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所在平台: Udemy |
课程主页: https://www.udemy.com/course/data-exploration-visualization-with-databases-and-power-bi/
课程评论：没有评论
**课程名称：** 使用数据库和 Power BI 进行数据探索与可视化 **课程概述：** 本课程是数据分析流程的起点，旨在教授学员如何通过探索大型数据集来发现初步的模式、特征和重点。通过结合手动方法和自动化工具（如数据可视化、图表和初步报告），学员可以构建对重要趋势和主要研究点的宏观认识。 课程内容将涵盖以下核心概念： * **探索性数据分析 (EDA)：** 理解数据的含义，提出关键问题，并确定最佳数据处理方法以获取所需答案。通过视觉和定量方法审视数据中的模式、趋势、异常值和意外结果，为后续研究指明方向。 * **数据分析：** 学习检查、清洗、转换和建模数据的过程，以发现有用的信息、得出结论并支持决策。 * **数据可视化：** 掌握以图形化方式呈现数据的方法，使决策者能够直观地理解分析结果，掌握复杂概念或识别新模式。 **实践内容：** 学员将学习如何连接到 **Microsoft SQL Server** 和 **PostgreSQL** 作为数据源，在创建可视化之前对数据库数据进行深入探索。 **目标：** 学完本课程后，学员将能够有效地进行数据探索，利用数据库和 Power BI 创造有意义的数据可视化，从而更好地理解数据并支持数据驱动的决策。
Data 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.Data analysis is a process of inspecting, cleansing, transforming, and modelling data with the goal of discovering useful information, informing conclusions, and supporting decision-making.Data visualization is the presentation of data in a pictorial or graphical format. It enables decision makers to see analytics presented visually, so they can grasp difficult concepts or identify new patterns.We will connect to Microsoft SQL Server and PostgreSQL as our data sources then explore the database data before creating visualizations.
