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2012 Strata+Hadoop World演讲资料整理
Strata大会探讨了大数据、数据科学以及计算机给整个技术和商业带来的各种变化。作为第四届Hadoop World大会，本次大会深入到了大数据行业。 Strata Conference+Hadoop World 为决策者提供了大数据的强大之处，推动着商业的发展，帮助业务人员特别是在金融、媒体和政府领域收集、分析和处理数据。Strata和Hadoop World的合并成为了Apache Hadoop社区最大的合并，它强调了Hadoop生态系统中的动手能力和商业利益。
Hadoop这一备受瞩目的技术随着大数据的发展愈发火爆起来，许多厂商以拥有Hadoop或类似技术进入大数据领域。在刚刚举办的Strata+Hadoop World大会上，这些厂商就发布了各自的大数据产品，并且大多与Hadoop密切相关。
| 序号 | 英文标题 | 中文标题 | 下载链接 |
| 1 | How to See Data | 洞察数据（数据的魅力，数据的艺术） |  |
| 2 | Facebooks Large Scale Monitoring System Built on HBase | Facebook基于HBase的大规模监控系统 | |
| 3 | Every Visualization You Have Seen is Worthless | 眼见为实 | |
| 4 | Designing for Data-driven Organizations | 如何服务数据为核心的企业 | |
| 5 | Designing Data Visualizations Workshop | 如何设计数据虚拟化仓库 | |
| 6 | What Business People Need to Know About Data Governance | 业务人员在数据治理方面需要知道的事情 | |
| 7 | Visualization – An Emerging Collaboration Opportunity | 可视化——新兴的合作机遇 | |
| 8 | Using HBase | 使用HBase | |
| 9 | Using Data to Tune A Software Team | 使用数据来管理软件团队 | |
| 10 | Trecul : Data Flow Processing Using LLVM-based JIT Compilation on Top of Hadoop | 数据流处理 | |
| 11 | The Death of the Enterprise Data Warehouse Presentation | 企业级数据仓库：穷途末路 | |
| 12 | Stuck in the Eighties: Why Marketers Still Don't Get Big Data | 数据营销时代为何迟迟不来 | |
| 13 | Start Small Before Going Big | 数据由小变大 | |
| 14 | Search and Real-time Analytics on Big Data | 大数据的搜索与实时更新 | |
| 15 | Revolution or Evolution | 改革还是变革？ | |
| 16 | Realtime Processing with Storm | Storm的实时处理 | |
| 17 | Performing Data Science with HBase | HBase实现数据科学 | |
| 18 | Data Science with Hadoop at Opower | Opower Hadoop的数据科学 | |
| 19 | Crunching Big Data with R and Hadoop | 使用R和Hadoop来分析大数据 | |
| 20 | Communicating Data Clearly | 清晰的交流数据 | |
| 21 | Commercial Graph_ A Map of Financial Relationships | 商业关系图 | |
| 22 | Combining the Power of Hadoop MapReduce with Object-based Dispersed Storage | 运用Hadoop MapReduce与基于对象的Dispersed存储技术 | |
| 23 | What_s a Customer Worth | 什么是客户价值 | |
| 24 | Building Rich, High Performance Tools for Practical Data Analysis | 为实际数据分析部署丰富的高性能工具 | |
| 25 | Building a Large-scale Data Collection System Using Flume NG | 使用Flum NG来部署大规模数据集合系统 | |
| 26 | Bringing the 'So What' to Big Data | 大数据漫谈 | |
| 27 | Big Data Direct – The Era of Self-driven Big Data Exploration | 自我挖掘的大数据时代 | |
| 28 | Beyond Hadoop_ Fast Ad-Hoc Queries on Big Data | Hadoop快速查询 | |
| 29 | Best Practices for Reproducible Research | 数字金融可重复性研究的最佳实践 | |
| 30 | Best Practices for Building and Deploying Predictive Models over Big Data | 构建和部署基于大数据的数字模型的最佳实践 | |
| 31 | Hadoop, HBase, and Healthcare | Hadoop、HBase和医疗 | |
| 32 | GraphBuilder – Scalable Graph Construction using Hadoop | GraphBuilder：使用Hadoop可扩展的图表建设 | |
| 33 | Helping the Worlds Farmers Adapt to Climate Change | 帮助世界的农民适应气候的变化 | |
| 34 | How a Traditional Media Company Embraced Big Data | 传统的媒体公司如何拥抱大数据 | |
| 35 | How Much Privacy Can We Really Expect | 隐私的保密性：何去何从 | |
| 36 | How To Plan a Successful Big Data Pilot | 大数据成功之路 | |
| 37 | Linking Census and Enterprise Data Sets | 企业数据集 | |
| 38 | Making Major League Data Work_ Carving Up Big Data into Useful Application | 大数据联盟：大数据转化为有价值的应用程序 | |
| 39 | Making Pig Fly_ Optimizing Data Processing on Hadoop | 优化Hadoop的数据处理 | |
| 40 | Moneyballing Criminal Justice_ Using Data to Reduce Crime | 使用数据来减低犯罪率 | |
| 41 | Moving to Big Data_ Strategies and Tactics for Setting Your Organization | 为企业实现大数据战略 | |
| 42 | Netflix_s Evolving Data Science Architecture | 数据科学架构的进化 | |
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