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AWS

Data Analysis and Visualization

Whizlabs Instructor

AWS: Data Analysis and Visualization Course is the fourth course of AWS Certified Data Analytics Speciality Specialization. This course teaches Data Analysis and Visualization by exploring AWS Services such as Athena, Kinesis, QuickSight, Redshift and Kibana. The course is divided into three modules and each module is further segmented by Lessons and Video Lectures. This course facilitates learners with approximately 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 Analysis and Visualization Course is the fourth course of AWS Certified Data Analytics Speciality Specialization. This course teaches Data Analysis and Visualization by exploring AWS Services such as Athena, Kinesis, QuickSight, Redshift and Kibana. The course is divided into three modules and each module is further segmented by Lessons and Video Lectures. This course facilitates learners with approximately 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: AWS: Data Analysis and Visualization Part 1

Module 2: AWS: Data Analysis and Visualization Part 2

Module 3: AWS: Data Analysis and Visualization Part 3

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What's inside

Syllabus

AWS: Data Analysis and Visualization Part 1
Welcome to Week 1 of the AWS: Data Analysis and Visualization. This week, we will focus on determining the operational characteristics of an analysis and visualization solution, and analyzing AWS services such as usage patterns, performance, and cost. We will also learn how to implement Kinesis Data Analytics to analyze streaming data in real-time. Through practical demonstrations, we will gain hands-on experience with analyzing data using Kinesis Data Analytics, and learn how to effectively use AWS services for analysis and visualization needs.
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Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Explores the industry-standard Amazon QuickSight
Covers the basics of AWS data visualization and analysis services
Provides hands-on experience with real-time data analytics using Kinesis
Involves using Amazon Redshift, ElasticSearch, and Kibana for data visualization
May have prerequisites since it's part of a specialization

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Reviews summary

Aws data analysis: foundational & practical

According to students, this course offers a solid foundation in AWS data analysis and visualization services, making it a valuable starting point for professionals and career-focused learners. Many highlight the hands-on labs and practical application as particularly effective for understanding complex concepts and applying them to real-world scenarios. The course provides good coverage of services like Kinesis, Redshift, Athena, and QuickSight. However, a significant concern raised by recent learners is the presence of outdated content and AWS console interfaces, which can lead to confusion. Some find the depth of coverage, especially for services like Kibana and Elasticsearch, too superficial for experienced users.
Provides a good introductory understanding of AWS data services.
"The course provides a solid foundation in AWS data services, especially QuickSight and Athena."
"Excellent course for anyone looking to get started with data analysis on AWS."
"Good course for getting an overview of AWS data analytics tools... It's a foundational course, so don't expect deep dives into every service."
"I found it a solid starting point for those completely new to this domain."
Strong emphasis on practical, hands-on learning activities.
"The hands-on labs were very helpful in understanding the concepts, though some felt a bit rushed. I particularly appreciated the focus on practical application."
"I enjoyed the practical aspects of this course. The demonstrations of Athena and QuickSight were very useful for my current work projects."
"Absolutely fantastic! This course provided me with exactly what I needed to understand AWS for data analysis. The hands-on sections were invaluable."
"I gained a good understanding of real-time data processing and warehousing through the practical examples."
Some learners encountered small technical problems with labs.
"Some of the labs had minor issues that required a bit of troubleshooting on my own."
"My experience was sometimes hindered by small technical hiccups during the hands-on sections."
Good for beginners, but lacks depth for advanced users on certain services.
"I found the content on Kibana and Elasticsearch to be a bit superficial; it felt more like a quick demo rather than a deep dive."
"For experienced cloud professionals, this course might be too basic. It's a good starting point if you're completely new to AWS data, but don't expect to become an expert."
"I would have loved more advanced topics, perhaps some optimization techniques for large datasets, but for an introductory/intermediate course, it's quite good."
"The course covers a good range of services, but sometimes felt like a high-level tour rather than hands-on training."
Videos and labs show outdated AWS console interfaces and information.
"I noticed some of the console interfaces shown in the videos were slightly outdated compared to the current AWS UI, which can be a bit confusing for new learners."
"Several parts of the video content were outdated, leading to confusion when following along with the labs."
"The outdated UI issues are a real pain. It's an okay course, but I think it could be improved with more current content and deeper lab exercises."

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 Analysis and Visualization with these activities:
Review Data Analysis Fundamentals
Review data analysis techniques to strengthen knowledge and prepare for topics in this course
Browse courses on Data Analysis Techniques
Show steps
  • Identify and gather relevant resources such as online tutorials, books, or videos
  • Review core principles of data analysis and modeling
  • Explore techniques for data cleaning, transformation, and analysis
Read 'Data Analysis and Visualization' by Thomas W. Miller
Supplement course content with a book that provides comprehensive coverage of data analysis and visualization
View Sports Analytics and Data Science: Winning the... on Amazon
Show steps
  • Read selected chapters to reinforce concepts learned in class
  • Work through exercises and examples to improve practical skills
Practice Data Analysis Exercises on Sample Datasets
Engage in hands-on practice to reinforce your understanding of the principles and techniques covered in the course.
Browse courses on Data Analysis
Show steps
  • Access provided sample datasets and exercise instructions.
  • Apply data analysis techniques to extract insights and draw conclusions.
  • Practice visualizing data using appropriate tools and techniques.
  • Validate your results and seek feedback to refine your understanding.
Six other activities
Expand to see all activities and additional details
Show all nine activities
Practice Data Analysis with Kaggle Datasets
Gain hands-on experience in data analysis by working with real-world datasets
Browse courses on Data Manipulation
Show steps
  • Explore Kaggle's library of publicly available datasets
  • Select a dataset relevant to your interests or the topics covered in the course
  • Apply data analysis techniques to extract insights and identify trends
Follow Tutorials on Amazon QuickSight
Develop practical skills in data visualization using Amazon QuickSight
Browse courses on Data Visualization
Show steps
  • Explore Amazon's official documentation and tutorials
  • Build interactive dashboards and visualizations using QuickSight's features
  • Share visualizations with stakeholders for data-driven decision-making
Create a Data Visualization Portfolio
Document learning progress and showcase data visualization capabilities
Show steps
  • Collect and organize data visualizations created throughout the course
  • Designate a platform or portfolio site to display your work
  • Provide brief descriptions and explanations for each visualization
  • Update the portfolio regularly with new projects
Attend an AWS Data Visualization Workshop
Learn from industry experts and gain practical experience in data visualization
Show steps
  • Identify and register for a relevant workshop offered by AWS or industry partners
  • Attend the workshop and actively participate in hands-on exercises
  • Connect with experts and industry professionals
Contribute to Open Source Data Visualization Projects
Gain practical experience and contribute to the data visualization community
Browse courses on Community Involvement
Show steps
  • Identify open source data visualization projects on platforms like GitHub
  • Review project documentation and identify areas to contribute
  • Develop or improve data visualization components or features
  • Collaborate with other contributors and receive feedback
Mentor Students in Data Analytics and Visualization
Enhance understanding by sharing knowledge and guiding others in data analytics and visualization
Browse courses on Teaching
Show steps
  • Volunteer or participate in mentoring programs
  • Share your expertise and best practices with students or junior professionals
  • Provide feedback and support to help them develop their skills and knowledge

Career center

Learners who complete AWS: Data Analysis and Visualization will develop knowledge and skills that may be useful to these careers:
Data Analyst
A Data Analyst helps businesses with data-driven decision-making by analyzing and interpreting data. They design and implement data collection systems, clean and prepare data for analysis, and build models to identify trends and patterns. This course can help you gain the skills and knowledge needed to become a successful Data Analyst. You will learn about different AWS services that can be used for data analysis and visualization, and you will gain hands-on experience with using these services to analyze data.
See salaries and explore the career path for Data Analyst
Business Intelligence Analyst
A Business Intelligence Analyst develops and maintains business intelligence systems, which help businesses track and analyze their performance and make data-driven decisions. They work closely with stakeholders to identify business needs and develop solutions to meet those needs. This course can help you gain the skills and knowledge needed to become a successful Business Intelligence Analyst. You will learn about different AWS services that can be used for data analysis and visualization, and you will gain hands-on experience with using these services to analyze data.
See salaries and explore the career path for Business Intelligence Analyst
Data Scientist
A Data Scientist is responsible for developing and implementing data science solutions to solve business problems. They work with data engineers to collect and clean data, and then use statistical and machine learning techniques to analyze data and build models. This course can help you gain the skills and knowledge needed to become a successful Data Scientist. You will learn about different AWS services that can be used for data analysis and visualization, and you will gain hands-on experience with using these services to analyze data.
See salaries and explore the career path for Data Scientist
Data Engineer
A Data Engineer is responsible for designing and implementing data pipelines to collect, store, and process data. They work with data scientists to develop data science solutions, and they also work with IT staff to maintain data infrastructure. This course can help you gain the skills and knowledge needed to become a successful Data Engineer. You will learn about different AWS services that can be used for data analysis and visualization, and you will gain hands-on experience with using these services to analyze data.
See salaries and explore the career path for Data Engineer
Statistician
A Statistician collects, analyzes, interprets, and presents data. They work in a variety of fields, including finance, healthcare, and marketing. This course can help you gain the skills and knowledge needed to become a successful Statistician. You will learn about different AWS services that can be used for data analysis and visualization, and you will gain hands-on experience with using these services to analyze data.
See salaries and explore the career path for Statistician
Data Visualization Engineer
A Data Visualization Engineer designs and develops data visualizations that help businesses communicate data insights to stakeholders. They work with data analysts and data scientists to identify the most effective ways to visualize data, and they use a variety of tools and techniques to create compelling data visualizations. This course can help you gain the skills and knowledge needed to become a successful Data Visualization Engineer. You will learn about different AWS services that can be used for data analysis and visualization, and you will gain hands-on experience with using these services to create data visualizations.
See salaries and explore the career path for Data Visualization Engineer
Software Engineer
A Software Engineer designs, develops, and maintains software applications. They work with a variety of programming languages and technologies, and they may specialize in a particular area of software development, such as data science or data visualization. This course can help you gain the skills and knowledge needed to become a successful Software Engineer. You will learn about different AWS services that can be used for data analysis and visualization, and you will gain hands-on experience with using these services to develop software applications.
See salaries and explore the career path for Software Engineer
Database Administrator
A Database Administrator manages and maintains databases. They ensure that databases are running smoothly and efficiently, and they work with developers to design and implement database solutions. This course can help you gain the skills and knowledge needed to become a successful Database Administrator. You will learn about different AWS services that can be used for data analysis and visualization, and you will gain hands-on experience with using these services to manage and maintain databases.
See salaries and explore the career path for Database Administrator
Big Data Engineer
A Big Data Engineer designs and develops solutions for managing and processing large datasets. They work with a variety of big data technologies, such as Hadoop and Spark, and they may specialize in a particular area of big data engineering, such as data analysis or data visualization. This course can help you gain the skills and knowledge needed to become a successful Big Data Engineer. You will learn about different AWS services that can be used for data analysis and visualization, and you will gain hands-on experience with using these services to manage and process big data.
See salaries and explore the career path for Big Data Engineer
Data Architect
A Data Architect designs and implements data architectures for organizations. They work with stakeholders to identify data needs and develop solutions to meet those needs. This course can help you gain the skills and knowledge needed to become a successful Data Architect. You will learn about different AWS services that can be used for data analysis and visualization, and you will gain hands-on experience with using these services to design and implement data architectures.
See salaries and explore the career path for Data Architect
Data Warehouse Engineer
A Data Warehouse Engineer designs and builds data warehouses. They work with data architects to identify data needs and develop solutions to meet those needs. This course can help you gain the skills and knowledge needed to become a successful Data Warehouse Engineer. You will learn about different AWS services that can be used for data analysis and visualization, and you will gain hands-on experience with using these services to design and build data warehouses.
See salaries and explore the career path for Data Warehouse Engineer
Machine Learning Engineer
A Machine Learning Engineer develops and implements machine learning models. They work with data scientists and data engineers to identify the most effective ways to use machine learning to solve business problems. This course can help you gain the skills and knowledge needed to become a successful Machine Learning Engineer. You will learn about different AWS services that can be used for data analysis and visualization, and you will gain hands-on experience with using these services to develop and implement machine learning models.
See salaries and explore the career path for Machine Learning Engineer
Information Technology Manager
An Information Technology Manager plans, implements, and manages the IT infrastructure for an organization. They work with a variety of IT technologies, including data analysis and visualization technologies. This course can help you gain the skills and knowledge needed to become a successful Information Technology Manager. You will learn about different AWS services that can be used for data analysis and visualization, and you will gain hands-on experience with using these services to manage and maintain IT infrastructure.
See salaries and explore the career path for Information Technology Manager
Web Developer
A Web Developer designs and develops websites. They work with a variety of programming languages and technologies, and they may specialize in a particular area of web development, such as data visualization. This course can help you gain the skills and knowledge needed to become a successful Web Developer. You will learn about different AWS services that can be used for data analysis and visualization, and you will gain hands-on experience with using these services to develop websites.
See salaries and explore the career path for Web Developer
Data Entry Clerk
A Data Entry Clerk enters data into computer systems. They may work in a variety of settings, such as offices, warehouses, and retail stores. This course may be helpful for you if you are interested in becoming a Data Entry Clerk. You will learn about different AWS services that can be used for data analysis and visualization, and you will gain hands-on experience with using these services to enter data.
See salaries and explore the career path for Data Entry Clerk

Reading list

We've selected seven 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 Analysis and Visualization.
Cover image
Oracle Big Data Handbook
Save
Provides a comprehensive overview of big data analytics using Hadoop. It covers all aspects of Hadoop, from data ingestion to data analysis. This book valuable resource for anyone who wants to learn about Hadoop or use it to implement big data analytics solutions.
Oracle Big Data Handbook (Oracle Press)
Paperback
$$
Oracle Big Data Handbook (Oracle Press)
Kindle Edition
$$$
Cover image
Simple Object-Oriented Design
Save
Provides a comprehensive overview of data science using Python. It covers all aspects of data science, from data cleaning to machine learning. This book valuable resource for anyone who wants to learn about data science or use it to solve real-world problems.
Simple Object-Oriented Design: Create clean,...
Kindle Edition
$$
Machine Learning Con Pytorch Y Scikit Lean
Save
Provides a comprehensive overview of machine learning using Python. It covers all aspects of machine learning, from data preprocessing to model evaluation. This book valuable resource for anyone who wants to learn about machine learning or use it to solve real-world problems.
(Español) Machine Learning con PyTorch y Scikit-Learn:...
Paperback
$$$
Cover image
Deep Learning with Python, Second Edition
Save
Provides a comprehensive overview of deep learning using Python. It covers all aspects of deep learning, from neural networks to convolutional neural networks. This book valuable resource for anyone who wants to learn about deep learning or use it to solve real-world problems.
Deep Learning with Python, Second Edition
Paperback
$$
Deep Learning with Python, Second Edition
Kindle Edition
$$
Cover image
Natural Language Processing with Python
Save
Provides a comprehensive overview of natural language processing using Python. It covers all aspects of natural language processing, from text classification to machine translation. This book valuable resource for anyone who wants to learn about natural language processing or use it to solve real-world problems.
Natural Language Processing with Python: Analyzing...
Paperback
$$$
Natural Language Processing with Python: Analyzing...
Kindle Edition
$$
Cover image
Hybrid Imaging and Visualization
Save
Provides a comprehensive overview of computer vision using Python. It covers all aspects of computer vision, from image processing to object detection. This book valuable resource for anyone who wants to learn about computer vision or use it to solve real-world problems.
Hybrid Imaging and Visualization: Employing Machine...
Kindle Edition
$$$$
Cover image
R for Data Science
Save
Provides a comprehensive overview of data visualization using R. It covers all aspects of data visualization, from data preparation to interactive visualizations. This book valuable resource for anyone who wants to learn about data visualization or use it to communicate data effectively.
R for Data Science: Import, Tidy, Transform,...
Paperback
$$
(Deutsch) R für Data Science: Daten importieren, bereinigen,...
Kindle Edition
$$$

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Course image
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:
  1. AWS Data Processing
  2. AWS: Security in Data Analytics
  3. AWS: Data Analysis and Visualization (viewing)
  4. AWS: Storage Systems and Data Management
  5. AWS: Data Collection Systems
Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
Explores the industry-standard Amazon QuickSight
Covers the basics of AWS data visualization and analysis services
Provides hands-on experience with real-time data analytics using Kinesis
Involves using Amazon Redshift, ElasticSearch, and Kibana for data visualization
May have prerequisites since it's part of a specialization
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