Modern Data Architectures with Python: A practical guide to building and deployi

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Modern Data Architectures with Python allows you to adopt a hands-on approach to learning the latest data tooling and techniques needed for architecting data solutions.

FORMATPaperback CONDITIONBrand New Publisher Description

Build scalable and reliable data ecosystems using Data Mesh, Databricks Spark, and KafkaKey FeaturesDevelop modern data skills used in emerging technologiesLearn pragmatic design methodologies such as Data Mesh and data lakehousesGain a deeper understanding of data governancePurchase of the print or Kindle book includes a free PDF eBookBook DescriptionModern Data Architectures with Python will teach you how to seamlessly incorporate your machine learning and data science work streams into your open data platforms. You'll learn how to take your data and create open lakehouses that work with any technology using tried-and-true techniques, including the medallion architecture and Delta Lake.Starting with the fundamentals, this book will help you build pipelines on Databricks, an open data platform, using SQL and Python. You'll gain an understanding of notebooks and applications written in Python using standard software engineering tools such as git, pre-commit, Jenkins, and Github. Next, you'll delve into streaming and batch-based data processing using Apache Spark and Confluent Kafka. As you advance, you'll learn how to deploy your resources using infrastructure as code and how to automate your workflows and code development. Since any data platform's ability to handle and work with AI and ML is a vital component, you'll also explore the basics of ML and how to work with modern MLOps tooling. Finally, you'll get hands-on experience with Apache Spark, one of the key data technologies in today's market.By the end of this book, you'll have amassed a wealth of practical and theoretical knowledge to build, manage, orchestrate, and architect your data ecosystems.What you will learnUnderstand data patterns including delta architectureDiscover how to increase performance with Spark internalsFind out how to design critical data diagramsExplore MLOps with tools such as AutoML and MLflowGet to grips with building data products in a data meshDiscover data governance and build confidence in your dataIntroduce data visualizations and dashboards into your data practiceWho this book is forThis book is for developers, analytics engineers, and managers looking to further develop a data ecosystem within their organization. While they're not prerequisites, basic knowledge of Python and prior experience with data will help you to read and follow along with the examples.

Author Biography

Brian Lipp is a Technology Polyglot, Engineer, and Solution Architect with a wide skillset in many technology domains. His programming background has ranged from R, Python, and Scala, to Go and Rust development. He has worked on Big Data systems, Data Lakes, data warehouses, and backend software engineering. Brian earned a Master of Science, CSIS from Pace University in 2009. He is currently a Sr. Data Engineer working with large Tech firms to build Data Ecosystems.

Table of Contents

Table of ContentsModern Data Processing ArchitecturesBasics of Data Analytics EngineeringCloud Storage and Processing ConceptsPython Batch and Stream Processing with SparkStreaming Data with KafkaPython MLOpsPython and SQL based VisualizationsIntegrating CI into your workflowData OrchestrationData GovernanceIntroduction to Saturn Insurance, Deploying CI and ELTData Governance and Dashboards

Details ISBN1801070490 Author Brian Lipp Pages 318 Publisher Packt Publishing Limited Year 2023 ISBN-13 9781801070492 Format Paperback Publication Date 2023-09-29 Imprint Packt Publishing Limited Subtitle A practical guide to building and deploying data pipelines, data warehouses, and data lakes with Python Place of Publication Birmingham Country of Publication United Kingdom Audience General UK Release Date 2023-09-29 DEWEY 005.13/3 We've got this

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