Big Data Modeling and Management Systems

开始时间: 04/22/2022 持续时间: Unknown

所在平台: CourseraArchive

课程类别: 计算机科学

大学或机构: CourseraNew

课程主页: https://www.coursera.org/archive/big-data-management

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课程详情

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+.

大数据建模和管理系统:确定了要分析的大数据问题后,如何使用大数据解决方案收集,存储和组织数据?在本课程中,您将体验适用于每一种的各种数据类型和管理工具。您将能够从大数据管理系统和分析工具的角度描述大量新的大数据平台背后的原因。通过有指导性的动手教程,您将熟悉使用实时和半结构化数据示例的技术。讨论的系统和工具包括:AsterixDB,HP Vertica,Impala,Neo4j,Redis,SparkSQL。本课程提供了从现有未开发数据源中提取价值并发现新数据源的技术。 在本课程结束时,您将能够:  *识别您自己的工作和日常生活中的不同数据元素  *说明您的团队为何需要设计大数据基础架构计划和信息系统设计  *确定各种数据类型所需的频繁数据操作  *选择适合您数据特征的数据模型  *应用技术处理流数据  *区分传统的数据库管理系统和大数据管理系统  *理解为什么会有这么多的数据管理系统  *为在线游戏公司设计大数据信息系统 本课程适用于数据科学新手。建议完成大数据入门。尽管需要具备安装应用程序和使用虚拟机的能力来完成动手分配,但不需要任何先验编程经验。有关完整的硬件和软件规格,请参阅专业化技术要求。 硬件要求: (A)四核处理器(建议支持VT-x或AMD-V),64位; (B)8 GB RAM; (C)20 GB可用磁盘。如何查找您的硬件信息:(Windows):通过单击“开始”按钮,右键单击“计算机”,然后单击“属性”,打开“系统”。 (Mac):通过单击Apple菜单,然后单击“关于本机”,打开“概述”。在过去3年中购买的大多数具有8 GB RAM的计算机都将满足最低要求。您将需要高速Internet连接。下载最大4 Gb的文件。 软件要求: 本课程依赖于几种开源软件工具,包括Apache Hadoop。可以免费下载和安装所有必需的软件(互联网提供商的数据费用除外)。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

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.

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课程简介

Once you’ve identified a big data issue to analyze, how do you collect, store and organize your data

课程标签

大数据 大数据模型 大数据管理 大数据公开课 大数据模型和管理系统 大数据专项课程 加州大学圣地亚哥分校 大数据课程 大数据建模 大数据建模和管理系统

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