论数据湖技术及其应用
近年来，随着移动互联网、物联网、工业互联网等技术的不断发展，企业级应用面临的数据规模不断增大，数据类型异常复杂。针对这 一 问题，业界提出“数据湖（Data Lake） ”这一新型的企业数据管理技术。数据湖是一个存储企业各种原始数据的大型仓库， 支持对任意规模的结构化、半结构化和非结构化数据进行集中式存储，数据按照原有结构进行存储，无须进行结构化处理；数据湖中的数据可供存取、处理、分析及传输，支撑大数据处理 、实时分析、机器学习、数据可视化等多种应用，最终支持企业的智能决策过程。
请围绕“数据湖技术及其应用”论题，依次从以下三个方面进行论述。
1.概要叙述你所参与管理或开发的软件项目，以及你在其中所承担的主要工作。
2. 详细阐述数据湖技术，并从主要数据来源、数据模式 (（Schema )）转换时机、数据存储成本、数据质量、面对用户和主要支撑应用类型等5个方面详细论述数据湖技术与数据仓库技术的差异。
3.详细说明你所参与的软件开发项目中，如何采用数据湖技术进行企业数据管理，并说明具体实施过程以及应用效果 。
正确答案及解析
正确答案
解析
一、应结合自己参与的信息系统项目，说明在其中所承担的工作。
二、数据仓库是一个优化的数据库，用于分析来自事务系统和业务线应用程序的关系数据。数据仓库技术需要事先定义数据结构和数据模式（Schema）以优化快速SQL查询 ，其中结果通常用于操作报告和分析。数据经过了清理、丰富和转换，因此可以充当用户可信任的“单一信息源”。与数据仓库不同，数据湖能够同时存储来自业务线应用程序的关系数据，以及来自移动应用程序、物联网设备和社交媒体的非关系数据 。在进行数据捕获时，无须定义数据结构或数据模式（Schema）。数据湖支持用户对数据使用不同类型的分析（如 SQL 查询、大数据分析、全文搜索、实时分析和机器学习等），为企业智能决策提供支撑。
下面从主要数据来源、数据模式转换时机、数据存储成本、数据质量、面对用户和主要支撑应用类型等六个方面对数据湖技术和数据仓库技术进行比较：
三、第三个问题要根据项目的实际情况来写自己是怎么做的，指出其参与管理和开发的项目是如何采用数据湖技术进行数据管理的，详细说明所采用的数据湖架构、主要的数据来源和质量、 数据模式转换方式和时机、数据存储基础设施、系统主要用户和支撑的上层应用等，同时文章收尾要对效果进行评价。
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