are working with streaming data or who are interested in analyzing streaming data in real-time.
Product Manager
A Product Manager is responsible for managing the development and launch of new products. The Amazon Kinesis Analytics course may be useful for this role, as it provides an introduction to streaming data processing and analysis. This course can help Product Managers learn how to use Amazon Kinesis Analytics to analyze streaming data in real-time. This can be useful for Product Managers who are working with streaming data or who are interested in analyzing streaming data in real-time.
Data Engineer
A Data Engineer is responsible for designing, building, and maintaining data pipelines. The Amazon Kinesis Analytics course may be useful for this role, as it provides an introduction to streaming data processing and analysis. This course can help Data Engineers learn how to use Amazon Kinesis Analytics to build streaming data pipelines. This can be useful for Data Engineers who are working with streaming data or who are interested in building streaming data applications.
Cloud Architect
A Cloud Architect is responsible for designing and implementing cloud computing solutions. The Amazon Kinesis Analytics course may be useful for this role, as it provides an introduction to streaming data processing and analysis in the cloud. This course can help Cloud Architects learn how to use Amazon Kinesis Analytics to build streaming data applications in the cloud. This can be useful for Cloud Architects who are working with streaming data or who are interested in building streaming data applications in the cloud.
DevOps Engineer
A DevOps Engineer is responsible for bridging the gap between development and operations teams. The Amazon Kinesis Analytics course may be useful for this role, as it provides an introduction to streaming data processing and analysis. This course can help DevOps Engineers learn how to use Amazon Kinesis Analytics to build and maintain streaming data applications. This can be useful for DevOps Engineers who are working with streaming data or who are interested in building and maintaining streaming data applications.
Security Analyst
A Security Analyst is responsible for identifying and preventing security breaches. The Amazon Kinesis Analytics course may be useful for this role, as it provides an introduction to streaming data processing and analysis. This course can help Security Analysts learn how to use Amazon Kinesis Analytics to analyze streaming data in real-time. This can be useful for Security Analysts who are working with streaming data or who are interested in analyzing streaming data in real-time.
Sales Analyst
A Sales Analyst is responsible for analyzing sales data to identify opportunities for improvement. The Amazon Kinesis Analytics course may be useful for this role, as it provides an introduction to streaming data processing and analysis. This course can help Sales Analysts learn how to use Amazon Kinesis Analytics to analyze streaming data in real-time. This can be useful for Sales Analysts who are working with streaming data or who are interested in analyzing streaming data in real-time.
Fraud Analyst
A Fraud Analyst is responsible for identifying and preventing fraud. The Amazon Kinesis Analytics course may be useful for this role, as it provides an introduction to streaming data processing and analysis. This course can help Fraud Analysts learn how to use Amazon Kinesis Analytics to analyze streaming data in real-time. This can be useful for Fraud Analysts who are working with streaming data or who are interested in analyzing streaming data in real-time.

Reading list

We've selected nine 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 Introduction to Amazon Kinesis Analytics.
Provides a comprehensive overview of data-intensive application design principles and patterns. It can serve as a valuable reference for learners who want to gain a deeper understanding of the architectural considerations for building streaming applications with Amazon Kinesis Analytics.
Explores the application of machine learning techniques to streaming data. It can provide valuable insights for learners who want to understand how Amazon Kinesis Analytics can be extended with machine learning capabilities for real-time data analysis and decision-making.
Provides a practical guide to big data analytics, including a discussion of stream processing. It covers topics such as data collection, storage, processing, and analysis.
Provides a practical guide to data science using the R programming language. Although it does not cover Kinesis Analytics, it provides a good overview of the principles of data science.
Provides a comprehensive overview of stream processing with Apache Flink. It covers the basics of Flink, as well as more advanced topics such as using Flink SQL and Flink Machine Learning to build streaming applications.
Provides a comprehensive overview of D3.js, with a focus on using D3.js to create data visualizations. It covers the basics of D3.js, as well as more advanced topics such as using D3.js to create interactive data visualizations.
Provides a comprehensive overview of machine learning with Python. It covers the basics of machine learning, as well as more advanced topics such as using machine learning for natural language processing and computer vision.
Provides a comprehensive overview of deep learning with Python. It covers the basics of deep learning, as well as more advanced topics such as using deep learning for natural language processing and computer vision.
Provides a comprehensive overview of reinforcement learning with Python. It covers the basics of reinforcement learning, as well as more advanced topics such as using reinforcement learning for game playing and robotics.

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