Modern Data Architectures with Python: A practical guide to building and deploying data pipelines, data warehouses

Description

Learn to build scalable and reliable data ecosystems using Data Mesh, Databricks Spark, and Kafka. Key Features Develop modern data skills in emerging technologies Learn pragmatic design methodologies like Data Mesh and Lake House Grow a deeper understanding of data governance Book Description Data Architecture with Python will teach you how to integrate your machine learning and data science work streams into your data platform. You will also learn how to take your data and build open lakehouses that can combine with any technology. This book will give you deep hands-on experience with tools like Kafka, Apache Spark, MongoDB, Neo4J, Delta Lake MLFlow, and SQL Dashboards. By the end of this journey, you would have amassed a wealth of hands-on and theoretical knowledge to architect your own data ecosystems. What you will learn Understand data pattern patterns such as Delta Architecture Learn key details in Spark Internals and how to increase performance Discover how to design critical Data diagrams Explore MLOps with tools like AutoML and MLflow Learn to build data products in a data mesh Discover data governance and how to build confidence in your data Learn how to introduce Data Visualizations and Dashboards into your data practice Who This Book Is For This book is great for developers, analytics engineers, and managers looking to further develop a data ecosystem within their organization. Basic Python will be useful but not required, Also, experience with data is useful but not necessary to read and do the labs.