[PDF] Data Architecture And The Experience Of Place eBook

Author : Anastasia Karandinou
Publisher : Routledge
Page : 386 pages
File Size : 28,97 MB
Release : 2018-11-12
Category : Architecture
ISBN : 1351139304

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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.

Author : Anastasia Karandinou
Publisher : Routledge
Page : 236 pages
File Size : 25,38 MB
Release : 2018-11-12
Category : Architecture
ISBN : 1351139312

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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.

Author : Charles Tupper
Publisher : Elsevier
Page : 442 pages
File Size : 28,92 MB
Release : 2011-05-09
Category : Computers
ISBN : 0123851270

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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

Author : Piethein Strengholt
Publisher : "O'Reilly Media, Inc."
Page : 404 pages
File Size : 34,81 MB
Release : 2020-07-29
Category : Computers
ISBN : 1492054739

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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

Author : Justin B. Hollander
Publisher : Taylor & Francis
Page : 253 pages
File Size : 16,33 MB
Release : 2020-10-15
Category : Architecture
ISBN : 1000178358

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Embracing a biological and evolutionary perspective to explain the human experience of place, Urban Experience and Design explores how cognitive science and biometric tools provide an evidence-based foundation for architecture and planning. Aiming to promote the creation of a healthier and happier public realm, this book describes how unconscious responses to stimuli, outside our conscious awareness, direct our experience of the built environment and govern human behavior in our surroundings. This collection contains 15 chapters, including contributions from researchers in the US, the UK, the Netherlands, France and Iran. Addressing topics such as the impact of eye-tracking analysis and seeing beauty and empathy within buildings, Urban Experience and Design encourages us to reframe our understanding of design, including the narrative of how modern architecture and planning came to be in the first place. This volume invites students, academics and scholars to see how cognitive science and biometric findings give us remarkable 21st-century metrics for evaluating and improving designs, even before they are built.

Author : W.H. Inmon
Publisher : Academic Press
Page : 431 pages
File Size : 47,29 MB
Release : 2019-04-30
Category : Computers
ISBN : 0128169176

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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

Author : Andrea Resmini
Publisher : Elsevier
Page : 273 pages
File Size : 49,89 MB
Release : 2011-03-23
Category : Language Arts & Disciplines
ISBN : 0123820952

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Pervasive Information Architecture explains the ‘why’ and ‘how’ of pervasive information architecture (IA) through detailed examples and real-world stories. It offers insights about trade-offs that can be made and techniques for even the most unique design challenges. The book will help readers master agile information structures while meeting their unique needs on such devices as smart phones, GPS systems, and tablets. The book provides examples showing how to: model and shape information to adapt itself to users’ needs, goals, and seeking strategies; reduce disorientation and increase legibility and way-finding in digital and physical spaces; and alleviate the frustration associated with choosing from an ever-growing set of information, services, and goods. It also describes relevant connections between pieces of information, services and goods to help users achieve their goals. This book will be of value to practitioners, researchers, academics, andstudents in user experience design, usability, information architecture, interaction design, HCI, web interaction/interface designer, mobile application design/development, and information design. Architects and industrial designers moving into the digital realm will also find this book helpful. Master agile information structures while meeting the unique user needs on such devices as smart phones, GPS systems, and tablets Find out the ‘why’ and ‘how’ of pervasive information architecture (IA) through detailed examples and real-world stories Learn about trade-offs that can be made and techniques for even the most unique design challenges

Author : W.H. Inmon
Publisher : Morgan Kaufmann
Page : 378 pages
File Size : 50,36 MB
Release : 2014-11-26
Category : Computers
ISBN : 0128020911

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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

Author : Zhamak Dehghani
Publisher : "O'Reilly Media, Inc."
Page : 387 pages
File Size : 11,39 MB
Release : 2022-03-08
Category : Computers
ISBN : 1492092363

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Many enterprises are investing in a next-generation data lake, hoping to democratize data at scale to provide business insights and ultimately make automated intelligent decisions. In this practical book, author Zhamak Dehghani reveals that, despite the time, money, and effort poured into them, data warehouses and data lakes fail when applied at the scale and speed of today's organizations. A distributed data mesh is a better choice. Dehghani guides architects, technical leaders, and decision makers on their journey from monolithic big data architecture to a sociotechnical paradigm that draws from modern distributed architecture. A data mesh considers domains as a first-class concern, applies platform thinking to create self-serve data infrastructure, treats data as a product, and introduces a federated and computational model of data governance. This book shows you why and how. Examine the current data landscape from the perspective of business and organizational needs, environmental challenges, and existing architectures Analyze the landscape's underlying characteristics and failure modes Get a complete introduction to data mesh principles and its constituents Learn how to design a data mesh architecture Move beyond a monolithic data lake to a distributed data mesh.