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所在平台: Udemy |
课程主页: https://www.udemy.com/course/big-data-hadoop-practice-test-t/
课程评论：没有评论
课程名称：大数据Hadoop实践测试 概述：大数据是指那些无法使用传统计算技术处理的大型数据集。它不仅仅是一种技术或工具，而是一个完整的学科，涉及多种工具、技术和框架。大数据包含大量、高速和可扩展的多样化数据，主要包括三种类型的数据：结构化数据（关系数据）、半结构化数据（XML数据）和非结构化数据（如Word、PDF、文本和媒体日志）。 大数据挑战：大数据涉及的主要挑战包括数据捕获、数据管理、存储、搜索、共享、传输、分析和展示。为了解决这些挑战，组织通常依靠企业服务器的支持。 大数据技术：大数据技术在提供更准确的分析方面至关重要，这有助于制定更有效的决策，从而提高运营效率、降低成本和减少商业风险。要有效利用大数据，需要具备能够管理和实时处理大量结构化和非结构化数据的基础设施，同时保障数据隐私和安全。目前市场上有多家供应商（如亚马逊、IBM、微软等）提供用于大数据处理的技术。 大数据技术主要可以分为两类： 1. 运营大数据：如MongoDB等系统，提供实时、交互性工作负载的运营能力，主要用于数据的捕获和存储。 2. NoSQL大数据系统：这些系统设计用于利用过去十年中出现的新云计算架构，以低成本和高效率进行大规模计算。它们使得运营大数据工作负载的管理变得更加简单、便宜和快速实施。有些NoSQL系统能够基于实时数据提供模式和趋势的洞察，且需要较少的编码，甚至不需要数据科学家和额外的基础设施。 此课程为有意了解和实操大数据技术的学员提供了理论与实践的结合，帮助学员掌握大数据分析的基本技能和技术。
Big data is a collection of large datasets that cannot be processed using traditional computing techniques. It is not a single technique or a tool, rather it has become a complete subject, which involves various tools, techniques and frameworks.Thus Big Data includes huge volume, high velocity, and extensible variety of data. The data in it will be of three types.Structured data − Relational data.Semi Structured data − XML data.Unstructured data − Word, PDF, Text, Media Logs.Big Data Challenges:The major challenges associated with big data are as follows −Capturing dataCurationStorageSearchingSharingTransferAnalysisPresentationTo fulfill the above challenges, organizations normally take the help of enterprise servers.Big Data Technologies:Big data technologies are important in providing more accurate analysis, which may lead to more concrete decision-making resulting in greater operational efficiencies, cost reductions, and reduced risks for the business.To harness the power of big data, you would require an infrastructure that can manage and process huge volumes of structured and unstructured data in realtime and can protect data privacy and security.There are various technologies in the market from different vendors including Amazon, IBM, Microsoft, etc., to handle big data. While looking into the technologies that handle big data, we examine the following two classes of technology.Operational Big Data:This include systems like MongoDB that provide operational capabilities for real-time, interactive workloads where data is primarily captured and stored.NoSQL Big Data systems are designed to take advantage of new cloud computing architectures that have emerged over the past decade to allow massive computations to be run inexpensively and efficiently. This makes operational big data workloads much easier to manage, cheaper, and faster to implement.Some NoSQL systems can provide insights into patterns and trends based on real-time data with minimal coding and without the need for data scientists and additional infrastructure.
