数据驱动建设 在建筑行业中穿越数据时代

本书的读者对象

本书以通俗易懂的语言编写,面向建筑行业的广大读者–从希望掌握现代建筑流程基础知识的学生和新手,到需要最新建筑数据管理方法的专业人士。无论您是建筑师、工程师、工头、施工经理还是数据分析师,这本包含大量独特插图和图表的综合指南都能为您提供宝贵的见解,帮助您了解如何在业务中使用数据来优化和自动化流程、改进决策以及使用现代工具管理不同级别的施工项目

本书是一本综合性指南,结合了将数据管理技术融入建筑流程的理论基础和实践建议。书中重点介绍了如何战略性地使用信息来优化运营、实现流程自动化、改进决策以及使用现代数字工具有效管理项目。

本书涵盖了建筑行业信息工作的理论和实践方面。通过详细的实例,它探讨了任务参数化、需求收集、处理非结构化和多格式数据以及将其转化为建筑公司有效解决方案的方法。

读者可以从需求的形成、基本数据模型的开发,到更复杂的异构信息源整合过程、ETL 流程的创建、信息管道的构建和机器学习模型的建立,逐一了解。这种循序渐进的方法可以清晰地展示建筑行业业务流程和决策支持系统的组织和自动化机制。本书每一部分最后都有一个实用章节,其中包含分步指导,可以将所学知识立即应用到实际项目中。

 

 

部分内容简介

本书围绕价值链中的数据转换概念展开:从数据收集和质量保证到分析处理,以及利用现代工具和方法提取有价值的实用解决方案。

表格开头

1 部分:建筑业的数字化发展 – 追溯数据管理从泥板到现代数字系统的历史变迁,分析模块化系统的出现以及信息数字化在工业革命背景下日益增长的重要性。

2 部分:建筑行业面临的信息挑战–探讨了数据分散、”信息孤岛”、HiPPO 方法对决策的影响以及专有格式的局限性等问题,并建议考虑向人工智能和 LLM 生态系统转变。

3 部分:建筑数据的系统化–对建筑数据进行分类,介绍其组织方法、与企业系统的整合,并讨论建立能力中心以实现信息流程的标准化。

4 部分:数据质量保证–揭示将不同信息转化为高质量结构化数据的方法,包括从各种来源提取数据、使用 LLM 进行验证和建模。

5 部分:成本和时间计算–涉及成本和规划计算的数字化、从 CAD(BIM)模型获取工程量的自动化、4D-8D 建模技术以及建筑项目的 ESG 计算。

6 部分:计算机辅助设计(CAD)和建筑信息模型(BIM–批判性地分析设计技术的演变、系统互操作性问题、开放数据格式的发展趋势以及将人工智能应用于设计的前景。

7 部分:数据分析与自动化 – 介绍信息可视化原理、关键性能指标、ETL 流程、工作流协调工具以及应用语言模型实现日常任务自动化。

8 部分:数据存储和管理–探讨数据存储格式、数据仓库和数据湖概念、数据管理原则和新方法,包括矢量数据库以及 DataOps 和 VectorOps 方法。

9 部分:大数据和机器学习–重点关注向基于历史数据的客观分析过渡、建筑工地上的物联网,以及应用机器学习算法预测项目成本和工期。

10 部分:数字数据时代的建筑业–展望建筑业的未来,分析从因果分析到关联分析的转变、建筑业 “优步化 “的概念以及数字化转型战略。

$171.60

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数据驱动建设 在建筑行业中穿越数据时代
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