Book Image

Data Engineering with AWS

By : Gareth Eagar
Book Image

Data Engineering with AWS

By: Gareth Eagar

Overview of this book

Written by a Senior Data Architect with over twenty-five years of experience in the business, Data Engineering for AWS is a book whose sole aim is to make you proficient in using the AWS ecosystem. Using a thorough and hands-on approach to data, this book will give aspiring and new data engineers a solid theoretical and practical foundation to succeed with AWS. As you progress, you’ll be taken through the services and the skills you need to architect and implement data pipelines on AWS. You'll begin by reviewing important data engineering concepts and some of the core AWS services that form a part of the data engineer's toolkit. You'll then architect a data pipeline, review raw data sources, transform the data, and learn how the transformed data is used by various data consumers. You’ll also learn about populating data marts and data warehouses along with how a data lakehouse fits into the picture. Later, you'll be introduced to AWS tools for analyzing data, including those for ad-hoc SQL queries and creating visualizations. In the final chapters, you'll understand how the power of machine learning and artificial intelligence can be used to draw new insights from data. By the end of this AWS book, you'll be able to carry out data engineering tasks and implement a data pipeline on AWS independently.
Table of Contents (19 chapters)
1
Section 1: AWS Data Engineering Concepts and Trends
6
Section 2: Architecting and Implementing Data Lakes and Data Lake Houses
13
Section 3: The Bigger Picture: Data Analytics, Data Visualization, and Machine Learning

Understanding QuickSight's advanced features – ML Insights and embedded dashboards

The enterprise edition of Amazon QuickSight includes two advanced features that can help you draw out additional insights from your data, and that can enable you to widely share your data by embedding dashboards into applications.

Amazon QuickSight ML Insights

QuickSight ML Insights uses the power of machine learning algorithms to automatically uncover insights and trends, forecast future data points, and identify anomalies in your data.

All of these ML Insights can be easily added to an analysis/dashboard without the author needing to have any machine learning experience or any real understanding of the underlying ML algorithms. However, for those who are interested in the underlying ML algorithms used by QuickSight, Amazon provides comprehensive documentation on this topic. Review the Amazon QuickSight documentation titled Understanding the ML Algorithim Used by Amazon QuickSight...