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所在平台: Udemy |
课程主页: https://www.udemy.com/course/sql-data-exploration-for-beginner-data-analyst/
课程评论：没有评论
课程名称：初学者数据分析师的SQL数据探索 课程概述：SQL（结构化查询语言）是访问和操作数据库的强大工具。通过SQL，用户可以执行数据库查询，检索数据，插入、更新和删除记录，创建新的数据库和表，定义存储过程和视图，并设置表、程序和视图的权限。数据探索是数据分析的第一步，在这个阶段，用户以非结构化的方式探索大型数据集，以发现初步的模式、特征和关注点。数据探索并不旨在揭示数据集中所有信息，而是帮助建立重要趋势的总体视图，并识别需要深入研究的主要点。 探索性数据分析（EDA）是数据分析过程的起点。在这一阶段，您需要理解现有数据，并确定要提出的问题和框架，以及如何最佳地操纵可用数据源以获取所需答案。通过观察数据中的模式、趋势、异常值和意外结果，结合视觉和定量方法，您将识别数据所讲述的故事，从而寻求线索，指引您的下一步动作、问题或研究领域。 这门课程旨在帮助初学者掌握SQL基础知识，并在数据分析过程中有效应用探索性数据分析的技能。
SQL stands for Structured Query Language. SQL lets you access and manipulate databasesSQL can execute queries against a databaseSQL can retrieve data from a databaseSQL can insert records in a databaseSQL can update records in a databaseSQL can delete records from a databaseSQL can create new databasesSQL can create new tables in a databaseSQL can create stored procedures in a databaseSQL can create views in a databaseSQL can set permissions on tables, procedures, and viewsData exploration is the initial step in data analysis, where users explore a large data set in an unstructured way to uncover initial patterns, characteristics, and points of interest. This process isn't meant to reveal every bit of information a dataset holds, but rather to help create a broad picture of important trends and major points to study in greater detail. Data exploration can use a combination of manual methods and automated tools such as data visualizations, charts, and initial reports.Exploratory Data Analysis (EDA) is the first step in your data analysis process. Here, you make sense of the data you have and then figure out what questions you want to ask and how to frame them, as well as how best to manipulate your available data sources to get the answers you need. You do this by taking a broad look at patterns, trends, outliers, unexpected results and so on in your existing data, using visual and quantitative methods to get a sense of the story this tells. You're looking for clues that suggest your logical next steps, questions or areas of research.
