Deciphering Data Architectures

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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.

Data Architecture

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Author : Charles Tupper
language : en
Publisher: Morgan Kaufmann Pub
Release Date : 2011

Data Architecture written by Charles Tupper and has been published by Morgan Kaufmann Pub this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Computers categories.

Data is an expensive and expansive asset. Information hunger has forced retention capacity from megabytes to terabytes of data. Millions of dollars are spent accumulating data, and millions more are paid to the professional staff that nurture, secure, and extract information out of these billions of bytes of data. To ensure that it is usable, data must be structured in a flexible manner that is responsive to change, and is readily available for access. This book explains the principles underlying data architecture, how data evolves with organizations, the challenges organizations face in structuring and managing data, and the proven methods and technologies to solve these complex issues. The author takes a holistic approach to the field of data architecture from various applied perspectives, including data modeling, data quality, enterprise information management, database design, data warehousing, and data governance. Key Features Explains the fundamental concepts of enterprise architecture through definitions and real-world scenarios Teaches data managers and planners how to build a data architecture roadmap, structure the right team, and build a set of solutions for the various challenges they face Offers concise case studies that highlight how fundamental principles are put into practice.

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.

In today's data-driven world, organizations must manage and analyze vast amounts of information to deliver the insights that give them a competitive advantage. Many turn to the medallion architecture because it's a proven and well-known design. Yet implementing a robust data pipeline 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: Lakehouse and medallion architecture fundamentals and key concepts Design considerations for Azure Databricks and Microsoft Fabric Scaling considerations, including governance, security, automation, and more How to make informed decisions when designing or implementing new data architectures Proven patterns for success that align with broader organizational objectives

Architecting Modern Data Platforms

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Author : Jan Kunigk
language : en
Publisher: O'Reilly Media
Release Date : 2018

Architecting Modern Data Platforms written by Jan Kunigk and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with Apache Hadoop categories.

There's a lot of information about big data technologies, but splicing these technologies into an end-to-end enterprise data platform is a daunting task not widely covered. With this practical book, you'll learn how to build big data infrastructure both on-premises and in the cloud and successfully architect a modern data platform. Ideal for enterprise architects, IT managers, application architects, and data engineers, this book shows you how to overcome the many challenges that emerge during Hadoop projects. You'll explore the vast landscape of tools available in the Hadoop and big data realm in a thorough technical primer before diving into: Infrastructure: Look at all component layers in a modern data platform, from the server to the data center, to establish a solid foundation for data in your enterprise Platform: Understand aspects of deployment, operation, security, high availability, and disaster recovery, along with everything you need to know to integrate your platform with the rest of your enterprise IT Taking Hadoop to the cloud: Learn the important architectural aspects of running a big data platform in the cloud while maintaining enterprise security and high availability

Practical Lakehouse Architecture

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Author : Gaurav Ashok Thalpati
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2024-07-24

Practical Lakehouse Architecture written by Gaurav Ashok Thalpati 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 2024-07-24 with Computers categories.

This concise yet comprehensive guide explains how to adopt a data lakehouse architecture to implement modern data platforms. It reviews the design considerations, challenges, and best practices for implementing a lakehouse and provides key insights into the ways that using a lakehouse can impact your data platform, from managing structured and unstructured data and supporting BI and AI/ML use cases to enabling more rigorous data governance and security measures. Practical Lakehouse Architecture shows you how to: Understand key lakehouse concepts and features like transaction support, time travel, and schema evolution Understand the differences between traditional and lakehouse data architectures Differentiate between various file formats and table formats Design lakehouse architecture layers for storage, compute, metadata management, and data consumption Implement data governance and data security within the platform Evaluate technologies and decide on the best technology stack to implement the lakehouse for your use case Make critical design decisions and address practical challenges to build a future-ready data platform Start your lakehouse implementation journey and migrate data from existing systems to the lakehouse

Data Pipelines Pocket Reference

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Author : James Densmore
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2021-02-10

Data Pipelines Pocket Reference written by James Densmore 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 2021-02-10 with Computers categories.

Data pipelines are the foundation for success in data analytics. Moving data from numerous diverse sources and transforming it to provide context is the difference between having data and actually gaining value from it. This pocket reference defines data pipelines and explains how they work in today's modern data stack. You'll learn common considerations and key decision points when implementing pipelines, such as batch versus streaming data ingestion and build versus buy. This book addresses the most common decisions made by data professionals and discusses foundational concepts that apply to open source frameworks, commercial products, and homegrown solutions. You'll learn: What a data pipeline is and how it works How data is moved and processed on modern data infrastructure, including cloud platforms Common tools and products used by data engineers to build pipelines How pipelines support analytics and reporting needs Considerations for pipeline maintenance, testing, and alerting

Azure Openai Service For Cloud Native Applications

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Author : Adrián González Sánchez
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2024-06-27

Azure Openai Service For Cloud Native Applications written by Adrián González Sánchez 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 2024-06-27 with Computers categories.

Get the details, examples, and best practices you need to build generative AI applications, services, and solutions using the power of Azure OpenAI Service. With this comprehensive guide, Microsoft AI specialist Adrián González Sánchez examines the integration and utilization of Azure OpenAI Service—using powerful generative AI models such as GPT-4 and GPT-4o—within the Microsoft Azure cloud computing platform. To guide you through the technical details of using Azure OpenAI Service, this book shows you how to set up the necessary Azure resources, prepare end-to-end architectures, work with APIs, manage costs and usage, handle data privacy and security, and optimize performance. You'll learn various use cases where Azure OpenAI Service models can be applied, and get valuable insights from some of the most relevant AI and cloud experts. Ideal for software and cloud developers, product managers, architects, and engineers, as well as cloud-enabled data scientists, this book will help you: Learn how to implement cloud native applications with Azure OpenAI Service Deploy, customize, and integrate Azure OpenAI Service with your applications Customize large language models and orchestrate knowledge with company-owned data Use advanced roadmaps to plan your generative AI project Estimate cost and plan generative AI implementations for adopter companies

Augmented Analytics

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Author : Willi Weber
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2024-05-31

Augmented Analytics written by Willi Weber 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 2024-05-31 with Business & Economics categories.

Augmented Analytics isn't just another book on data and analytics; it's a holistic resource for reimagining the way your entire organization interacts with information to become insight-driven. Moving beyond traditional, limited ways of making sense of data, Augmented Analytics provides a dynamic, actionable strategy for improving your organization's analytical capabilities. With this book, you can infuse your workflows with intelligent automation and modern artificial intelligence, empowering more team members to make better decisions. You'll find more in these pages than just how to add another forecast to your dashboard; you'll discover a complete approach to achieving analytical excellence in your organization. You'll explore: Key elements and building blocks of augmented analytics, including its benefits, potential challenges, and relevance in today's business landscape Best practices for preparing and implementing augmented analytics in your organization, including analytics roles, workflows, mindsets, tool sets, and skill sets Best practices for data enablement, liberalization, trust, and accessibility How to apply a use-case approach to drive business value and use augmented analytics as an enabler, with selected case studies This book provide a clear, actionable path to accelerate your journey to analytical excellence.

Delta Lake The Definitive Guide

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Author : Denny Lee
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2024-10-30

Delta Lake The Definitive Guide written by Denny Lee 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 2024-10-30 with Computers categories.

Ready to simplify the process of building data lakehouses and data pipelines at scale? In this practical guide, learn how Delta Lake is helping data engineers, data scientists, and data analysts overcome key data reliability challenges with modern data engineering and management techniques. Authors Denny Lee, Tristen Wentling, Scott Haines, and Prashanth Babu (with contributions from Delta Lake maintainer R. Tyler Croy) share expert insights on all things Delta Lake--including how to run batch and streaming jobs concurrently and accelerate the usability of your data. You'll also uncover how ACID transactions bring reliability to data lakehouses at scale. This book helps you: Understand key data reliability challenges and how Delta Lake solves them Explain the critical role of Delta transaction logs as a single source of truth Learn the Delta Lake ecosystem with technologies like Apache Flink, Kafka, and Trino Architect data lakehouses with the medallion architecture Optimize Delta Lake performance with features like deletion vectors and liquid clustering

Building A Scalable Data Warehouse With Data Vault 2 0

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Author : Daniel Linstedt
language : en
Publisher: Morgan Kaufmann
Release Date : 2015-09-15

Building A Scalable Data Warehouse With Data Vault 2 0 written by Daniel Linstedt and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-09-15 with Computers categories.

The Data Vault was invented by Dan Linstedt at the U.S. Department of Defense, and the standard has been successfully applied to data warehousing projects at organizations of different sizes, from small to large-size corporations. Due to its simplified design, which is adapted from nature, the Data Vault 2.0 standard helps prevent typical data warehousing failures. "Building a Scalable Data Warehouse" covers everything one needs to know to create a scalable data warehouse end to end, including a presentation of the Data Vault modeling technique, which provides the foundations to create a technical data warehouse layer. The book discusses how to build the data warehouse incrementally using the agile Data Vault 2.0 methodology. In addition, readers will learn how to create the input layer (the stage layer) and the presentation layer (data mart) of the Data Vault 2.0 architecture including implementation best practices. Drawing upon years of practical experience and using numerous examples and an easy to understand framework, Dan Linstedt and Michael Olschimke discuss: - How to load each layer using SQL Server Integration Services (SSIS), including automation of the Data Vault loading processes. - Important data warehouse technologies and practices. - Data Quality Services (DQS) and Master Data Services (MDS) in the context of the Data Vault architecture. - Provides a complete introduction to data warehousing, applications, and the business context so readers can get-up and running fast - Explains theoretical concepts and provides hands-on instruction on how to build and implement a data warehouse - Demystifies data vault modeling with beginning, intermediate, and advanced techniques - Discusses the advantages of the data vault approach over other techniques, also including the latest updates to Data Vault 2.0 and multiple improvements to Data Vault 1.0