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所在平台: Udemy |
课程主页: https://www.udemy.com/course/power-bi-desktop-combo-query-editor-dax-data-modelling-relationship/
课程评论:没有评论
本课程专注于 Microsoft Power BI Desktop 中的核心商业智能功能,包括 Power Query 编辑器、数据建模和 DAX(数据分析表达式)。 **Power BI Desktop** 是微软提供的一套商业智能工具,旨在帮助商业智能专业人士从数据中获取轻松、快速且关键的业务洞察。它整合了三个主要工具:Power Query、Power Pivot 和 Power View。 **Power Query 编辑器**(也称为 Power BI Query Editor)允许用户连接到数百种数据源,简化数据准备过程,并进行临时分析。其主要功能包括: * **数据发现**:查找和连接各种来源的数据,包括企业数据库、文件、社交媒体和大数据。 * **数据加载**:选择已检查的数据并将其加载到 Power Query 中进行处理。 * **数据修改**:变形导入的每个数据表结构,筛选和清洗数据,并将不同的数据源合并。 * **数据清洗**:确保数据的可靠性和易用性。 通过 Power Query,用户可以“混搭”自己的数据,使其符合要求,并为自助式 BI 解决方案做好准备。这个过程在数据仓储领域被称为 ETL(Extract Transform Load),即**提取、转换、加载**。 **Power Pivot** 是 Power BI 中的分析工具。在 Power BI Query Editor 中导入数据后,用户可以使用各种 **DAX 公式**来驱动分析。 课程将涵盖 Power BI Query Editor 的详细用法、数据建模技巧以及 DAX 函数的应用,并提供实用的开发技巧和指导,以增强现有的 Power BI 项目。课程还将从 Power BI Desktop 的基本安装和配置开始,指导用户连接数据源,转换和准备数据以供分析,并创建有效的数据视图。 总而言之,本课程旨在赋能学习者,让他们能够熟练运用 Power BI Desktop 的数据准备、建模和分析功能,从而更有效地从数据中提取有价值的业务洞察。
Microsoft Power BI is a suite of Business Intelligence tools, designed to help the BI professionals get easier, quick and crucial business insights from their data. It contains three main tool-set combined in one single software:Power QueryPower PivotPower ViewPower Query lets you to connect to hundreds of data sources, simplify data preparation and drive ad-hoc analysis. It is also know as Power BI Query Editor.Power Pivot is the analytical tool in Power BI. Using various DAX formulas you can drive your analytical journey. This is the second step after you import the data into Power BI using Power BI Query Editor.This course will focus completely on features for Power BI Query Editor, Date Modelling and DAX inside Power BI Desktop.Before you can present any analysis or insight, you need source data. Your source data could be in many places and in many formats. Nonetheless, you need to access it, look at it, and quite possibly clean it up to some extent. You may also need to join separate data sources before you can shape the data into a coherent data set using PowerPivot, deliver the results using Power View or Power Map, and then share it using Power BI.Discovering, loading, cleaning, and modifying source data is where Power BI Query editor comes in. It lets you load, shape and streamline data from multiple sources.Power BI Query Editor allows you to do many things with source data, but the four main steps are likely to be Import data from a wide variety of sources. This covers corporate databases to files, and social media to big data.Merge data from multiple sources into a coherent structure.Shape data into the columns and records that suit your uses.Cleanse your data to make it reliable and easy to use.There was a time when these processes required dedicated teams of IT specialists. Well, not any more. With Power Query, you can mash up your own data so that it is the way you want it and is ready to use as part of your self-service BI solution.This course will start with the basic installation and configuration of Power BI Desktop, and go on to connect your data sources with it. You'll transform and get your data ready for analysis, and create effective data views using it. You would be performing following tasks mainlyData Discovery -Find and connect to a myriad of data sources containing potentially useful data. This can be from both public and private data sources.Data Loading -Select the data you have examined and load it into Power Query for shaping.Data Modification -Modify the structure of each data table that you have imported, filter and clean the data itself, and then join any separate data sources.Although I have outlined these three steps as if they are completely separate and sequential, the reality is that they often blend into a single process. Indeed there could be many occasions when you will examine the data after it has been loaded into Power Query-or join data tables before you clean them. The core objective will, however, always remain the same: find some data and then load it into Power Query where you can tweak, clean, and shape it.This process could be described simplistically as "First, catch your data." In the world of data warehousing, the specialists call it ETL, which is short for Extract Transform Load. Despite the reassuring confidence that the acronym brings, this process is rarely a smooth logical progression through a clear-cut series of processes. The reality is often far messier than that. You may often find yourself importing some data, cleaning it, importing some more data from another source, combining the second data set with the first one, cleaning some more, and then repeating many of these operations several times.This course will excite and empower you to get more out of Power BI Query Editor via detailed recipes, development tips and guidance on enhancing existing Power BI Projects.