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Kim Schmidt

AWS Glue and Amazon Athena have transformed the way big data workflows are built in the day of AI and ML. Learn how to build for now and the future, how to future-proof your data, and know the significance of what you’ll learn can't be overstated.

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AWS Glue and Amazon Athena have transformed the way big data workflows are built in the day of AI and ML. Learn how to build for now and the future, how to future-proof your data, and know the significance of what you’ll learn can't be overstated.

How to architect and build big data analytics in the AWS cloud in the day of AI and ML has been transformed by both AWS Glue and Amazon Athena. In this course, Serverless Analytics on AWS, you'll gain the ability to have one centralized data source for all your globally scattered data silos regardless if the data is structured, unstructured, or semi-structured so you can perform multiple types of advanced analytics on the data by multiple people simultaneously without affecting the underlying data store wherever in the world each data set is located, keeping the data in sync with any changes to the source data. First, you'll learn how to use AWS Glue Crawlers, AWS Glue Data Catalog, and AWS Glue Jobs to dramatically reduce data preparation time, doing ETL “on the fly”. Next, you’ll discover how to immediately analyze your data without regard to data format, giving actionable insights within seconds. Finally, you’ll explore how to use AWS best practices to keep up by having AI and ML analytics incorporated into your analytics workflows, future-proofing your data via immutable logs. When you’re finished with this course, you'll have the skills and knowledge of using state of the art serverless technologies to provide a myriad of insight types whenever you need them.

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What's inside

Syllabus

Course Overview
Download and Install Course Prerequisites
The State of Analytics in the AWS Cloud
Infrastructure and Data Setup via Amazon CloudFormation
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The Power of AWS Glue
Creating AWS Glue Resources and Populating the AWS Glue Data Catalog
The Power of Amazon Athena
How to AI and ML Your Apps and Business Processes

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Teaches how to future-proof data, which is essential in today's ever-changing technological landscape and continuous innovation and growth
Focuses on serverless technologies and their integration with AI and ML, which is a hot and highly sought-after topic in the industry
Core audience: data analysts, data engineers, and data scientists who are looking to enhance their skills with serverless analytics technologies
Provides a centralized data source for scattered data silos, which enables comprehensive analytics and improved data management
Covers both structured and unstructured data, which is increasingly common in today's data-driven world

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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 Serverless Analytics on AWS with these activities:
AWS Glue Crawlers, Data Catalog, and Jobs Fundamentals
Refreshes foundational knowledge about AWS Glue, ETL, Data Catalog, and Jobs.
Browse courses on AWS Glue
Show steps
  • Review the AWS Glue documentation on Crawlers, Data Catalog, and Jobs.
  • Complete the AWS Glue Fundamentals tutorial.
Walkthrough of AWS Glue and Amazon Athena Hands-on Lab
Provides practical experience working with AWS Glue and Amazon Athena.
Browse courses on AWS Glue
Show steps
  • Follow the step-by-step instructions in the AWS Glue and Amazon Athena Hands-on Lab.
  • Experiment with different data sources and query types.
Show all two activities

Career center

Learners who complete Serverless Analytics on AWS will develop knowledge and skills that may be useful to these careers:
Data Engineer
**Data Engineers** design and build data pipelines to ensure data is available, reliable, and accessible for analysis and insights. This course aligns perfectly with the responsibilities of Data Engineers, offering practical knowledge in leveraging AWS Glue and Athena. It equips them with the skills to ingest, process, and prepare data, as well as perform complex transformations and analytics in a scalable and efficient manner. By mastering these technologies, Data Engineers can build robust and scalable data pipelines that support critical business decisions.
Data Analyst
**Data Analysts** play a vital role in extracting insights from raw data by combining programming and analytical skills. This course, 'Serverless Analytics on AWS', provides a solid foundation for Data Analysts to enhance their skills in data preparation, analytics, and visualization using AWS services like Glue and Athena. By mastering these technologies, Data Analysts can effectively manage large and complex datasets, automate data pipelines, and deliver valuable insights that drive data-driven decision-making within organizations.
Analytics Engineer
**Analytics Engineers** design and build data analytics solutions that enable organizations to make data-driven decisions. This course, 'Serverless Analytics on AWS', provides Analytics Engineers with the skills to use AWS services like Glue and Athena to develop scalable, efficient, and cost-effective analytics solutions. By mastering these technologies, Analytics Engineers can build data pipelines that automate data ingestion, transformation, and analysis, enabling organizations to derive valuable insights from their data.
Big Data Architect
**Big Data Architects** design and implement big data solutions that handle large and complex datasets. This course, 'Serverless Analytics on AWS', provides Big Data Architects with the skills to use AWS services like Glue and Athena to build scalable, resilient, and cost-effective big data architectures. By mastering these technologies, Big Data Architects can design and deploy big data solutions that support real-time data processing, data warehousing, and machine learning applications.
Data Scientist
**Data Scientists** use a combination of coding, statistics, and machine learning to extract insights from data and develop predictive models. This course provides a valuable foundation for Data Scientists to enhance their skills in data preparation, analysis, and visualization using AWS services like Glue and Athena. By mastering these technologies, Data Scientists can efficiently handle large and complex datasets, automate data pipelines, and build effective machine learning models that drive data-driven decision-making.
Data Governance Analyst
**Data Governance Analysts** develop and implement data governance policies and procedures to ensure the quality, security, and compliance of data. This course provides a valuable foundation for Data Governance Analysts to understand the use of AWS services like Glue and Athena in the context of data lineage, data quality management, and data access control. By mastering these technologies, Data Governance Analysts can implement effective data governance frameworks that support regulatory compliance and ensure the trustworthiness of data assets.
Data Management Analyst
**Data Management Analysts** design and manage data systems to ensure data is reliable, accessible, and secure. This course provides a strong foundation for Data Management Analysts to understand the use of AWS services like Glue and Athena in the context of data integration, data quality management, and data governance. By mastering these technologies, Data Management Analysts can implement effective data management strategies that support business objectives and regulatory compliance.
Data Integration Engineer
**Data Integration Engineers** design and implement data integration solutions to combine data from multiple sources. This course provides a valuable foundation for Data Integration Engineers to enhance their skills in data extraction, transformation, and loading (ETL) using AWS services like Glue and Athena. By mastering these technologies, Data Integration Engineers can automate the process of integrating data from various sources, ensuring data consistency and completeness for downstream applications and analytics.
Machine Learning Engineer
**Machine Learning Engineers** apply machine learning algorithms to solve complex business problems. This course, 'Serverless Analytics on AWS', provides a strong foundation for Machine Learning Engineers to understand the use of AWS services like Glue and Athena in the context of data preparation and feature engineering. By leveraging these technologies, Machine Learning Engineers can automate the process of extracting, transforming, and enriching data, enabling them to focus on model development and deployment.
Data Warehouse Engineer
**Data Warehouse Engineers** design and manage data warehouses to support data analysis and reporting. This course provides a strong foundation for Data Warehouse Engineers to understand the use of AWS services like Glue and Athena in the context of data warehouse design, implementation, and optimization. By mastering these technologies, Data Warehouse Engineers can build scalable and reliable data warehouses that meet the growing demands of data-driven organizations.
Business Analyst
**Business Analysts** help organizations improve their performance by analyzing data and identifying areas for improvement. This course, 'Serverless Analytics on AWS', provides Business Analysts with the skills to leverage AWS services like Glue and Athena to access, analyze, and interpret data. By mastering these technologies, Business Analysts can gain valuable insights into business operations, customer behavior, and market trends, enabling them to make data-driven recommendations and drive growth.
Machine Learning Architect
**Machine Learning Architects** design and implement machine learning solutions that meet the business needs of organizations. This course, 'Serverless Analytics on AWS', provides Machine Learning Architects with the skills to use AWS services like Glue and Athena to build scalable, secure, and cost-effective machine learning pipelines. By mastering these technologies, Machine Learning Architects can design and deploy machine learning models that leverage large volumes of data for training and inference, enabling organizations to gain valuable insights and make informed decisions.
Cloud Architect
**Cloud Architects** design and implement cloud computing solutions that meet the business needs of organizations. This course, 'Serverless Analytics on AWS', provides Cloud Architects with the skills to leverage AWS services like Glue and Athena to build scalable, secure, and cost-effective data analytics solutions. By mastering these technologies, Cloud Architects can design and deploy cloud-based data pipelines that support real-time analytics, data warehousing, and machine learning applications.
Database Administrator
**Database Administrators** manage and maintain database systems to ensure optimal performance and data integrity. This course provides a valuable foundation for Database Administrators to enhance their skills in data storage, management, and optimization using AWS services like Glue and Athena. By mastering these technologies, Database Administrators can effectively handle large and complex datasets, automate data pipelines, and implement robust data backup and recovery strategies.
Software Engineer
**Software Engineers** design, develop, and maintain software applications. This course, 'Serverless Analytics on AWS', provides Software Engineers with the skills to use AWS services like Glue and Athena to build data-driven applications. By mastering these technologies, Software Engineers can develop applications that ingest, process, and analyze large volumes of data in real-time, enabling them to build innovative and data-centric solutions.

Reading list

We've selected six 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 Serverless Analytics on AWS.
Provides a comprehensive overview of data engineering on AWS, including data pipelines, data quality, and data governance.
Provides a practical guide to using Python for data analysis, covering topics like data cleaning, data manipulation, and data visualization.
Offers a detailed exploration of data-intensive application design principles and patterns, providing a foundation for building scalable and reliable data systems.
Offers a theoretical foundation for big data systems and technologies, covering topics like data models, distributed computing, and data security.
Provides a comprehensive introduction to big data analytics using Hadoop, covering topics like data storage, processing, and analysis.
Offers a gentle introduction to machine learning concepts and techniques, providing a foundation for understanding more advanced topics.

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