Data Architecture And The Experience Of Place


Data Architecture And The Experience Of Place
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Data Architecture And The Experience Of Place


Data Architecture And The Experience Of Place
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Author : Anastasia Karandinou
language : en
Publisher: Routledge
Release Date : 2018-11-12

Data Architecture And The Experience Of Place written by Anastasia Karandinou and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-12 with Architecture categories.


The notion of data is increasingly encountered in spatial, creative and cultural studies. Big data and artificial intelligence are significantly influencing a number of disciplines. Processes, methods and vocabularies from sciences, architecture, arts are borrowed, discussed and tweaked, and new cross-disciplinary fields emerge. More and more, artists and designers are drawing on hard data to interpret the world and to create meaningful, sensuous environments. Architects are using neurophysiological data to improve their understanding of people’s experiences in built spaces. Different disciplines collaborate with scientists to visualise data in different and creative ways, revealing new connections, interpretations and readings. This often demonstrates a genuine desire to comprehend human behaviour and experience and to – possibly – inform design processes accordingly. At the same time, this opens up questions as to why this desire and curiosity is emerging now, how it relates to recent technological advances and how it converses with the cultural, philosophical and methodological context of the disciplines with which it engages. Questions are also raised as to how the use of data and data-informed methods may serve, support, promote and/or challenge political agendas. Data, Architecture and the Experience of Place provides an overview of new approaches on this significant subject and is ideal for students and researchers in digital architecture, architectural theory, design, digital media, sensory studies and related fields.



Data Architecture A Primer For The Data Scientist


Data Architecture A Primer For The Data Scientist
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Author : W.H. Inmon
language : en
Publisher: Academic Press
Release Date : 2019-04-30

Data Architecture A Primer For The Data Scientist written by W.H. Inmon and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-30 with Computers categories.


Over the past 5 years, the concept of big data has matured, data science has grown exponentially, and data architecture has become a standard part of organizational decision-making. Throughout all this change, the basic principles that shape the architecture of data have remained the same. There remains a need for people to take a look at the "bigger picture" and to understand where their data fit into the grand scheme of things. Data Architecture: A Primer for the Data Scientist, Second Edition addresses the larger architectural picture of how big data fits within the existing information infrastructure or data warehousing systems. This is an essential topic not only for data scientists, analysts, and managers but also for researchers and engineers who increasingly need to deal with large and complex sets of data. Until data are gathered and can be placed into an existing framework or architecture, they cannot be used to their full potential. Drawing upon years of practical experience and using numerous examples and case studies from across various industries, the authors seek to explain this larger picture into which big data fits, giving data scientists the necessary context for how pieces of the puzzle should fit together. New case studies include expanded coverage of textual management and analytics New chapters on visualization and big data Discussion of new visualizations of the end-state architecture



Data Architecture


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



Big Data Architect S Handbook


Big Data Architect S Handbook
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Author : Syed Muhammad Fahad Akhtar
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-06-21

Big Data Architect S Handbook written by Syed Muhammad Fahad Akhtar 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 2018-06-21 with Computers categories.


A comprehensive end-to-end guide that gives hands-on practice in big data and Artificial Intelligence Key Features Learn to build and run a big data application with sample code Explore examples to implement activities that a big data architect performs Use Machine Learning and AI for structured and unstructured data Book Description The big data architects are the “masters” of data, and hold high value in today’s market. Handling big data, be it of good or bad quality, is not an easy task. The prime job for any big data architect is to build an end-to-end big data solution that integrates data from different sources and analyzes it to find useful, hidden insights. Big Data Architect’s Handbook takes you through developing a complete, end-to-end big data pipeline, which will lay the foundation for you and provide the necessary knowledge required to be an architect in big data. Right from understanding the design considerations to implementing a solid, efficient, and scalable data pipeline, this book walks you through all the essential aspects of big data. It also gives you an overview of how you can leverage the power of various big data tools such as Apache Hadoop and ElasticSearch in order to bring them together and build an efficient big data solution. By the end of this book, you will be able to build your own design system which integrates, maintains, visualizes, and monitors your data. In addition, you will have a smooth design flow in each process, putting insights in action. What you will learn Learn Hadoop Ecosystem and Apache projects Understand, compare NoSQL database and essential software architecture Cloud infrastructure design considerations for big data Explore application scenario of big data tools for daily activities Learn to analyze and visualize results to uncover valuable insights Build and run a big data application with sample code from end to end Apply Machine Learning and AI to perform big data intelligence Practice the daily activities performed by big data architects Who this book is for Big Data Architect’s Handbook is for you if you are an aspiring data professional, developer, or IT enthusiast who aims to be an all-round architect in big data. This book is your one-stop solution to enhance your knowledge and carry out easy to complex activities required to become a big data architect.



Enterprise Data Architecture How To Navigate Its Landscape


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 Architecture A Primer For The Data Scientist


Data Architecture A Primer For The Data Scientist
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Author : W.H. Inmon
language : en
Publisher: Morgan Kaufmann
Release Date : 2014-11-26

Data Architecture A Primer For The Data Scientist written by W.H. Inmon and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-26 with Computers categories.


Today, the world is trying to create and educate data scientists because of the phenomenon of Big Data. And everyone is looking deeply into this technology. But no one is looking at the larger architectural picture of how Big Data needs to fit within the existing systems (data warehousing systems). Taking a look at the larger picture into which Big Data fits gives the data scientist the necessary context for how pieces of the puzzle should fit together. Most references on Big Data look at only one tiny part of a much larger whole. Until data gathered can be put into an existing framework or architecture it can’t be used to its full potential. Data Architecture a Primer for the Data Scientist addresses the larger architectural picture of how Big Data fits with the existing information infrastructure, an essential topic for the data scientist. Drawing upon years of practical experience and using numerous examples and an easy to understand framework. W.H. Inmon, and Daniel Linstedt define the importance of data architecture and how it can be used effectively to harness big data within existing systems. You’ll be able to: Turn textual information into a form that can be analyzed by standard tools. Make the connection between analytics and Big Data Understand how Big Data fits within an existing systems environment Conduct analytics on repetitive and non-repetitive data Discusses the value in Big Data that is often overlooked, non-repetitive data, and why there is significant business value in using it Shows how to turn textual information into a form that can be analyzed by standard tools Explains how Big Data fits within an existing systems environment Presents new opportunities that are afforded by the advent of Big Data Demystifies the murky waters of repetitive and non-repetitive data in Big Data



Scalable Data Architecture With Java


Scalable Data Architecture With Java
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Author : Sinchan Banerjee
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-09-30

Scalable Data Architecture With Java written by Sinchan Banerjee 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 2022-09-30 with Computers categories.


Orchestrate data architecting solutions using Java and related technologies to evaluate, recommend and present the most suitable solution to leadership and clients Key FeaturesLearn how to adapt to the ever-evolving data architecture technology landscapeUnderstand how to choose the best suited technology, platform, and architecture to realize effective business valueImplement effective data security and governance principlesBook Description Java architectural patterns and tools help architects to build reliable, scalable, and secure data engineering solutions that collect, manipulate, and publish data. This book will help you make the most of the architecting data solutions available with clear and actionable advice from an expert. You'll start with an overview of data architecture, exploring responsibilities of a Java data architect, and learning about various data formats, data storage, databases, and data application platforms as well as how to choose them. Next, you'll understand how to architect a batch and real-time data processing pipeline. You'll also get to grips with the various Java data processing patterns, before progressing to data security and governance. The later chapters will show you how to publish Data as a Service and how you can architect it. Finally, you'll focus on how to evaluate and recommend an architecture by developing performance benchmarks, estimations, and various decision metrics. By the end of this book, you'll be able to successfully orchestrate data architecture solutions using Java and related technologies as well as to evaluate and present the most suitable solution to your clients. What you will learnAnalyze and use the best data architecture patterns for problemsUnderstand when and how to choose Java tools for a data architectureBuild batch and real-time data engineering solutions using JavaDiscover how to apply security and governance to a solutionMeasure performance, publish benchmarks, and optimize solutionsEvaluate, choose, and present the best architectural alternativesUnderstand how to publish Data as a Service using GraphQL and a REST APIWho this book is for Data architects, aspiring data architects, Java developers and anyone who wants to develop or optimize scalable data architecture solutions using Java will find this book useful. A basic understanding of data architecture and Java programming is required to get the best from this book.



Data Architecture


Data Architecture
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Author : W. H. Inmon
language : en
Publisher:
Release Date : 2014

Data Architecture written by W. H. Inmon and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with Data mining categories.


Today, the world is trying to create and educate data scientists because of the phenomenon of Big Data. And everyone is looking deeply into this technology. But no one is looking at the larger architectural picture of how Big Data needs to fit within the existing systems (data warehousing systems). Taking a look at the larger picture into which Big Data fits gives the data scientist the necessary context for how pieces of the puzzle should fit together. Most references on Big Data look at only one tiny part of a much larger whole. Until data gathered can be put into an existing framework or architecture it can't be used to its full potential. Data Architecture a Primer for the Data Scientist addresses the larger architectural picture of how Big Data fits with the existing information infrastructure, an essential topic for the data scientist. Drawing upon years of practical experience and using numerous examples and an easy to understand framework. W.H. Inmon, and Daniel Linstedt define the importance of data architecture and how it can be used effectively to harness big data within existing systems. You'll be able to: Turn textual information into a form that can be analyzed by standard tools. Make the connection between analytics and Big Data Understand how Big Data fits within an existing systems environment Conduct analytics on repetitive and non-repetitive data Discusses the value in Big Data that is often overlooked, non-repetitive data, and why there is significant business value in using it Shows how to turn textual information into a form that can be analyzed by standard tools. Explains how Big Data fits within an existing systems environment Presents new opportunities that are afforded by the advent of Big Data Demystifies the murky waters of repetitive and non-repetitive data in Big Data.



Data Management At Scale


Data Management At Scale
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Author : Piethein Strengholt
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2020-07-29

Data Management At Scale 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 2020-07-29 with Computers categories.


As data management and integration continue to evolve rapidly, storing all your data in one place, such as a data warehouse, is no longer scalable. In the very near future, data will need to be distributed and available for several technological solutions. With this practical book, you’ll learnhow to migrate your enterprise from a complex and tightly coupled data landscape to a more flexible architecture ready for the modern world of data consumption. Executives, data architects, analytics teams, and compliance and governance staff will learn how to build a modern scalable data landscape using the Scaled Architecture, which you can introduce incrementally without a large upfront investment. Author Piethein Strengholt provides blueprints, principles, observations, best practices, and patterns to get you up to speed. Examine data management trends, including technological developments, regulatory requirements, and privacy concerns Go deep into the Scaled Architecture and learn how the pieces fit together Explore data governance and data security, master data management, self-service data marketplaces, and the importance of metadata



Deciphering Data Architectures


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.