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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/big-data-management
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课程名称：大数据建模与管理系统 课程概述：在本课程中，您将学习在识别出需要分析的大数据问题后，如何使用大数据解决方案来收集、存储和组织数据。课程将体验各种数据类型和适合的管理工具，并探讨大数据管理系统和分析工具的演变原因。通过指导性实践教程，您将熟悉使用实时和半结构化数据的技术。讨论的系统和工具包括：AsterixDB、HP Vertica、Impala、Neo4j、Redis、SparkSQL。该课程提供从未被充分利用的数据源中提取价值的技术，并发现新的数据源。 课程目标： - 识别自身工作和日常生活问题中的不同数据元素 - 解释团队为何需要设计大数据基础设施计划和信息系统设计 - 识别各种数据类型所需的常见数据操作 - 根据数据特征选择适当的数据模型 - 应用处理流数据的技术 - 区分传统数据库管理系统与大数据管理系统 - 理解为何有如此多的数据管理系统 - 为在线游戏公司设计大数据信息系统 学习对象：本课程适合大数据科学初学者，建议先完成《大数据入门》课程。虽然不需要编程经验，但需具备安装应用程序和使用虚拟机的能力以完成实践作业。有关完整的硬件和软件规范，请参考专业领域的技术要求。 硬件要求： (A) 四核处理器（推荐支持VT-x或AMD-V），64位；(B) 8GB内存；(C) 20GB可用磁盘空间。 软件要求： 本课程依赖多种开源软件工具，包括Apache Hadoop。所有必需的软件可以免费下载安装（不包含互联网的流量费用）。软件要求包括：Windows 7+、Mac OS X 10.10+、Ubuntu 14.04+ 或 CentOS 6+、VirtualBox 5+。 课程大纲： 1. 大数据建模与管理介绍 - 理解大数据建模与管理的基本概念。 2. 大数据建模 - 掌握大数据建模的详细信息及实用技能。 3. 大数据建模（第二部分） - 深入学习向量空间模型、图数据模型等具体建模方法。 4. 处理数据模型 - 掌握流数据格式的处理技能，包括气象数据和Twitter推文。 5. 大数据管理：DBMS中的“M” - 了解大数据管理所需的不同数据库管理系统。 6. 为在线游戏设计大数据管理系统 - 针对虚构的在线游戏“抓住粉色火烈鸟”学习大数据建模与管理。
Name:Introduction to Big Data Modeling and Management
Description:Welcome to this course on big data modeling and management. Modeling and managing data is a central focus of all big data projects. In these lessons we introduce you to the concepts behind big data modeling and management and set the stage for the remainder of the course.
Name:Big Data Modeling
Description:Modeling big data depends on many factors including data structure, which operations may be performed on the data, and what constraints are placed on the models. In these lessons you will learn the details about big data modeling and you will gain the practical skills you will need for modeling your own big data projects.
Name:Big Data Modeling (Part 2)
Description:These lessons continue to shed light on big data modeling with specific approaches including vector space models, graph data models, and more.
Name:Working With Data Models
Description:Data models deal with many different types of data formats. Streaming data is becoming ubiquitous, and working with streaming data requires a different approach from working with static data. In these lessons you will gain practical hands-on experience working with different forms of streaming data including weather data and twitter feeds.
Name:Big Data Management: The "M" in DBMS
Description:Managing big data requires a different approach to database management systems because of the wide variation in data structure which does not lend itself to traditional DBMSs. There are many applications available to help with big data management. In these lessons we introduce you to some of these applications and provide insight into how and when they might be appropriate for your own big data management challenges.
Name:Designing a Big Data Management System for an Online Game
Description:In these lessons we give you the opportunity to learn about big data modeling and management using a fictitious online game called "Catch the Pink Flamingo".
Once you’ve identified a big data issue to analyze, how do you collect, store and organize your data using Big Data solutions? In this course, you will experience various data genres and management tools appropriate for each. You will be able to describe the reasons behind the evolving plethora of new big data platforms from the perspective of big data management systems and analytical tools. Through guided hands-on tutorials, you will become familiar with techniques using real-time and semi-structured data examples. Systems and tools discussed include: AsterixDB, HP Vertica, Impala, Neo4j, Redis, SparkSQL. This course provides techniques to extract value from existing untapped data sources and discovering new data sources. At the end of this course, you will be able to: * Recognize different data elements in your own work and in everyday life problems * Explain why your team needs to design a Big Data Infrastructure Plan and Information System Design * Identify the frequent data operations required for various types of data * Select a data model to suit the characteristics of your data * Apply techniques to handle streaming data * Differentiate between a traditional Database Management System and a Big Data Management System * Appreciate why there are so many data management systems * Design a big data information system for an online game company This course is for those new to data science. Completion of Intro to Big Data is recommended. No prior programming experience is needed, although the ability to install applications and utilize a virtual machine is necessary to complete the hands-on assignments. Refer to the specialization technical requirements for complete hardware and software specifications. Hardware Requirements: (A) Quad Core Processor (VT-x or AMD-V support recommended), 64-bit; (B) 8 GB RAM; (C) 20 GB disk free. How to find your hardware information: (Windows): Open System by clicking the Start button, right-clicking Computer, and then clicking Properties; (Mac): Open Overview by clicking on the Apple menu and clicking “About This Mac.” Most computers with 8 GB RAM purchased in the last 3 years will meet the minimum requirements.You will need a high speed internet connection because you will be downloading files up to 4 Gb in size. Software Requirements: This course relies on several open-source software tools, including Apache Hadoop. All required software can be downloaded and installed free of charge (except for data charges from your internet provider). Software requirements include: Windows 7+, Mac OS X 10.10+, Ubuntu 14.04+ or CentOS 6+ VirtualBox 5+.
