Analyzing Data on AWS from Pluralsight

Studying for the Amazon Certified Data Analytics - Specialty exam, or need to do Big Data Analytics on AWS? In this course, you’ll learn four Amazon Analytics services—specifically Redshift, Elasticsearch, Kinesis Data Analytics, and Athena.

Amazon offers four powerful services for data analytics. Only, there’s a lot you need to know to use them effectively.

In this course, Analyzing Data on AWS,

First, you’ll learn how to analyze streaming log files or other text data with Elasticsearch and how to visualize the data with Kibana. Next, you’ll discover how to directly query data in S3 using Amazon Athena along with the Glue Data Catalog and Glue crawlers. Then, you’ll explore SQL queries on real time streaming data with Kinesis Data Analytics. Finally, you’ll learn how to design and use Amazon’s data warehouse—Redshift.

When you’re finished with this course, you’ll have learned key topics covered by the Amazon Data Analytics - Specialty exam, and be ready to create your own data analytics projects on AWS.

This certification from Amazon Web Services validates that you're an expert in AWS data lakes and analytics products.

This course is ideal for anyone preparing for the AWS Certified Data Analytics - Specialty Certification, or who would like to create their own data analytics projects on AWS.

In this course, Analyzing Data on AWS, you’ll learn to configure and use Amazon Elasticsearch, Amazon Athena, Kinesis Data Analytics, and Amazon Redshift - key topics covered in the Amazon Data Analytics - Specialty exam.

As long as you already know some SQL and have some skills with Amazon's cloud, you're ready for this course.

What's inside

Syllabus

Course Overview

Data Analytics on AWS

Amazon Elasticsearch

Amazon Athena

Kinesis Data Analytics

Amazon Redshift

Course Summary

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Ideal for individuals preparing for the AWS Certified Data Analytics - Specialty Certification or seeking to create data analytics projects on AWS

Introduces four key Amazon Analytics services: Redshift, Elasticsearch, Kinesis Data Analytics, and Athena

Taught by Clarke Bishop, an experienced instructor in AWS data analytics

Covers essential topics from the Amazon Data Analytics - Specialty exam

Emphasizes hands-on learning through configuring and using Amazon data analytics services

Assumes prior knowledge of SQL and some familiarity with Amazon's cloud services

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 Analyzing Data on AWS with these activities:

Review SQL basics

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SQL is a key component of this course and refreshing your skills before the course starts will provide a solid foundation to build upon.

Browse courses on SQL

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Read tutorials on SQL basics
Complete online SQL exercises

Compile study notes and practice questions for the exam

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Helps students organize their learning and prepare effectively for the exam.

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Review the course materials and identify key concepts
Create study notes and practice questions based on these concepts

Review basic SQL concepts

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Refreshes students' foundational knowledge of SQL, which is essential for the course.

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Review online tutorials or documentation on basic SQL
Practice writing simple SQL queries

16 other activities

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Review Big Data Concepts

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Review fundamental concepts and technologies related to big data to strengthen your foundational knowledge before starting the course.

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Read articles and watch videos about big data
Review notes from previous courses or certifications
Participate in online forums and discussions about big data
Attend a webinar or workshop on big data
Test your understanding through practice questions or quizzes

Attend a meetup or conference related to data analytics on AWS

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Connects students with industry professionals and provides opportunities for networking.

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Research and identify a relevant meetup or conference
Register for the event
Attend the event and engage with other professionals

Follow tutorials on Amazon Data Analytics - Specialty exam topics

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Provides students with additional support and guidance on the key concepts covered in the exam.

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Identify the key topics covered by the exam
Search for and select tutorials that cover these topics
Follow the tutorials and complete the exercises provided

Follow tutorials on Elasticsearch

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Elasticsearch is a powerful tool for data analytics. Following tutorials will provide you with hands-on practice and a deeper understanding of its capabilities.

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Find tutorials on the Elasticsearch website
Follow the tutorials and complete the exercises

AWS Data Analytics Workshop

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Attend an AWS Data Analytics workshop to learn from experts, explore real-world use cases, and get hands-on practice with AWS data analytics services.

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Research and find an AWS Data Analytics workshop
Register for the workshop
Attend the workshop and actively participate
Take notes and ask questions
Follow up with the workshop organizers

Solve Kinesis Data Analytics exercises

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Kinesis Data Analytics exercises will challenge you to apply your understanding of real-time data streaming and improve your problem-solving skills.

Browse courses on Kinesis Data Analytics

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Find exercises on the Kinesis Data Analytics website
Solve the exercises using the Kinesis Data Analytics console

Create a Study Guide

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Organize and synthesize your learning materials to improve your retention and recall of key concepts.

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Gather all relevant course materials
Organize materials by topic or module
Highlight and summarize important concepts
Create flashcards or mind maps
Review and update your study guide regularly

Practice SQL queries on real-time streaming data with Kinesis Data Analytics

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Provides students with hands-on experience with a core technology covered in the course.

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Set up a Kinesis Data Analytics stream
Write SQL queries to process the streaming data
Test the queries and analyze the results

Write a blog post about your experience with Amazon Analytics services

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Writing a blog post will allow you to revisit the concepts you've learned, solidify your understanding, and share your knowledge with others.

Browse courses on Data Analytics

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Choose a topic related to Amazon Analytics services
Research and gather information
Write the blog post
Publish the blog post

Create a data analytics project using multiple AWS services

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Helps students apply their knowledge of AWS data analytics services and develop their problem-solving skills.

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Choose a data source and a data analytics problem to solve
Design a data analytics pipeline using Redshift, Elasticsearch, Kinesis Data Analytics, and Athena
Implement the data analytics pipeline using AWS services
Test and evaluate the data analytics pipeline

Build a data visualization dashboard

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Creating a data visualization dashboard will allow you to apply the skills you learn in the course and gain practical experience in data analysis.

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Choose a dataset
Design the dashboard
Build the dashboard using Kibana

Practice SQL Queries

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Practice writing and executing SQL queries to reinforce your understanding of data retrieval and manipulation.

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Review the SQL syntax and semantics
Set up a local SQL environment
Practice writing simple queries to retrieve data
Practice writing more complex queries using joins and subqueries
Practice writing queries to manipulate data

Design and Build a Data Lake

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Create a data lake to store and manage large amounts of data from various sources, gaining hands-on experience in data lake design and implementation.

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Choose the appropriate cloud storage service
Create a data model and schema
Ingest data into the data lake
Create Glue Data Catalog and crawlers
Test and validate the data lake

Create a blog post or presentation summarizing the course content

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Encourages students to synthesize their understanding of the course content and share their knowledge with others.

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Review the course materials and identify the key concepts
Summarize these concepts in a blog post or presentation
Share your blog post or presentation with others

Develop a data analytics solution for a real-world problem

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Applying your knowledge to solve a real-world problem will reinforce your understanding of data analytics and demonstrate your skills to potential employers.

Browse courses on Data Analytics

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Identify a problem that can be solved using data analytics
Design a data analytics solution using Amazon Redshift
Implement the solution and evaluate its effectiveness

Volunteer at a Data Analytics Non-Profit

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Apply your data analytics skills to make a meaningful contribution to a non-profit organization.

Browse courses on Data Analytics

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Research and find a data analytics non-profit
Contact the non-profit and inquire about volunteer opportunities
Complete the volunteer application and onboarding process
Dedicate time to volunteer and participate in data analytics projects
Reflect on your experience and share your learnings

Career center

Learners who complete Analyzing Data on AWS will develop knowledge and skills that may be useful to these careers:

Big Data Analyst

Big Data Analysts play a key role in the field of data analytics. The course Analyzing Data on AWS can help you build a foundation towards this career. It introduces you to four Amazon Analytics services, including Redshift, Elasticsearch, Kinesis Data Analytics, and Athena, equipping you with the skills to analyze big data effectively. With hands-on experience in these tools, you'll gain the ability to manage large volumes of data, extract insights, and generate reports. This will enable you to contribute to data-driven decision-making and derive meaningful value from big data.

See salaries and explore the career path for Big Data Analyst

Data Analyst

As a Data Analyst, you will focus on analyzing data to identify trends, patterns, and insights. To succeed in this role, you need a strong understanding of data analysis techniques and tools. The Analyzing Data on AWS course provides a great starting point by introducing you to four key Amazon Analytics services. Through hands-on exercises, you'll learn how to query data in S3, analyze streaming data, and design data warehouses. These skills will help you effectively extract meaningful insights from data and support decision-making in various industries.

See salaries and explore the career path for Data Analyst

Data Engineer

Data Engineers are responsible for designing, building, and maintaining data pipelines and infrastructure. The Analyzing Data on AWS course can help you develop the necessary skills for this role. You'll gain proficiency in Amazon Elasticsearch, Amazon Athena, Kinesis Data Analytics, and Amazon Redshift. These tools are essential for handling large volumes of data, ensuring data quality, and building efficient data processing systems. By completing this course, you'll be well-equipped to contribute to the design and implementation of data pipelines that support data-driven applications.

See salaries and explore the career path for Data Engineer

Database Administrator

Database Administrators are responsible for managing and maintaining databases, ensuring their availability and performance. The Analyzing Data on AWS course can enhance your skills in this field. You'll gain experience with Amazon Redshift, a powerful data warehouse service. Through hands-on exercises, you'll learn how to design, configure, and optimize Redshift clusters. This knowledge will enable you to effectively manage databases, ensuring data integrity and supporting data-intensive applications.

See salaries and explore the career path for Database Administrator

Data Scientist

Data Scientists use their expertise in data analysis, machine learning, and statistics to uncover insights from data. Analyzing Data on AWS can provide a strong foundation for this career path. The course introduces you to Amazon Elasticsearch, Amazon Athena, Kinesis Data Analytics, and Amazon Redshift. These tools are essential for handling large datasets, performing data analysis, and building machine learning models. By gaining proficiency in these services, you'll be well-prepared to contribute to data science projects and drive data-driven decision-making.

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

Machine Learning Engineers develop and deploy machine learning models to solve real-world problems. To excel in this role, you need a strong understanding of data analysis techniques and tools. Analyzing Data on AWS can help you build a foundation in this area. You'll gain experience with Amazon Elasticsearch, Amazon Athena, Kinesis Data Analytics, and Amazon Redshift. These tools are commonly used in machine learning pipelines for data preparation, feature engineering, and model evaluation. By mastering these services, you'll enhance your ability to develop and deploy effective machine learning solutions.

See salaries and explore the career path for Machine Learning Engineer

Cloud Architect

Cloud Architects design and manage cloud computing solutions. The Analyzing Data on AWS course can provide valuable insights into cloud-based data analytics. You'll gain experience with Amazon Elasticsearch, Amazon Athena, Kinesis Data Analytics, and Amazon Redshift. These services offer scalable and cost-effective solutions for data storage, processing, and analysis. By understanding the capabilities and limitations of these tools, you'll be better equipped to design and implement cloud-based data analytics solutions that meet the needs of your organization.

See salaries and explore the career path for Cloud Architect

Data Architect

Data Architects design and manage data architectures to meet the needs of an organization. Analyzing Data on AWS can provide a strong foundation for this role. You'll gain experience with Amazon Elasticsearch, Amazon Athena, Kinesis Data Analytics, and Amazon Redshift. These services offer a wide range of capabilities for data storage, processing, and analysis. By understanding how these tools can be combined to create scalable and efficient data architectures, you'll be well-prepared to design and implement data solutions that support the growth and success of your organization.

See salaries and explore the career path for Data Architect

Business Analyst

Business Analysts use data to identify and solve business problems. Analyzing Data on AWS can enhance your skills in this area. You'll gain experience with Amazon Elasticsearch, Amazon Athena, Kinesis Data Analytics, and Amazon Redshift. These tools enable you to access, analyze, and visualize data from various sources. By mastering these services, you'll be able to extract meaningful insights from data, identify trends and patterns, and support decision-making processes within your organization.

See salaries and explore the career path for Business Analyst

Data Visualization Analyst

Data Visualization Analysts specialize in presenting data in a clear and visually appealing way. Analyzing Data on AWS can provide valuable skills for this role. You'll gain experience with Amazon Elasticsearch, Amazon Athena, Kinesis Data Analytics, and Amazon Redshift. These services offer powerful data visualization capabilities that enable you to create interactive dashboards, charts, and graphs. By mastering these tools, you'll be well-equipped to transform complex data into compelling visuals that communicate insights effectively.

See salaries and explore the career path for Data Visualization Analyst

Quantitative Analyst

Quantitative Analysts use mathematical and statistical techniques to analyze data and make predictions. Analyzing Data on AWS can provide a strong foundation for this role. You'll gain experience with Amazon Elasticsearch, Amazon Athena, Kinesis Data Analytics, and Amazon Redshift. These services offer scalable and cost-effective solutions for data storage, processing, and analysis. By understanding the capabilities and limitations of these tools, you'll be well-equipped to develop and implement quantitative models that support decision-making in various industries.

See salaries and explore the career path for Quantitative Analyst

Market Research Analyst

Market Research Analysts conduct research on markets and consumer behavior. Analyzing Data on AWS can provide valuable skills for this role. You'll gain experience with Amazon Elasticsearch, Amazon Athena, Kinesis Data Analytics, and Amazon Redshift. These services enable you to access, analyze, and visualize data from various sources, including social media, surveys, and market research reports. By mastering these tools, you'll be able to extract meaningful insights from data, identify trends and patterns, and support decision-making processes within your organization.

See salaries and explore the career path for Market Research Analyst

Operations Research Analyst

Operations Research Analysts use mathematical and analytical techniques to improve the efficiency and effectiveness of systems. Analyzing Data on AWS can provide a strong foundation for this role. You'll gain experience with Amazon Elasticsearch, Amazon Athena, Kinesis Data Analytics, and Amazon Redshift. These services offer scalable and cost-effective solutions for data storage, processing, and analysis. By understanding the capabilities and limitations of these tools, you'll be well-equipped to develop and implement analytical models that optimize operations and decision-making.

See salaries and explore the career path for Operations Research Analyst

Financial Analyst

Financial Analysts use data to make informed decisions about investments and financial strategies. Analyzing Data on AWS can provide valuable skills for this role. You'll gain experience with Amazon Elasticsearch, Amazon Athena, Kinesis Data Analytics, and Amazon Redshift. These services offer scalable and cost-effective solutions for data storage, processing, and analysis. By understanding the capabilities and limitations of these tools, you'll be well-equipped to analyze financial data, identify trends and patterns, and develop investment recommendations.

See salaries and explore the career path for Financial Analyst

Actuary

Actuaries use mathematical and statistical techniques to assess risk and uncertainty. Analyzing Data on AWS can provide a strong foundation for this role. You'll gain experience with Amazon Elasticsearch, Amazon Athena, Kinesis Data Analytics, and Amazon Redshift. These services offer scalable and cost-effective solutions for data storage, processing, and analysis. By understanding the capabilities and limitations of these tools, you'll be well-equipped to develop and implement actuarial models that assess risk and support decision-making in various industries.

See salaries and explore the career path for Actuary

Analyzing Data on AWS

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