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

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

主要议题

3

* Truthfulness, accuracy or precision, correctness

Volume 巨量 Velocity 爆量 Veracity* 多变Variety 多样

Data at rest

Terabytes to exabytes of existing

data to process

Data in motion

Streaming data, milliseconds to

seconds to respond

Data in many forms

Structured, unstructured, text,

multimedia

Data in doubt

Uncertainty due to data inconsistency& incompleteness,

ambiguities, latency, deception, model approximations

我们已经进入了一个崭新的计算时代

突破性技术因素的推动力

Social Media

Cloud Computing

Mobile

Internet of Things

Big data objectives

Customer-centric outcomes

Operational optimization

Risk / financial management

New business model

Employee collaboration

Improving customer experience by better understanding behaviors

drives almost half of all active big data efforts followed by Operational

Optimization

Realizing a competitive advantage

63%

58%

37%

2012

2011

201070%

increase

Nearly two out of three respondents reports realizing a

competitive advantage from information and analytics

Big data activities

Three out of four organizations have big data activities underway; and one in four are either in pilot

or production

IBM Institute for Business Value and the University of Oxford Saïd Business School

全球大数据市场最新动态

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The requirement is to analyze many sources of data

Source: Forrester Research, June 2011 Global Big Data Online Survey

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。

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。

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

信息的使用关乎企业发展的命脉…

分析整合

交易系统

管理

业务分析应用

外部数据源

多维分析

流计算

大数据主数据

非结构化数据结构化数据

流数据 管控质量 数据安全生命周期

数据仓库

数据标准

内容

时间序列

转换和清洗

变信息为企业洞察力

完整的信息分析生态系统

大数据分析的广泛应用Insurance

• 360˚ View of Domain or Subject

• Catastrophe Modeling

• Fraud & Abuse

• Producer Performance Analytics

• Analytics Sandbox

Banking

• Optimizing Offers and Cross-sell

• Customer Service and Call Center Efficiency

• Fraud Detection & Investigation

• Credit & Counterparty Risk

Telco

• Pro-active Call Center

• Network Analytics• Location Based

Services

Energy & Utilities

• Smart Meter Analytics• Distribution Load

Forecasting/Scheduling

• Condition Based Maintenance

• Create & Target Customer Offerings

Media & Entertainment

• Business process transformation

• Audience & Marketing Optimization

• Multi-Channel Enablement

• Digital commerce optimization

Retail

• Actionable Customer Insight

• Merchandise Optimization

• Dynamic Pricing

Travel & Transport

• Customer Analytics & Loyalty Marketing

• Predictive Maintenance Analytics

• Capacity & Pricing Optimization

Consumer Products

• Shelf Availability• Promotional Spend

Optimization• Merchandising

Compliance• Promotion

Exceptions & Alerts

Government

• Civilian Services• Defense &

Intelligence• Tax & Treasury

Services

Healthcare

• Measure & Act on Population Health Outcomes

• Engage Consumers in their Healthcare

Automotive

• Advanced Condition Monitoring

• Data Warehouse Optimization

• Actionable Customer Intelligence

Life Sciences

• Increase visibility into drug safety and effectiveness

Chemical & Petroleum

• Operational Surveillance, Analysis & Optimization

• Data Warehouse Consolidation, Integration & Augmentation

• Big Data Exploration for Interdisciplinary Collaboration

Aerospace & Defense

• Uniform Information Access Platform

• Data Warehouse Optimization

• Airliner Certification Platform

• Advanced Condition Monitoring (ACM)

Electronics

• Customer/ Channel Analytics

• Advanced Condition Monitoring

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优化交通案例方案背景

方案描述

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；

有限的道路资源

不断增长的车流量缓解供需矛盾，更有效的交通预测

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；

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

大数据电信的案例 Our understanding of AT&T’s Big Data Mission

Common capability driving diverse value creation 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

Support AT&T Business Market Opportunities

Comprehensive Capabilities

AT&T Big Data Hub

Business Model Expansion

Industries

Innovative services

Innovative products

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Federated Discovery and NavigationHadoop File System

Data Warehousing

Stream Computing

Text Analytics Engine

Integration, Data Quality, Security, Life Cycle Management, MDM

AutomotiveConnected Car

HealthcareHome Monitoring

Insurance

Mobile Banking Retail

Travel& Transport

Deliver New Products & Services

Shared Services Capability

AT&T Analytics Center of Excellence

Comprehensive set of Capabilities

AT&T Big Data Analytics Platform

Industry Reach / Operational Knowledge

大数据生产设备管理的案例 -Analytics is a key enabler in maximizing asset productivity and process efficiency

Process Integration

Optimize operations and maintenance

Enhance manufacturing and product quality

Asset Performance

Improve quality and reduce failures and outages

Optimize service and support

Source: IBM CIO Study, "The Essential CIO" Source: IBM Institute for Business Value and MIT Sloan Management Review, “Analytics: The New Path to Value”

Best-in-Class companies use the data they collect more effectively, and turn that data into

actionable intelligenceSource: Aberdeen Group. Asset Management: Using Analytics to Drive Predictive Maintenance. Mar 2013.

Best-in-Class companies leverage all technology enablers to enhance

outcomes83 percent of CIOs cited

analytics as the primary path to competitiveness

Organizations that lead in analytics outperform those that are just

beginning to adopt analytics by 3 times

3x

83%

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• 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

IBM Predictive Maintenance and Quality reduces operational costs, improves asset productivity and increases process efficiency

Combined with out-of-box models, dashboards, reports and source connectors

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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

•临近灾害预警检验•月降水预报检验•短期降水预报检验

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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）

大数据分析优化的技术让建立企业级的气象站成为可能

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

Geospatial Location data

Social MediaSearch, blogs, tweets, text

messages

Entities & Relationships

Persons of interest, targets, watch lists

Sensorsoptical, acoustic, thermal,

chemical, etc.

• Continuous ingest of relevant structured and unstructured data

• Holistic entity or activity-centric picture across multiple data sources and types of intelligence

ImagerySatellite, aerial,

cameraNewCapability

- 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

重大案件犯罪率降低了30% ，暴力犯罪降低了 15%

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

公共安全案例数据源

方案描述

方案结果

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亚洲卫生局减少了诊断错误

• 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 17

“ 超过 80 ％ 的医疗数据是医疗影像”

利用的功能：Hadoop 系统

图片： Boaz Yiftach

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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）。

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