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Author: Phillip Bernstein Publisher: Birkhäuser ISBN: 3035610444 Category : Architecture Languages : de Pages : 200
Book Description
A systemic transformation is underway in architectural design, engineering and construction. The discipline and profession of architecture is being reshaped in a moment where information, insight and predictions generated during the design process move into construction no longer essentially via drawings. Other, more profound digital techniques yield fundamentally different workflows, responsibilities and business models for architects. This book offers a comprehensive framework, detailed analysis and critical assessment of the challenges and opportunities inherent in those changes. The author sets out to provide direction for a new era in architectural creation that can be understood and managed by a profession which must become better equipped to direct its future.
Author: Phillip Bernstein Publisher: Birkhäuser ISBN: 3035610444 Category : Architecture Languages : de Pages : 200
Book Description
A systemic transformation is underway in architectural design, engineering and construction. The discipline and profession of architecture is being reshaped in a moment where information, insight and predictions generated during the design process move into construction no longer essentially via drawings. Other, more profound digital techniques yield fundamentally different workflows, responsibilities and business models for architects. This book offers a comprehensive framework, detailed analysis and critical assessment of the challenges and opportunities inherent in those changes. The author sets out to provide direction for a new era in architectural creation that can be understood and managed by a profession which must become better equipped to direct its future.
Author: Charles Tupper Publisher: Elsevier ISBN: 9780123851277 Category : Computers Languages : en Pages : 448
Book Description
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: Anastasia Karandinou Publisher: Routledge ISBN: 1351139304 Category : Architecture Languages : en Pages : 386
Book Description
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: Randy Deutsch Publisher: John Wiley & Sons ISBN: 1118898702 Category : Architecture Languages : en Pages : 384
Book Description
“In this comprehensive book, Professor Randy Deutsch has unlocked and laid bare the twenty-first century codice nascosto of architecture. It is data. Big data. Data as driver. . .This book offers us the chance to become informed and knowledgeable pursuers of data and the opportunities it offers to making architecture a wonderful, useful, and smart art form.” —From the Foreword by James Timberlake, FAIA Written for architects, engineers, contractors, owners, and educators, and based on today’s technology and practices, Data-Driven Design and Construction: 25 Strategies for Capturing, Applying and Analyzing Building Data addresses how innovative individuals and firms are using data to remain competitive while advancing their practices. seeks to address and rectify a gap in our learning, by explaining to architects, engineers, contractors and owners—and students of these fields—how to acquire and use data to make more informed decisions. documents how data-driven design is the new frontier of the convergence between BIM and architectural computational analyses and associated tools. is a book of adaptable strategies you and your organization can apply today to make the most of the data you have at your fingertips. Data-Driven Design and Construction was written to help design practitioners and their project teams make better use of BIM, and leverage data throughout the building lifecycle.
Author: François Lévy Publisher: John Wiley & Sons ISBN: 1119252806 Category : Architecture Languages : en Pages : 240
Book Description
Paves the path for the adoption and effective implementation of BIM by design firms, emphasizing the design opportunities that this workflow affords This book expands on BIM (Building Information Modeling), showing its applicability to a range of design-oriented projects. It emphasizes the full impact that a data modeling tool has on design processes, systems, and the high level of collaboration required across the design team. It also explains the quantitative analysis opportunities that BIM affords for sustainable design and for balancing competing design agendas, while highlighting the benefits BIM offers to designing in 3D for construction. The book concludes with a deep look at the possible future of BIM and digitally-enhanced design. Through clear explanation of the processes involved and compelling case studies of design-oriented projects presented with full-color illustrations, BIM for Design Firms: Data Rich Architecture at Small and Medium Scales proves that the power of BIM is far more than an improved documentation and sharing environment. It offers chapters that discuss a broad range of digital design, including problems with BIM, how readers can leverage BIM workflows for complex projects, the way BIM is taught, and more. Helps architects in small and medium design studios realize the cost and efficiency benefits of using BIM Demonstrates how the use of BIM is as relevant and beneficial for a range of projects, from small buildings to large and complex commercial developments Highlights the quantitative analysis opportunities of data-rich BIM models across design disciplines for climate responsiveness, design exploration, visualization, documentation, and error detection Includes full-color case studies of small to medium projects, so that examples are applicable to a range of practice types Features projects by Arca Architects, ARX Protugal Arquitectos, Bearth & Deplazes, Durbach Block Jaggers, Flansburgh Architects, and LEVER Architecture BIM for Design Firms is an excellent book for architects in small and medium-sized studios (including design departments within large firms) as well as for architecture students.
Author: Ahsan Zafar Publisher: Packt Publishing Ltd ISBN: 1801076901 Category : Computers Languages : en Pages : 376
Book Description
Learn everything you need to become a successful data architect on the Salesforce platform Key Features Adopt best practices relating to data governance and learn how to implement them Learn how to work with data in Salesforce while maintaining scalability and security of an instance Gain insights into managing large data volumes in Salesforce Book Description As Salesforce orgs mature over time, data management and integrations are becoming more challenging than ever. Salesforce Data Architecture and Management follows a hands-on approach to managing data and tracking the performance of your Salesforce org. You'll start by understanding the role and skills required to become a successful data architect. The book focuses on data modeling concepts, how to apply them in Salesforce, and how they relate to objects and fields in Salesforce. You'll learn the intricacies of managing data in Salesforce, starting from understanding why Salesforce has chosen to optimize for read rather than write operations. After developing a solid foundation, you'll explore examples and best practices for managing your data. You'll understand how to manage your master data and discover what the Golden Record is and why it is important for organizations. Next, you'll learn how to align your MDM and CRM strategy with a discussion on Salesforce's Customer 360 and its key components. You'll also cover data governance, its multiple facets, and how GDPR compliance can be achieved with Salesforce. Finally, you'll discover Large Data Volumes (LDVs) and best practices for migrating data using APIs. By the end of this book, you'll be well-versed with data management, data backup, storage, and archiving in Salesforce. What you will learn Understand the Salesforce data architecture Explore various data backup and archival strategies Understand how the Salesforce platform is designed and how it is different from other relational databases Uncover tools that can help in data management that minimize data trust issues in your Salesforce org Focus on the Salesforce Customer 360 platform, its key components, and how it can help organizations in connecting with customers Discover how Salesforce can be used for GDPR compliance Measure and monitor the performance of your Salesforce org Who this book is for This book is for aspiring architects, Salesforce admins, and developers. You will also find the book useful if you're preparing for the Salesforce Data Architecture and Management exam. A basic understanding of Salesforce is assumed.
Author: W.H. Inmon Publisher: Academic Press ISBN: 0128169176 Category : Computers Languages : en Pages : 431
Book Description
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: Bill Inmon Publisher: ISBN: 9781634621175 Category : Big data Languages : en Pages : 0
Book Description
Data Lake Architecture will explain how to build a useful data lake, where data scientists and data analysts can solve business challenges and identify new business opportunities
Author: Ivan Mistrik Publisher: Morgan Kaufmann ISBN: 0128093382 Category : Computers Languages : en Pages : 470
Book Description
Software Architecture for Big Data and the Cloud is designed to be a single resource that brings together research on how software architectures can solve the challenges imposed by building big data software systems. The challenges of big data on the software architecture can relate to scale, security, integrity, performance, concurrency, parallelism, and dependability, amongst others. Big data handling requires rethinking architectural solutions to meet functional and non-functional requirements related to volume, variety and velocity. The book's editors have varied and complementary backgrounds in requirements and architecture, specifically in software architectures for cloud and big data, as well as expertise in software engineering for cloud and big data. This book brings together work across different disciplines in software engineering, including work expanded from conference tracks and workshops led by the editors. Discusses systematic and disciplined approaches to building software architectures for cloud and big data with state-of-the-art methods and techniques Presents case studies involving enterprise, business, and government service deployment of big data applications Shares guidance on theory, frameworks, methodologies, and architecture for cloud and big data
Author: Phillip Bernstein
Author: Phillip Bernstein
Author: Charles Tupper
Author: Davina Jackson
Author: Anastasia Karandinou
Author: Randy Deutsch
Author: François Lévy
Author: Ahsan Zafar
Author: W.H. Inmon
Author: Bill Inmon
Author: Ivan Mistrik