Modern Data Architectures With Python
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Modern Data Architectures With Python
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Author : Brian Lipp
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-09-29
Modern Data Architectures With Python written by Brian Lipp and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-29 with Computers categories.
Build scalable and reliable data ecosystems using Data Mesh, Databricks Spark, and Kafka Key Features Develop modern data skills used in emerging technologies Learn pragmatic design methodologies such as Data Mesh and data lakehouses Gain a deeper understanding of data governance Purchase of the print or Kindle book includes a free PDF eBook Book 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 learn Understand data patterns including delta architecture Discover how to increase performance with Spark internals Find out how to design critical data diagrams Explore MLOps with tools such as AutoML and MLflow Get to grips with building data products in a data mesh Discover data governance and build confidence in your data Introduce data visualizations and dashboards into your data practice Who 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.
Redis Mastery Advanced Techniques For Scalable Data Architecture
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Author : Adam Jones
language : en
Publisher: Walzone Press
Release Date : 2025-01-03
Redis Mastery Advanced Techniques For Scalable Data Architecture written by Adam Jones and has been published by Walzone Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-03 with Computers categories.
Unleash the full potential of your data with "Redis Mastery: Advanced Techniques for Scalable Data Architecture," the ultimate guide to mastering Redis—an essential in-memory database that amplifies application performance. This comprehensive tome takes you beyond the basics, delving into sophisticated techniques that propel your data architecture to new heights. Explore the intricacies of Redis's robust data structures, secure and fine-tune your deployment, and tackle advanced challenges like seamless scaling and ensuring high availability. Discover diverse applications from powering real-time analytics to managing complex message queues. Whether you're a developer seeking to optimize application efficiency, a system administrator focused on resilient data stores, or a tech enthusiast eager to master cutting-edge database solutions, this book is your indispensable resource. With lucid explanations, practical demonstrations, and seasoned advice, "Redis Mastery" equips you to harness Redis's full capabilities. Revolutionize your data handling with advanced techniques that augment durability and enable effortless scalability. Elevate your data strategy and build high-performance, future-ready applications with "Redis Mastery: Advanced Techniques for Scalable Data Architecture." Redis is your gateway to crafting applications that excel under pressure and adapt seamlessly to ever-evolving demands. Secure your copy today and embark on your journey to becoming a Redis virtuoso!
Deciphering Data Architectures
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Author : James Serra
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2024-02-06
Deciphering Data Architectures written by James Serra and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-06 with Computers categories.
Data fabric, data lakehouse, and data mesh have recently appeared as viable alternatives to the modern data warehouse. These new architectures have solid benefits, but they're also surrounded by a lot of hyperbole and confusion. This practical book provides a guided tour of these architectures to help data professionals understand the pros and cons of each. James Serra, big data and data warehousing solution architect at Microsoft, examines common data architecture concepts, including how data warehouses have had to evolve to work with data lake features. You'll learn what data lakehouses can help you achieve, as well as how to distinguish data mesh hype from reality. Best of all, you'll be able to determine the most appropriate data architecture for your needs. With this book, you'll: Gain a working understanding of several data architectures Learn the strengths and weaknesses of each approach Distinguish data architecture theory from reality Pick the best architecture for your use case Understand the differences between data warehouses and data lakes Learn common data architecture concepts to help you build better solutions Explore the historical evolution and characteristics of data architectures Learn essentials of running an architecture design session, team organization, and project success factors Free from product discussions, this book will serve as a timeless resource for years to come.
Comprehensive Guide To Matillion For Data Integration
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Author : Richard Johnson
language : en
Publisher: HiTeX Press
Release Date : 2025-06-12
Comprehensive Guide To Matillion For Data Integration written by Richard Johnson and has been published by HiTeX Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-12 with Computers categories.
"Comprehensive Guide to Matillion for Data Integration" Unlock the full potential of modern cloud data integration with the "Comprehensive Guide to Matillion for Data Integration." This meticulously structured resource provides a deep exploration of contemporary ETL and ELT architectures, equipping readers with the context and clarity needed to navigate an evolving data ecosystem. Through comparative analysis and best-practice recommendations, it situates Matillion within the broader landscape of cloud-native data platforms, addressing the imperatives of scalability, security, and compliance that define today’s enterprise data strategies. From foundational concepts to advanced engineering techniques, the guide walks through every critical stage of deploying, managing, and optimizing Matillion environments. Readers will find practical guidance on architecture fundamentals, project setup, version control, and automated deployments, all crucial for ensuring robust, scalable, and reliable data pipelines. Detailed chapters cover integration with leading cloud data warehouses, operationalization, error handling, and monitoring, empowering data teams to deliver high-quality, resilient workflows under demanding production conditions. Distinguished by its focus on real-world application and future-proofing, the book delves into advanced data engineering practices, governance, security models, and cost optimization. A wealth of patterns and case studies illuminate best practices for both migration and greenfield build-outs, while insights into Matillion’s roadmap prepare readers for the ongoing evolution of cloud-based ETL. Whether you are a data engineer, architect, or platform owner, this guide is an essential companion for leveraging Matillion at enterprise scale.
Building Medallion Architectures
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Author : Piethein Strengholt
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2025-03-28
Building Medallion Architectures written by Piethein Strengholt and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-28 with Computers categories.
To deliver the insights that give them a competitive advantage, organizations increasingly turn to the proven Medallion architecture. Yet implementing a robust data architecture can be difficult, particularly when it comes to using the Medallion architecture's Bronze, Silver, and Gold layers—done wrong, it can hamper your ability to make data-driven decisions. This practical guide helps you build a Medallion architecture the right way with Azure Databricks and Microsoft Fabric. Drawing on hands-on experience from the field, Piethein Strengholt demystifies common assumptions and complex problems you'll face when embarking on a new data architecture. Architects and engineers of all stripes will find answers to the most typical questions along with insights from real organizations about what's worked, what hasn't, and why. You'll learn: Learn how to build a Medallion architecture with Azure Databricks and Microsoft Fabric Gain insights from three real case studies that illustrate practical field experience and lessons learned Explore scaling considerations, including governance, security, generative AI, and more Make informed decisions when designing or implementing new data architectures Get proven patterns for success that align with broader organizational objectives
Big Data On Kubernetes
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Author : Neylson Crepalde
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-07-19
Big Data On Kubernetes written by Neylson Crepalde and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-19 with Computers categories.
Gain hands-on experience in building efficient and scalable big data architecture on Kubernetes, utilizing leading technologies such as Spark, Airflow, Kafka, and Trino Key Features Leverage Kubernetes in a cloud environment to integrate seamlessly with a variety of tools Explore best practices for optimizing the performance of big data pipelines Build end-to-end data pipelines and discover real-world use cases using popular tools like Spark, Airflow, and Kafka Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionIn today's data-driven world, organizations across different sectors need scalable and efficient solutions for processing large volumes of data. Kubernetes offers an open-source and cost-effective platform for deploying and managing big data tools and workloads, ensuring optimal resource utilization and minimizing operational overhead. If you want to master the art of building and deploying big data solutions using Kubernetes, then this book is for you. Written by an experienced data specialist, Big Data on Kubernetes takes you through the entire process of developing scalable and resilient data pipelines, with a focus on practical implementation. Starting with the basics, you’ll progress toward learning how to install Docker and run your first containerized applications. You’ll then explore Kubernetes architecture and understand its core components. This knowledge will pave the way for exploring a variety of essential tools for big data processing such as Apache Spark and Apache Airflow. You’ll also learn how to install and configure these tools on Kubernetes clusters. Throughout the book, you’ll gain hands-on experience building a complete big data stack on Kubernetes. By the end of this Kubernetes book, you’ll be equipped with the skills and knowledge you need to tackle real-world big data challenges with confidence.What you will learn Install and use Docker to run containers and build concise images Gain a deep understanding of Kubernetes architecture and its components Deploy and manage Kubernetes clusters on different cloud platforms Implement and manage data pipelines using Apache Spark and Apache Airflow Deploy and configure Apache Kafka for real-time data ingestion and processing Build and orchestrate a complete big data pipeline using open-source tools Deploy Generative AI applications on a Kubernetes-based architecture Who this book is for If you’re a data engineer, BI analyst, data team leader, data architect, or tech manager with a basic understanding of big data technologies, then this big data book is for you. Familiarity with the basics of Python programming, SQL queries, and YAML is required to understand the topics discussed in this book.
Introduction To Data Platforms
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Author : Anthony David Giordano
language : en
Publisher: Fulton Books, Inc.
Release Date : 2022-11-03
Introduction To Data Platforms written by Anthony David Giordano and has been published by Fulton Books, Inc. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-03 with Computers categories.
Digital, cloud, and artificial intelligence (AI) have disrupted how we use data. This disruption has changed the way we need to provision, curate, and publish data for the multiple use cases in today's technology-driven environment. This text will cover how to design, develop, and evolve a data platform for all the uses of enterprise data needed in today's digital organization. This book focuses on explaining what a data platform is, what value it provides, how is it engineered, and how to deploy a data platform and support organization. In this context, Introduction to Data Platforms reviews the current requirements for data in the digital age and quantifies the use cases; discusses the evolution of data over the past twenty years, which is a core driver of the modern data platform; defines what a data platform is and defines the architectural components and layers of a data platform; provides the architectural layers or capabilities of a data platform; reviews cloud- and commercial-software vendors that populate the data-platform space; provides a step-by-step approach to engineering, deploying, supporting, and evolving a data-platform environment; provides a step-by-step approach to migrating legacy data warehouses, data marts, and data lakes/sandboxes to a data platform; and reviews organizational structures for managing data platform environments.
97 Things Every Data Engineer Should Know
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Author : Tobias Macey
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2021-06-11
97 Things Every Data Engineer Should Know written by Tobias Macey and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-11 with Computers categories.
Take advantage of the sky-high demand for data engineers today. With this in-depth book, current and aspiring engineers will learn powerful, real-world best practices for managing data big and small. Contributors from Google, Microsoft, IBM, Facebook, Databricks, and GitHub share their experiences and lessons learned for overcoming a variety of specific and often nagging challenges. Edited by Tobias Macey from MIT Open Learning, this book presents 97 concise and useful tips for cleaning, prepping, wrangling, storing, processing, and ingesting data. Data engineers, data architects, data team managers, data scientists, machine learning engineers, and software engineers will greatly benefit from the wisdom and experience of their peers. Projects include: Building pipelines Stream processing Data privacy and security Data governance and lineage Data storage and architecture Ecosystem of modern tools Data team makeup and culture Career advice.
Data Engineering With Apache Spark Delta Lake And Lakehouse
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Author : Manoj Kukreja
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-10-22
Data Engineering With Apache Spark Delta Lake And Lakehouse written by Manoj Kukreja and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-22 with Computers categories.
Understand the complexities of modern-day data engineering platforms and explore strategies to deal with them with the help of use case scenarios led by an industry expert in big data Key FeaturesBecome well-versed with the core concepts of Apache Spark and Delta Lake for building data platformsLearn how to ingest, process, and analyze data that can be later used for training machine learning modelsUnderstand how to operationalize data models in production using curated dataBook Description In the world of ever-changing data and schemas, it is important to build data pipelines that can auto-adjust to changes. This book will help you build scalable data platforms that managers, data scientists, and data analysts can rely on. Starting with an introduction to data engineering, along with its key concepts and architectures, this book will show you how to use Microsoft Azure Cloud services effectively for data engineering. You'll cover data lake design patterns and the different stages through which the data needs to flow in a typical data lake. Once you've explored the main features of Delta Lake to build data lakes with fast performance and governance in mind, you'll advance to implementing the lambda architecture using Delta Lake. Packed with practical examples and code snippets, this book takes you through real-world examples based on production scenarios faced by the author in his 10 years of experience working with big data. Finally, you'll cover data lake deployment strategies that play an important role in provisioning the cloud resources and deploying the data pipelines in a repeatable and continuous way. By the end of this data engineering book, you'll know how to effectively deal with ever-changing data and create scalable data pipelines to streamline data science, ML, and artificial intelligence (AI) tasks. What you will learnDiscover the challenges you may face in the data engineering worldAdd ACID transactions to Apache Spark using Delta LakeUnderstand effective design strategies to build enterprise-grade data lakesExplore architectural and design patterns for building efficient data ingestion pipelinesOrchestrate a data pipeline for preprocessing data using Apache Spark and Delta Lake APIsAutomate deployment and monitoring of data pipelines in productionGet to grips with securing, monitoring, and managing data pipelines models efficientlyWho this book is for This book is for aspiring data engineers and data analysts who are new to the world of data engineering and are looking for a practical guide to building scalable data platforms. If you already work with PySpark and want to use Delta Lake for data engineering, you'll find this book useful. Basic knowledge of Python, Spark, and SQL is expected.
Game Programming Gems 6
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Author : Michael Dickheiser
language : en
Publisher:
Release Date : 2006
Game Programming Gems 6 written by Michael Dickheiser and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Computers categories.
One CD-ROM disc in pocket.