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.
Deciphering Data Architectures
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Author : James Serra
language : en
Publisher:
Release Date : 2024-04-02
Deciphering Data Architectures written by James Serra and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-02 with 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 each architecture to help data professionals understand its pros and cons. In the process, 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, and 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. By reading this book, you'll: Gain a working understanding of several data architectures Know the pros and cons of each approach Distinguish data architecture theory from the reality Learn to 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 Alleviate confusion by clearly defining each data architecture Know what architectures to use for each cloud provider
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.
Cloud Data Architectures Demystified
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Author : Ashok Boddeda
language : en
Publisher: BPB Publications
Release Date : 2023-09-27
Cloud Data Architectures Demystified written by Ashok Boddeda and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-27 with Computers categories.
Learn using Cloud data technologies for improving data analytics and decision-making capabilities for your organization KEY FEATURES ● Get familiar with the fundamentals of data architecture and Cloud computing. ● Design and deploy enterprise data architectures on the Cloud. ● Learn how to leverage AI/ML to gain insights from data. DESCRIPTION Cloud data architectures are a valuable tool for organizations that want to use data to make better decisions. By understanding the different components of Cloud data architectures and the benefits they offer, organizations can select the right architecture for their needs. This book is a holistic guide for using Cloud data technologies to ingest, transform, and analyze data. It covers the entire data lifecycle, from collecting data to transforming it into actionable insights. The readers will get a comprehensive overview of Cloud data technologies and AI/ML algorithms. The readers will learn how to use these technologies and algorithms to improve decision-making, optimize operations, and identify new opportunities. By the end of the book, you will have a comprehensive understanding of loud data architectures and the confidence to implement effective solutions that drive business success. WHAT YOU WILL LEARN ● Learn the fundamental principles of data architecture. ● Understand the working of different cloud ecosystems such as AWS, Azure & GCP. ● Explore different Snowflake data services. ● Learn how to implement data governance policies and procedures. ● Use artificial intelligence (AI) and machine learning (ML) to gain insights from data. WHO THIS BOOK IS FOR This book is for executives, IT professionals, and data enthusiasts who want to learn more about Cloud data architectures. It does not require any prior experience, but a basic understanding of data concepts and technology landscapes will be helpful. TABLE OF CONTENTS 1. Data Architectures and Patterns 2. Enterprise Data Architectures 3. Cloud Fundamentals 4. Azure Data Eco-system 5. AWS Data Services 6. Google Data Services 7. Snowflake Data Eco-system 8. Data Governance 9. Data Intelligence: AI-ML Modeling and Services
Data Architecture
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Author : Charles Tupper
language : en
Publisher: Elsevier
Release Date : 2011-05-09
Data Architecture written by Charles Tupper and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-05-09 with Computers categories.
Data Architecture: From Zen to Reality explains the principles underlying data architecture, how data evolves with organizations, and the challenges organizations face in structuring and managing their data. Using a holistic approach to the field of data architecture, the book describes proven methods and technologies to solve the complex issues dealing with data. It covers the various applied areas of data, including data modelling and data model management, data quality, data governance, enterprise information management, database design, data warehousing, and warehouse design. This text is a core resource for anyone customizing or aligning data management systems, taking the Zen-like idea of data architecture to an attainable reality. The book presents fundamental concepts of enterprise architecture with definitions and real-world applications and scenarios. It teaches data managers and planners about the challenges of building a data architecture roadmap, structuring the right team, and building a long term set of solutions. It includes the detail needed to illustrate how the fundamental principles are used in current business practice. The book is divided into five sections, one of which addresses the software-application development process, defining tools, techniques, and methods that ensure repeatable results. Data Architecture is intended for people in business management involved with corporate data issues and information technology decisions, ranging from data architects to IT consultants, IT auditors, and data administrators. It is also an ideal reference tool for those in a higher-level education process involved in data or information technology management. Presents fundamental concepts of enterprise architecture with definitions and real-world applications and scenarios Teaches data managers and planners about the challenges of building a data architecture roadmap, structuring the right team, and building a long term set of solutions Includes the detail needed to illustrate how the fundamental principles are used in current business practice
Enterprise Data Architecture How To Navigate Its Landscape
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Author : Dave Knifton
language : en
Publisher: Paragon Publishing
Release Date : 2014-10-16
Enterprise Data Architecture How To Navigate Its Landscape written by Dave Knifton and has been published by Paragon Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10-16 with Computers categories.
Are you looking to make better use of data captured within your organisation or want to learn more about how Data Architecture can transform your operations? Answering these questions is at the very heart of Navigating the Data Architecture Landscape. By reading this book you will learn how to: Introduce or improve the Data Architecture function of your organisation Enhance your skills in this domain to deliver more from your data. You may be wondering how a book can do this if it knows nothing about where you are now, or where you want to be? It can, because by leveraging its principles you will discover how to create optimised potential routes to achieve your own Data Architectural objectives. Basic building blocks, concepts and models are defined, enabling you to create new or adapt existing frameworks appropriate for any data landscape. Practical tips and suggestions are also detailed throughout, helping you gain immediate improvements from the way you work and enhance the benefits your organisation can derive from its data. So if you are a Data Architect or deal with data in your organisation and want to learn how to transform the positive yield from its data, then this book is a must read for you! “David has been there and dealt with the issues, which is why this book is an outstanding resource for Data Architects and indeed anyone dealing with the serious challenges of an enterprise data landscape.” – Richard Rendell, Technical Services Director, AgeSmart “An essential read for anyone wishing to practically achieve more benefit from data for their organisation within today’s constraints.” – Reem Zahran - Director, Offering Development, IMS Health “This book provides a comprehensive set of tools enabling you to improve the business outcomes from your organisation’s use of data.” – Andrew Rowland, Global Head Database Engineering, UBS This book is an essential read for Data Architects or indeed anyone wanting to improve the benefit that their organisation can derive from its data usage. It does this by providing principles and models that are appropriate to use within any framework, or even the absence of one. The book is designed to be practical and contains many tips and suggestions as well as examples that can be used as the basis for the reader's own Data Architectural definitions. The breadth of the book covers contemporary themes for Data Architecture and the chapters include; Data Modelling, Enterprise Data Models, Data Governance, Master Data Management and Big Data
Data Mesh
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Author : Zhamak Dehghani
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2022-03-08
Data Mesh written by Zhamak Dehghani 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 2022-03-08 with Computers categories.
We're at an inflection point in data, where our data management solutions no longer match the complexity of organizations, the proliferation of data sources, and the scope of our aspirations to get value from data with AI and analytics. In this practical book, author Zhamak Dehghani introduces data mesh, a decentralized sociotechnical paradigm drawn from modern distributed architecture that provides a new approach to sourcing, sharing, accessing, and managing analytical data at scale. Dehghani guides practitioners, architects, technical leaders, and decision makers on their journey from traditional big data architecture to a distributed and multidimensional approach to analytical data management. Data mesh treats data as a product, considers domains as a primary concern, applies platform thinking to create self-serve data infrastructure, and introduces a federated computational model of data governance. Get a complete introduction to data mesh principles and its constituents Design a data mesh architecture Guide a data mesh strategy and execution Navigate organizational design to a decentralized data ownership model Move beyond traditional data warehouses and lakes to a distributed data mesh
Scalable Big Data Architecture
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Author : Bahaaldine Azarmi
language : en
Publisher: Apress
Release Date : 2015-12-31
Scalable Big Data Architecture written by Bahaaldine Azarmi and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-31 with Computers categories.
This book highlights the different types of data architecture and illustrates the many possibilities hidden behind the term "Big Data", from the usage of No-SQL databases to the deployment of stream analytics architecture, machine learning, and governance. Scalable Big Data Architecture covers real-world, concrete industry use cases that leverage complex distributed applications , which involve web applications, RESTful API, and high throughput of large amount of data stored in highly scalable No-SQL data stores such as Couchbase and Elasticsearch. This book demonstrates how data processing can be done at scale from the usage of NoSQL datastores to the combination of Big Data distribution. When the data processing is too complex and involves different processing topology like long running jobs, stream processing, multiple data sources correlation, and machine learning, it’s often necessary to delegate the load to Hadoop or Spark and use the No-SQL to serve processed data in real time. This book shows you how to choose a relevant combination of big data technologies available within the Hadoop ecosystem. It focuses on processing long jobs, architecture, stream data patterns, log analysis, and real time analytics. Every pattern is illustrated with practical examples, which use the different open sourceprojects such as Logstash, Spark, Kafka, and so on. Traditional data infrastructures are built for digesting and rendering data synthesis and analytics from large amount of data. This book helps you to understand why you should consider using machine learning algorithms early on in the project, before being overwhelmed by constraints imposed by dealing with the high throughput of Big data. Scalable Big Data Architecture is for developers, data architects, and data scientists looking for a better understanding of how to choose the most relevant pattern for a Big Data project and which tools to integrate into that pattern.
Modern Data Architecture On Aws
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Author : Behram Irani
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-08-31
Modern Data Architecture On Aws written by Behram Irani 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 2023-08-31 with Computers categories.
Discover all the essential design and architectural patterns in one place to help you rapidly build and deploy your modern data platform using AWS services Key Features Learn to build modern data platforms on AWS using data lakes and purpose-built data services Uncover methods of applying security and governance across your data platform built on AWS Find out how to operationalize and optimize your data platform on AWS Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionMany IT leaders and professionals are adept at extracting data from a particular type of database and deriving value from it. However, designing and implementing an enterprise-wide holistic data platform with purpose-built data services, all seamlessly working in tandem with the least amount of manual intervention, still poses a challenge. This book will help you explore end-to-end solutions to common data, analytics, and AI/ML use cases by leveraging AWS services. The chapters systematically take you through all the building blocks of a modern data platform, including data lakes, data warehouses, data ingestion patterns, data consumption patterns, data governance, and AI/ML patterns. Using real-world use cases, each chapter highlights the features and functionalities of numerous AWS services to enable you to create a scalable, flexible, performant, and cost-effective modern data platform. By the end of this book, you’ll be equipped with all the necessary architectural patterns and be able to apply this knowledge to efficiently build a modern data platform for your organization using AWS services.What you will learn Familiarize yourself with the building blocks of modern data architecture on AWS Discover how to create an end-to-end data platform on AWS Design data architectures for your own use cases using AWS services Ingest data from disparate sources into target data stores on AWS Build data pipelines, data sharing mechanisms, and data consumption patterns using AWS services Find out how to implement data governance using AWS services Who this book is for This book is for data architects, data engineers, and professionals creating data platforms. The book's use case–driven approach helps you conceptualize possible solutions to specific use cases, while also providing you with design patterns to build data platforms for any organization. It's beneficial for technical leaders and decision makers to understand their organization's data architecture and how each platform component serves business needs. A basic understanding of data & analytics architectures and systems is desirable along with beginner’s level understanding of AWS Cloud.
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Author :
language : en
Publisher: "O'Reilly Media, Inc."
Release Date :
written by 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 with categories.