Summary and Highlights: Introduction to Big Data摘要和重点：大数据导论

In this lesson, you learned that:
在本课程中，你学习了：

• Personal assistants like Siri, Alexa, and Google Now use Big Data and IoT to gather data and devise answers.
  像 Siri、Alexa 和 Google Now 这样的个人助理使用大数据和物联网来收集数据并制定答案。
• Big Data Analytics helps companies gain insights from the data collected by IoT devices.
  大数据分析帮助公司从物联网设备收集的数据中获得洞察。
• Big Data requires parallel processing on account of massive volumes of data that are too large to fit on any one computer.
  大数据需要并行处理，因为其数据量巨大，无法存储在任何一台计算机上。
• “Embarrassingly parallel” calculations are the kinds of workloads that can easily be divided and run independently of one another. If any single process fails, that process has no impact on the other processes and can simply be re-run.
  “令人尴尬的并行”计算是那些可以轻松划分并独立运行的工作负载。如果任何一个进程失败，该进程不会对其他进程产生影响，只需重新运行即可。
• Open-source projects, which are free and completely transparent, run the world of Big Data and include the Hadoop project and big data tools like Apache Hive and Apache Spark.
  开源项目，免费且完全透明，运行着大数据的世界，包括 Hadoop 项目以及 Apache Hive 和 Apache Spark 等大数据工具。
• The Big Data tool ecosystem includes the following six main tooling categories: data technologies, analytics and visualization, business intelligence, cloud providers, NoSQL databases, and programming tools.
  大数据工具生态系统包括以下六个主要工具类别：数据技术、分析和可视化、商业智能、云服务提供商、NoSQL 数据库和编程工具。