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所在平台: Udemy |
课程主页: https://www.udemy.com/course/perform-common-query-tasks-in-power-bi-desktop/
课程评论：没有评论
课程名称：在 Power BI Desktop 中执行常见查询任务 课程概述：Power BI 是由微软开发的数据分析工具，用于可视化数据和发现有用的见解。在本课程中，您将学习如何在 Power BI Desktop 中使用查询编辑器。Power BI 有多个版本，包括 Power BI Desktop、Power BI 服务、Power BI 移动版和 Power BI 开发者版。其中，Power BI Desktop 是免费的版本，查询编辑器在所有三个版本中均可用。 Power BI Desktop 包含多个组件，能够进行数据转换、建模和可视化，并从数据中生成报告。Power BI 中的查询编辑器用于在数据实际加载到 Power BI 之前，编辑或转换数据文件。查询编辑器充当一个中间数据容器，您可以通过选择行和列、拆分行和列、透视和反透视列等方式来修改数据。查询编辑器的更改不会影响实际数据集。完成数据的预处理后，您可以将其加载到 Power BI 环境中。 Power Query 是一个数据转换和准备引擎，具有图形界面以从各类数据源获取数据，并提供 Power Query 编辑器来应用转换。由于该引擎可用于多种产品和服务，因此数据存储的位置取决于 Power Query 的使用场合。通过使用 Power Query，您可以执行数据的提取、转换和加载（ETL）处理。
Power BI is a data analytics tool developed by Microsoft used to visualize data and find useful insights. In this article, you will see how to work with the Query Editor in Power BI desktop. Power BI comes in various versions, i.e., Power BI Desktop, Power BI Service, Power BI Mobile, and Power BI Developer. Power BI desktop is the free version, and the query editor is available in all three versions.Power BI Desktop has several components to transform, model, and visualize data and also generate reports from data. The Query Editor in Power BI is used to transform or edit data files before they are actually loaded into the Power BI.The Query Editor plays the role of an intermediate data container where you can modify data by selecting rows and columns, splitting rows and columns, pivoting and unpivoting columns, etc. The changes made by the Query Editor in Power BI are not reflected in the actual dataset. Once you have pre-processed the data and have transformed it into the required format, you can load the data into the Power BI environment.Power Query is a data transformation and data preparation engine. Power Query comes with a graphical interface for getting data from sources and a Power Query Editor for applying transformations. Because the engine is available in many products and services, the destination where the data will be stored depends on where Power Query was used. Using Power Query, you can perform the extract, transform, and load (ETL) processing of data.
