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AWS: Data Collection Systems Course is the first course of the AWS Certified Data Analytics Speciality Specialization. This Course is designed to describe data collection systems and their characteristics in detail. This course is basically divided into three modules and each module is further segmented by Lessons and Video Lectures. This course facilitates learners with approximately 3:30-4:00 Hours Video lectures that provide both Theory and Hands -On knowledge. Also, Graded and Ungraded Quiz are provided with every module in order to test the ability of learners.
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AWS: Data Collection Systems Course is the first course of the AWS Certified Data Analytics Speciality Specialization. This Course is designed to describe data collection systems and their characteristics in detail. This course is basically divided into three modules and each module is further segmented by Lessons and Video Lectures. This course facilitates learners with approximately 3:30-4:00 Hours Video lectures that provide both Theory and Hands -On knowledge. Also, Graded and Ungraded Quiz are provided with every module in order to test the ability of learners.
Read more
AWS: Data Collection Systems Course is the first course of the AWS Certified Data Analytics Speciality Specialization. This Course is designed to describe data collection systems and their characteristics in detail. This course is basically divided into three modules and each module is further segmented by Lessons and Video Lectures. This course facilitates learners with approximately 3:30-4:00 Hours Video lectures that provide both Theory and Hands -On knowledge. Also, Graded and Ungraded Quiz are provided with every module in order to test the ability of learners.
Module 1: Data Collection Systems and Data Streams in AWS
Module 2: Data Integration Services in AWS
Module 3: Data Compression and Transformation in AWS
e.g. This is primarily aimed at first- and second-year undergraduates interested in engineering or science, along with high school students and professionals with an interest in programming.
Register for this course and see more details by visiting:
OpenCourser.com/course/4pubj0/aws
What's inside
Syllabus
Data Collection Systems and Data Streams in AWS
Welcome to Week 1 of the AWS: Data Collection Systems. This week, we will learn about data collection systems and implement Kinesis Data Streams and Kinesis Data Firehose. We will gain hands-on experience with real-time data streaming and learn how to effectively load stream data into data stores and processing services. By the end of the week, we should have a better understanding of how to use Kinesis services to process real-time data.
Read more
Syllabus
Data Collection Systems and Data Streams in AWS
Welcome to Week 1 of the AWS: Data Collection Systems. This week, we will learn about data collection systems and implement Kinesis Data Streams and Kinesis Data Firehose. We will gain hands-on experience with real-time data streaming and learn how to effectively load stream data into data stores and processing services. By the end of the week, we should have a better understanding of how to use Kinesis services to process real-time data.
Read more
Data Integration Services in AWS
Welcome to Week 2 of the AWS: Data Collection Systems.This week, we will explore data integration services and their characteristics. This will involve analyzing the frequency, volume, batch, streaming, and transactional data to determine the appropriate integration services needed. We will also gain hands-on experience with implementing the AWS Glue service, a fully managed ETL service that makes it easy to move data between data stores. By the end of the module, we should have a solid understanding of how to effectively integrate different types of data using AWS Glue and other data integration services.
Data Compression and Transformation in AWS
Welcome to Week 3 of the AWS: Data Collection Systems. This week, we will learn how to compare different data collection systems and choose the appropriate one for our needs. We will also explore how to implement data order, format, and compression techniques to optimize data ingestion processes. Additionally, we will analyze data transformation while ingesting the data in AWS to ensure the data is in a usable format for downstream applications. By the end of the week, we should have a solid understanding of how to optimize data ingestion processes and ensure the data is in a usable format for downstream applications.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Suitable for persons studying engineering or science in first or second year at undergraduate level
Appropriate for those with an interest in programming regardless of their current study or occupation
Introduces the Kinesis Data Streams and Kinesis Data Firehose for hands-on experience with real-time data streaming
Provides practical experience with AWS Glue, a fully managed ETL service, for seamless data integration
Covers data order, format, and compression techniques for optimizing data ingestion processes
Save this course
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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 AWS: Data Collection Systems with these
activities:
Create a study guide
Show steps
Creating a study guide will help students organize and review the course material.
Show steps
-
Gather your notes, handouts, and other course materials.
-
Review the material and identify the key concepts.
-
Organize the key concepts into a logical structure.
-
Create a study guide that summarizes the key concepts.
Review notes from prerequisite courses
Show steps
This course builds directly upon knowledge gained from prerequisite courses. Reviewing notes from these courses will activate prior knowledge and reinforce the concepts that will be covered in this course.
Browse courses on
Data Collection
Show steps
-
Locate notes from prerequisite courses.
-
Skim materials for main concepts.
-
Take additional notes or make annotations as needed.
Review database theory
Show steps
Reviewing fundamental database theory will help students as they begin to learn more advanced database concepts.
Browse courses on
Database Theory
Show steps
-
Read through your notes from an introductory database course.
-
Work through practice problems or exercises that cover basic database concepts, like data modeling and SQL querying.
-
Attend a refresher workshop or tutorial on database theory.
Nine other activities
Expand to see all activities and additional details
Show all 12 activities
Read 'Data Analytics with AWS' by Chris Erickson
Show steps
This book provides a comprehensive overview of data analytics with AWS, covering topics such as data collection, storage, processing, and visualization.
Show steps
-
Read through the book, taking notes on key concepts.
-
Complete the exercises and practice problems at the end of each chapter.
-
Use the book as a reference when working on course assignments.
Complete tutorials on AWS Kinesis
Show steps
Hands-on tutorials will provide students with practical experience working with AWS Kinesis, which is a key component of the course.
Browse courses on
AWS Kinesis
Show steps
-
Find a tutorial that covers the basics of AWS Kinesis.
-
Follow the tutorial step-by-step, creating your own Kinesis stream and writing data to it.
-
Experiment with different Kinesis features, such as partitioning and data retention.
Follow online tutorials on data integration
Show steps
This course includes a module on data integration. Following guided tutorials on this topic will provide additional hands-on experience and reinforce the concepts covered in the module.
Browse courses on
Data Integration
Show steps
-
Search for online tutorials on data integration.
-
Select reputable tutorials aligned with the course content.
-
Complete the tutorials and take notes.
Join a study group
Show steps
Working with peers in a study group can provide support and motivation, and can help students learn from each other.
Show steps
-
Find a study group that meets regularly.
-
Attend study group meetings and actively participate in discussions.
-
Work together on practice problems or projects.
Build a data pipeline using AWS Glue
Show steps
Building a data pipeline using AWS Glue will give students hands-on experience with a key tool for data analysts.
Browse courses on
AWS Glue
Show steps
-
Design the data pipeline, including the data sources, transformations, and destination.
-
Create the data pipeline using AWS Glue.
-
Test the data pipeline and make any necessary adjustments.
Solve practice problems on data compression algorithms
Show steps
This course will cover various data compression algorithms. Completing practice problems will strengthen your understanding of the algorithms and their applications.
Browse courses on
Data Compression
Show steps
-
Identify relevant textbooks or online resources.
-
Work through practice problems.
-
Verify solutions and analyze results.
Practice writing SQL queries
Show steps
Regular practice with SQL queries will help students develop proficiency in data analysis, which is a key skill for data analysts.
Browse courses on
SQL
Show steps
-
Find a set of practice SQL queries online or in a textbook.
-
Work through the queries, checking your answers against the provided solutions.
-
Try to write your own SQL queries to solve specific data analysis problems.
Build a prototype data pipeline
Show steps
This course emphasizes the practical applications of data collection systems. Building a prototype data pipeline will allow you to apply the concepts learned and gain real-world experience.
Browse courses on
Data Pipelines
Show steps
-
Define the scope and requirements of the data pipeline.
-
Choose appropriate tools and technologies.
-
Design and implement the data pipeline.
-
Test and iterate on the prototype.
Develop a data analytics solution for a real-world problem
Show steps
Working on a real-world project will allow students to apply the skills they learn in the course to a practical problem.
Show steps
-
Identify a real-world problem that can be solved using data analytics.
-
Gather data from a variety of sources.
-
Clean and prepare the data for analysis.
-
Develop a data analytics solution to solve the problem.
-
Present the solution to a group of peers or experts.
Create a study guide
Show steps
Creating a study guide will help students organize and review the course material.
Show steps
Show steps
Show steps
- Gather your notes, handouts, and other course materials.
- Review the material and identify the key concepts.
- Organize the key concepts into a logical structure.
- Create a study guide that summarizes the key concepts.
Review notes from prerequisite courses
Show steps
This course builds directly upon knowledge gained from prerequisite courses. Reviewing notes from these courses will activate prior knowledge and reinforce the concepts that will be covered in this course.
Browse courses on
Data Collection
Show steps
Show steps
Show steps
- Locate notes from prerequisite courses.
- Skim materials for main concepts.
- Take additional notes or make annotations as needed.
Review database theory
Show steps
Reviewing fundamental database theory will help students as they begin to learn more advanced database concepts.
Browse courses on
Database Theory
Show steps
Show steps
Show steps
- Read through your notes from an introductory database course.
- Work through practice problems or exercises that cover basic database concepts, like data modeling and SQL querying.
- Attend a refresher workshop or tutorial on database theory.
Nine other activities
Expand to see all activities and additional details
Show all 12 activities
Read 'Data Analytics with AWS' by Chris Erickson
Show steps
This book provides a comprehensive overview of data analytics with AWS, covering topics such as data collection, storage, processing, and visualization.
Show steps
Show steps
Show steps
- Read through the book, taking notes on key concepts.
- Complete the exercises and practice problems at the end of each chapter.
- Use the book as a reference when working on course assignments.
Complete tutorials on AWS Kinesis
Show steps
Hands-on tutorials will provide students with practical experience working with AWS Kinesis, which is a key component of the course.
Browse courses on
AWS Kinesis
Show steps
Show steps
Show steps
- Find a tutorial that covers the basics of AWS Kinesis.
- Follow the tutorial step-by-step, creating your own Kinesis stream and writing data to it.
- Experiment with different Kinesis features, such as partitioning and data retention.
Follow online tutorials on data integration
Show steps
This course includes a module on data integration. Following guided tutorials on this topic will provide additional hands-on experience and reinforce the concepts covered in the module.
Browse courses on
Data Integration
Show steps
Show steps
Show steps
- Search for online tutorials on data integration.
- Select reputable tutorials aligned with the course content.
- Complete the tutorials and take notes.
Join a study group
Show steps
Working with peers in a study group can provide support and motivation, and can help students learn from each other.
Show steps
Show steps
Show steps
- Find a study group that meets regularly.
- Attend study group meetings and actively participate in discussions.
- Work together on practice problems or projects.
Build a data pipeline using AWS Glue
Show steps
Building a data pipeline using AWS Glue will give students hands-on experience with a key tool for data analysts.
Browse courses on
AWS Glue
Show steps
Show steps
Show steps
- Design the data pipeline, including the data sources, transformations, and destination.
- Create the data pipeline using AWS Glue.
- Test the data pipeline and make any necessary adjustments.
Solve practice problems on data compression algorithms
Show steps
This course will cover various data compression algorithms. Completing practice problems will strengthen your understanding of the algorithms and their applications.
Browse courses on
Data Compression
Show steps
Show steps
Show steps
- Identify relevant textbooks or online resources.
- Work through practice problems.
- Verify solutions and analyze results.
Practice writing SQL queries
Show steps
Regular practice with SQL queries will help students develop proficiency in data analysis, which is a key skill for data analysts.
Browse courses on
SQL
Show steps
Show steps
Show steps
- Find a set of practice SQL queries online or in a textbook.
- Work through the queries, checking your answers against the provided solutions.
- Try to write your own SQL queries to solve specific data analysis problems.
Build a prototype data pipeline
Show steps
This course emphasizes the practical applications of data collection systems. Building a prototype data pipeline will allow you to apply the concepts learned and gain real-world experience.
Browse courses on
Data Pipelines
Show steps
Show steps
Show steps
- Define the scope and requirements of the data pipeline.
- Choose appropriate tools and technologies.
- Design and implement the data pipeline.
- Test and iterate on the prototype.
Develop a data analytics solution for a real-world problem
Show steps
Working on a real-world project will allow students to apply the skills they learn in the course to a practical problem.
Show steps
Show steps
Show steps
- Identify a real-world problem that can be solved using data analytics.
- Gather data from a variety of sources.
- Clean and prepare the data for analysis.
- Develop a data analytics solution to solve the problem.
- Present the solution to a group of peers or experts.
Career center
Learners who complete AWS: Data Collection Systems will develop knowledge and skills
that may be useful to these careers:
Data Engineer
Data Engineer
Data Engineers design, build, and maintain data management systems. They collect, analyze, and interpret data to identify trends and patterns, and to develop and implement solutions to improve business operations. This course will provide you with the knowledge and skills to design and implement data collection systems, integrate data from different sources, and transform data into a usable format for downstream applications. These skills are essential for success as a Data Engineer.
Data Scientist
Data Scientist
Data Scientists use scientific methods and algorithms to extract insights from data, and to develop and implement data-driven solutions to improve business operations. They use a variety of tools and techniques to collect, analyze, and interpret data, and to develop and implement data-driven solutions. This course will provide you with the knowledge and skills to collect, analyze, and interpret data, and to develop and implement data-driven solutions. These skills are essential for success as a Data Scientist.
Data Analyst
Data Analyst
Data Analysts collect, analyze, interpret, and present data to help businesses make informed decisions. They use a variety of tools and techniques to extract insights from data, and to develop and implement data-driven solutions to improve business operations. This course will provide you with the knowledge and skills to collect and analyze data from a variety of sources, and to develop and implement data-driven solutions. These skills are essential for success as a Data Analyst.
Database Administrator
Database Administrator
Database Administrators are responsible for the design, implementation, and maintenance of database systems. They ensure that databases are available, reliable, and performant, and that data is securely stored and managed. This course will provide you with the knowledge and skills to design and implement data collection systems, integrate data from different sources, and transform data into a usable format for downstream applications. These skills are essential for success as a Database Administrator.
Business Analyst
Business Analyst
Business Analysts identify and solve business problems by analyzing data and developing data-driven solutions. They use a variety of tools and techniques to collect, analyze, and interpret data, and to develop and implement data-driven solutions to improve business operations. This course will provide you with the knowledge and skills to collect and analyze data, and to develop and implement data-driven solutions. These skills are essential for success as a Business Analyst.
Data Integration Specialist
Data Integration Specialist
Data Integration Specialists design, build, and maintain data integration systems. They connect data from different sources, transform it into a usable format, and deliver it to downstream applications. This course will provide you with the knowledge and skills to design and implement data collection systems, integrate data from different sources, and transform data into a usable format for downstream applications. These skills are essential for success as a Data Integration Specialist.
Data Architect
Data Architect
Data Architects design and implement data management systems. They work with business stakeholders to identify data needs, and develop and implement data-driven solutions to meet those needs. This course will provide you with the knowledge and skills to design and implement data collection systems, integrate data from different sources, and transform data into a usable format for downstream applications. These skills are essential for success as a Data Architect.
Data Warehouse Engineer
Data Warehouse Engineer
Data Warehouse Engineers design, build, and maintain data warehouses. They collect, analyze, and interpret data from a variety of sources, and develop and implement data-driven solutions to improve business operations. This course will provide you with the knowledge and skills to collect and analyze data from a variety of sources, and to develop and implement data-driven solutions. These skills are essential for success as a Data Warehouse Engineer.
ETL Developer
ETL Developer
ETL Developers design, build, and maintain ETL (Extract, Transform, Load) pipelines. They collect data from a variety of sources, transform it into a usable format, and load it into a data warehouse or other data store. This course will provide you with the knowledge and skills to design and implement data collection systems, integrate data from different sources, and transform data into a usable format for downstream applications. These skills are essential for success as an ETL Developer.
Big Data Engineer
Big Data Engineer
Big Data Engineers design, build, and maintain big data systems. They collect and analyze large volumes of data, and develop and implement data-driven solutions to improve business operations. This course will provide you with the knowledge and skills to design and implement data collection systems, integrate data from different sources, and transform data into a usable format for downstream applications. These skills are essential for success as a Big Data Engineer.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software systems. They use a variety of programming languages and technologies to create software that meets the needs of businesses and organizations. This course will provide you with the knowledge and skills to design and implement data collection systems, integrate data from different sources, and transform data into a usable format for downstream applications. These skills may be useful for success as a Software Engineer, particularly those working on data-intensive applications.
Technical Architect
Technical Architect
Technical Architects design and implement the technical architecture of systems and applications. They work with business stakeholders and development teams to identify technical requirements, and develop and implement technical solutions to meet those requirements. This course will provide you with the knowledge and skills to design and implement data collection systems, integrate data from different sources, and transform data into a usable format for downstream applications. These skills may be useful for success as a Technical Architect, particularly those working on data-intensive applications.
DevOps Engineer
DevOps Engineer
DevOps Engineers work to bridge the gap between development and operations teams. They use a variety of tools and techniques to automate and streamline the software development and deployment process. This course will provide you with the knowledge and skills to design and implement data collection systems, integrate data from different sources, and transform data into a usable format for downstream applications. These skills may be useful for success as a DevOps Engineer, particularly those working on data-intensive applications.
Cloud Engineer
Cloud Engineer
Cloud Engineers design, build, and maintain cloud computing systems. They use a variety of cloud technologies to create and manage cloud-based applications and services. This course will provide you with the knowledge and skills to design and implement data collection systems, integrate data from different sources, and transform data into a usable format for downstream applications. These skills may be useful for success as a Cloud Engineer, particularly those working on data-intensive applications.
Data Science Manager
Data Science Manager
Data Science Managers lead and manage data science teams. They work with business stakeholders to identify data science needs, and develop and implement data science solutions to meet those needs. This course will provide you with the knowledge and skills to design and implement data collection systems, integrate data from different sources, and transform data into a usable format for downstream applications. These skills may be useful for success as a Data Science Manager.
For more career information including salaries, visit:
OpenCourser.com/course/4pubj0/aws
Reading list
We've selected 11 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
AWS: Data Collection Systems.
Explores fundamental concepts and architectures for building scalable and reliable data-intensive applications, providing valuable insights for AWS data collection systems.
Covers data transformation concepts, tools, and techniques for preparing data for analysis and reporting.
Provides a broad overview of big data analytics, including data collection, processing, and analysis techniques.
Provides a comprehensive overview of the AWS Certified Solutions Architect Associate exam, including the topics covered and the skills required to pass the exam.
Introduces data science concepts and techniques for business professionals, providing insights into data collection and analysis.
Offers a comprehensive overview of data compression techniques. It is particularly useful for gaining a deeper understanding of how to optimize data ingestion processes and ensure data is in a usable format for downstream applications.
Provides a theoretical foundation for data compression techniques, helping to understand how they can be applied to optimize data ingestion and storage in AWS.
Provides a hands-on approach to big data analytics using Java, complementing the course's theoretical concepts.
Introduces data science concepts and techniques for beginners, providing a foundation for the course's more advanced topics.
Provides specialized knowledge on data integration techniques using Microsoft SQL Server, complementing the course's broader coverage.
Provides a comprehensive overview of data transformation algorithms and techniques, complementing the course's practical focus.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/4pubj0/aws
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Effort
3 weeks of study, 3-3:30 hours/week
Level
Introductory
Via
Coursera
Institution
Whizlabs
Instructor
Whizlabs Instructor
Language
English
This course belongs to a
collection
called
Exam Prep DAS-C01: AWS Certified Data Analytics Specialty. It's comprised of five courses:
- AWS Data Processing
- AWS: Security in Data Analytics
- AWS: Data Analysis and Visualization
- AWS: Storage Systems and Data Management
- AWS: Data Collection Systems (viewing)
Good to know
Suitable for persons studying engineering or science in first or second year at undergraduate level
Appropriate for those with an interest in programming regardless of their current study or occupation
Introduces the Kinesis Data Streams and Kinesis Data Firehose for hands-on experience with real-time data streaming
Provides practical experience with AWS Glue, a fully managed ETL service, for seamless data integration
Covers data order, format, and compression techniques for optimizing data ingestion processes
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