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IBM大数据 和 分析

IBM大数据 和 分析. 陈景浩 IBM 大中华区 软件部 业务发展总经理 alexc@cn.ibm.com. 主要议题. IBM 对大数据的理解 大数据平台战略 大数据平台 全球的案例 结语. 我们已经进入了一个崭新的计算时代. Volume 巨量. Velocity 爆量. Variety 多样. Veracity* 多变. Data in motion. Data in many forms. Data in doubt. Data at rest.

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IBM大数据 和 分析

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  1. IBM大数据和分析 陈景浩 IBM 大中华区 软件部 业务发展总经理 alexc@cn.ibm.com

  2. 主要议题 • IBM对大数据的理解 • 大数据平台战略 • 大数据平台全球的案例 • 结语

  3. 我们已经进入了一个崭新的计算时代 Volume 巨量 Velocity爆量 Variety多样 Veracity*多变 Data in motion Data in many forms Data in doubt Data at rest Uncertainty due to data inconsistency& incompleteness, ambiguities, latency, deception, model approximations Terabytes to exabytes of existing data to process Streaming data, milliseconds to seconds to respond Structured, unstructured, text, multimedia * Truthfulness, accuracy or precision, correctness 3

  4. 突破性技术因素的推动力 Cloud Computing Social Media Mobile Internet of Things

  5. 全球大数据市场最新动态 Big data activities Big data objectives Realizing a competitive advantage 2012 63% 2011 58% Customer-centric outcomes Employee collaboration 2010 37% Operational optimization 70% increase Risk / financial management New business model Three out of four organizations have big data activities underway; and one in four are either in pilot or production Nearly two out of three respondents reports realizing a competitive advantage from information and analytics Improving customer experience by better understanding behaviors drives almost half of all active big data efforts followed by Operational Optimization IBM Institute for Business Value and the University of Oxford Saïd Business School

  6. The requirement is to analyze many sources of data Source: Forrester Research, June 2011 Global Big Data Online Survey 6

  7. 信息的使用关乎企业发展的命脉… 数量增长 每一天都会产生超过 15 PB 的新信息。数据量预计每 2 年就会翻一番。 多样性增长 80% 的新数据增长源自非关系数据类型和非传统数据类型，如电子邮件、文档、RFID 源、多媒体等 需要作出“更明智的”决策70% 的高管认为，未及时作出决策以及所作出的决策欠佳对其公司的业绩产生了不利影响。

  8. 完整的信息分析生态系统 业务分析应用 交易系统 分析 整合 内容 大数据 主数据 管理 多维分析 转换和清洗 流计算 结构化数据 数据仓库 非结构化数据 时间序列 外部数据源 流数据 管控 质量 生命周期 数据标准 数据安全 变信息为企业洞察力

  9. 大数据分析的广泛应用 Media & Entertainment Energy & Utilities Banking Insurance Telco • Optimizing Offers and Cross-sell • Customer Service and Call Center Efficiency • Fraud Detection & Investigation • Credit & Counterparty Risk • 360˚ View of Domain or Subject • Catastrophe Modeling • Fraud & Abuse • Producer Performance Analytics • Analytics Sandbox • Pro-active Call Center • Network Analytics • Location Based Services • Smart Meter Analytics • Distribution Load Forecasting/Scheduling • Condition Based Maintenance • Create & Target Customer Offerings • Business process transformation • Audience & Marketing Optimization • Multi-Channel Enablement • Digital commerce optimization Travel & Transport Consumer Products Government Healthcare Retail • Actionable Customer Insight • Merchandise Optimization • Dynamic Pricing • Customer Analytics & Loyalty Marketing • Predictive Maintenance Analytics • Capacity & Pricing Optimization • Shelf Availability • Promotional Spend Optimization • Merchandising Compliance • Promotion Exceptions & Alerts • Civilian Services • Defense & Intelligence • Tax & Treasury Services • Measure & Act on Population Health Outcomes • Engage Consumers in their Healthcare Aerospace & Defense Chemical & Petroleum Life Sciences Automotive Electronics • Operational Surveillance, Analysis & Optimization • Data Warehouse Consolidation, Integration & Augmentation • Big Data Exploration for Interdisciplinary Collaboration • Uniform Information Access Platform • Data Warehouse Optimization • Airliner Certification Platform • Advanced Condition Monitoring (ACM) • Advanced Condition Monitoring • Data Warehouse Optimization • Actionable Customer Intelligence • Customer/ Channel Analytics • Advanced Condition Monitoring • Increase visibility into drug safety and effectiveness

  10. 优化交通案例 方案背景 有限的道路资源 • 政府如何最大程度上利用现有路况资源，减少交通瓶颈，缓解交通压力，是优化交通的重要方面； 缓解供需矛盾，更有效的交通预测 不断增长的车流量 • 现有的交通预测能力，通常会具有较大的滞后性，导致交通路线的指引效果大打折扣； 方案描述 斯德哥尔摩交通实时预测系统采集了丰富的数据源，提供实时、有效的交通预测能力 • 数据源 • 车载GPS • 线圈传感器 • 交通速度 • 流动交通密度 • TV 隧道视频 • 实时天气数据 • 警察 • 工建 • 预测结果 • 通过SMS提供交通的实时预测结果； • 频度可调整：一刻钟，半小时，1小时… • 很好的缓解了交通压力 10

  11. 大数据电信的案例 Our understanding of AT&T’s Big Data MissionCommon capability driving diverse value creation opportunities Federated Discovery and Navigation Hadoop File System Data Warehousing Stream Computing Text Analytics Engine Integration, Data Quality, Security, Life Cycle Management, MDM 11 AT&T Big Data Hub Deliver New Products & Services Support AT&T Business Market Opportunities AT&T Business Solutions • Intelligent Cities - Traffic • Government and 911 • Enterprise • Fleet tracking and performance monitoring • Healthcare Monitoring Home Solutions • Healthcare Monitoring • Alarm Monitoring and Security • Up-sell / Cross sell • Targeted Ad insertion • Optimize Video Network Traffic Mobility • Location Based Services • Connected Car • Healthcare Monitoring • Mobile Banking • Up-sell / Cross-sell • Targeted Advertising Comprehensive Capabilities Business Model Expansion Industries Innovative services Innovative products Travel& Transport Insurance Automotive Connected Car Healthcare Home Monitoring Mobile Banking Retail IndustryReach / Operational Knowledge Shared Services Capability AT&T Analytics Center of Excellence Comprehensive set of Capabilities AT&T Big Data Analytics Platform

  12. 大数据生产设备管理的案例 -Analytics is a key enabler in maximizing asset productivity and process efficiency 3x Organizations that lead in analytics outperform those that are just beginning to adopt analytics by 3 times 83% Best-in-Class companies use the data they collect more effectively, and turn that data into actionable intelligence Best-in-Class companies leverage all technology enablers to enhance outcomes 83 percent of CIOs cited analytics as the primary path to competitiveness Source: Aberdeen Group. Asset Management: Using Analytics to Drive Predictive Maintenance. Mar 2013. Asset Performance • Improve quality and reduce failures and outages • Optimize service and support Process Integration • Optimize operations and maintenance • Enhance manufacturing and product quality Source: IBM Institute for Business Value and MIT Sloan Management Review, “Analytics: The New Path to Value” Source: IBM CIO Study, "The Essential CIO" 12

  13. IBM Predictive Maintenance and Quality reduces operational costs, improves asset productivity and increases process efficiency 大数据分析的技术能实现最生产管理高级别的 PMQ -预测性维修和质量 非计划性维修 计划性维修 预防性维修 预测性维修 • Monitor, maintain and optimize assets for better availability, utilization and performance • Predict asset failure to optimize quality and supply chain processes • Remove guesswork from the decision-making process Combined with out-of-box models, dashboards, reports and source connectors 13

  14. 大数据分析优化的技术让 建立企业级的气象站 成为可能 雨量计验证区域 锦屏坝区（3站）； 锦屏流域（15站）； 雅砻江中下游（90站） 临近灾害预警检验 月降水预报检验 短期降水预报检验 14

  15. IBM在高精度数值气象领域关键性能 • 常规天气预报能力 • 预测空间分辨率：可达1公里 • 风速预报平均误差：小于0.5米/秒 • 温度预报平均误差：小于0.5度 • 风功率次日预报准确度：超过92% （国内同类型厂商提供预报平均约为50-75%） • 风功率超短期预准确度：超过94% （国内同类型厂商提供预报平均约为50-78%） • 滚动气象6小时预报计算时间：小于30分钟 • 灾害天气预报能力 • 流域面雨量预报准确度可达80%（包括长江中下游梅雨期和珠江流域华南前汛期） • 强风预报相关性评分：超过90%； • 雷暴雨团预报有效时间：3小时 • 雷击预报相关性评分：超过80%； • 台风路径48h预报误差：小于50公里； • 最大台风风圈强度综合评分：超过90% • 以上项目结果来自与降水预测系统同一气象模型 • - 各地区预报准确度差异取决于当地气象环境特征和观测数据条件。 *相关指标数据基于国际通用的评估方法与定义

  16. 公共安全案例 DATA Sensors optical, acoustic, thermal, chemical, etc. Imagery Satellite, aerial, camera 数据源 NewCapability 快速、准确的集成和分析各种渠道的多样化信息，包括非法停车，呼救电话，目击者证词和犯罪调查等 • Continuous ingest of relevant structured and unstructured data • Holistic entity or activity-centric picture across multiple data sources and types of intelligence 方案描述 • 通过事先防范，识别潜在犯罪地点，降低犯罪率，提升公共安全 • 更有效地组织和调配资源 Entities & Relationships Persons of interest, targets, watch lists Geospatial Location data 方案结果 重大案件犯罪率降低了30%，暴力犯罪降低了15% Social Media Search, blogs, tweets, text messages

  17. 亚洲卫生局减少了诊断错误 • 利用的功能： • Hadoop 系统 • 远程医疗成像诊断服务，以改善农村医疗状况 • 自动筛分和分析大型影像集合，寻找异常和疾病 • 让放射学者和病理学者有可能分析： • 数千个患者影像 • 预期的显著改进： • 减少诊断错误 • 利用医生对类似案例的处理经验改进结果 “超过 80％ 的医疗数据是医疗影像” 17 17 图片： Boaz Yiftach

  18. 亚洲的电信运营商降低了 计费成本并提高了客户满意度 • 功能： • 流计算 • 分析加速器 • 实时调解和分析每天 60亿 CDR • 数据处理时间从12 小时缩短为 1 秒 • 硬件成本降低至原先的1/8 • 主动地解决会影响顾客满意度的问题（如掉话）。 18

  19. 结语: 面向业务的大数据以关键业务为起点，为未来需求实现点到面的扩展 • 大数据不是单纯的技术，而是一种如何利用数据资源的商业策略 • 如何开始大数据建设至关重要 • 在不同的建设阶段，要借助于大数据平台的产品能力来加速实现 • 在早期的基础建设层面要充分考虑兼容将来的扩展需求，逐步演进大数据平台

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