、提升竞争 力的关键。阿里云作为行业的领军者，其 Data+AI 技术体系正引领着无数企业 迈向数据智能的新纪元。 本书整理了阿里云在 Data+AI 领域的最新实践案例与深度洞察，涵盖电商、游 戏、营销、运营等多个行业的成功经验，以及技术专家对数据库与 AI 融合趋势 的专业解读。通过理论与实践的结合，我们将共同探索 Data+AI 如何成为企业 智能化转型的核心驱动力，帮助每一位读者找到属于自己的数据智能之路。 第一部分：Data+AI 大咖观点 ............................................................... 1 1. 大咖说 | Data+Al：企业智能化转型的核心驱动力 .......................................... 1 2. 媒体声音 | 重磅升级，阿里云发布首个"Data+Al"驱动的一站式多模数据平 ......... 20 第二部分：Data+AI 行业应用 ............................................................. 25 1. 拥抱 Data+AI | 破解电商 7 大挑战，DMS+AnalyticDB 助力企业智能决策 . 25 2. 拥抱 Data+Al 丨解码 Data+Al 助力游戏日志智能分析 .....

Energy Consumption Non-Green Energy Difficult Cable routing Long construction period Data not cross connected Data updated not timely Indicator not visible Inconsistent command Mains power instability Supervision High Operation Intensity Ports Technological Innovation ： Automatic driving, AI, big data, Intelligent tally, intelligent gate, automatic wharf, intelligent robot Smart Port construction security: port control One network joint control and one-stop service AI Video Cloud Computing IoT Big Data 5G Two Wheel Efficiency Optimize the allocation of port machinery resources, make intelligent

中铁天宝智慧 工地解决方 案 智联工地，慧享数据 All your data in one place 1 、建立智慧工地 智联工地，慧享数据 All your data in one place 1.1 、建立定位基站，使用北斗定位系统 仅 GPS GPS+GLONASS+ 北斗 项目 GPS+GLONASS+ 北斗 精度提升 GPS+GLONASS GPS 卫星 20~23 颗 2% 1.8mm 1.9mm 垂直最大偏差 8.0mm 33.3% 12.0mm 17.0mm 垂直均方差 2.4mm 16.5% 2.9mm 3.8mm 智联工地，慧享数据 All your data in one place 1.2 、创建并使用 BIM 设计 构建工程模型 构建地质模型 施工组织设计  整合的基础  数字化施工要求三维设计；  实现从勘察、设计、施工到运营维护过程整合的必要载 智联工地，慧享数据 All your data in one place 1.3 、在现场建立网络覆盖及视频监控 智联工地，慧享数据 All your data in one place 2 、数字化施工：三维挖掘机引导系统 智联工地，慧享数据 All your data in one place 2 、数字化施工：推土机三维引导系统 智联工地，慧享数据 All your data in one place

Reduction in engineer’s NPT Chevron  50-80% reduction in time for workflow execution  Integrated data to desktop functionality across asset  Complete KPI visibility drives quality and efficiency Petrobras SPE Paper 115367  SPE Paper 111990  SPE Paper 127517  SPE Paper 127520  New Tool Manages Big Data in Real Time, AAPG Explorer, January 2016 ADNOC  Shortfall identification and management cycle Stage 1A Calculated Variables 09-Operating Guidelines Mid Term Work Plan 08-Virtual Metering Data Acquisition & Validation 01-Well Shut-in Testing 02-Well Production Testing & Validation 03-Production

businesses, offering a taste of what would eventually explode into today's omnipresence of sophisticated data tools. I stepped further into the digital realm at Rhodes University, where the untapped potential marked my enlistment into the world of unbroken connectivity. While working at the International Data Corporation, I leveraged technology to morph a week-long task into a few short hours by writing Excel field of AI and its development of ChatGPT, a powerful AI model trained on vast amounts of internet data. • The capabilities of ChatGPT, including its extensive knowledge base and its ability to

cybersecurity, and process optimization, ensuring we can take full advantage of accurate, timely data. The insights included in this report are designed to help inform your decisions in this evolving address these challenges. While the skills gap and labor shortage remain primary business challenges, data from this year's report shows that the shift towards smart manufacturing solutions is not correlated Intelligence/Machine Learning to support quality control in the next 12 months, and 38% will use data collected from current sources to drive product quality monitoring and improvements. Globally

the definitive source of global mobile operator data, analysis and forecasts, and publisher of authoritative industry reports and research. Our data covers every operator group, network and MVNO in accurate and complete set of industry metrics available, comprising tens of millions of individual data points, updated daily. GSMA Intelligence is relied on by leading operators, vendors, regulators third-party industry players, to support strategic decision-making and long- term investment planning. The data is used as an industry reference point and is frequently cited by the media and by the industry

Web Server Project A H/W OS Data Base Login Config Users Roles Integration … HIS LIS RIS PACS Hospital System H/W OS Web Server Project B H/W OS Data Base Login Config Users Roles Integration … H/W OS Web Server Project C H/W OS Data Base Login Config Users Roles Integration … H/W OS Web Server … H/W OS Data Base Login Config Users Roles Integration … 之前 Web Server Product A H/W OS Data Base Login Config Users Roles Integration … HIS LIS RIS PACS Hospital System H/W OS Web Server Product B H/W OS Data Base Login Config Users Roles

学校管理者：科研数据汇编 • 科研人员：科研论文数据治理 • 学校管理者：校间科研数据对比平台 • 科研人员 / 学校管理者：大数据辅助科研系统 全场景数据应用实践 Data application practice 26 种常见分析模 型 管理主题 Management topics 各类 领导主题 Leadership theme 启动 高校数据治理工作 Observing data compliance from data consumption 性别：空 190 0-01-01 320 10 21 9 8 1012 3345 139 7809090 从数据消费观察业务逻辑性 Observing business logic from data consumption 人 事系 统 从数据消费观察数据完整性 Observing data integrity integrity from data consumption 职 评数 据 源 教 师发 展 系统 教 务系 统 科 研系 统 研 究生 系 统 1. 有效主数据模型 2. 按全量补充集成 3. 评估业务系统应用效果 严格执行标准转换 / 统一 清 洗问题 数据合规性检测 不合格数据更新 通过真实应用 场景牵引生产 通过真实应用 场景发现问题 校级数据资产

云原生数据湖 BI Reports Data Warehouse Structured Data ETL Structured, Semi-structured & Unstructured Data ETL Data Science Machine Learning Data Warehouse BI Reports Data Science Machine Learning Caching, Indexing Layer Data Lakehouse Data Lake Structured, Semi-structured & Unstructured Data 1980 年 2010 年 2019+ 数据仓库 Data Warehouse 大数据 / 数据湖 Big Data/Data Lake 云原生数据湖 Data Lakehouse 数据类型：关系型、非关系型、