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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/intro-business-analytics
课程评论：没有评论
课程名称：商业分析导论：与数据沟通 课程概述：本课程向学生介绍商业分析的科学，同时注重在数字领域中巧妙使用数字的方法。其目标是为企业和管理者提供应用数据分析解决日常专业挑战所需的基础。学生将学习识别适合自身需求的分析工具；理解有效和可靠的数据收集、分析及可视化方式；并在决策中利用数据为其机构、组织或客户提供支持。 课程大纲： 1. 课程导入与模块1：用大脑看到的图片 - 描述：本模块将帮助你打下成为优秀数据沟通者的基础。完成后，你将了解数据可视化的历史，掌握当今的数据可视化工具，建立与视觉效果的联系，并评估数据可视化的有效性。 2. 模块2：快速工作与慢思考 - 描述：此模块介绍访问数据的各种方法，数据可以是公开的或公司内部的。同时，模块还回顾了分析师为何要为分析定义明确的目标。你将了解指导数字营销分析的框架及其在数据可视化中的重要性。 3. 模块3：寻找你的数据故事 - 描述：在这一模块中，你将学习通过可视化发现数据中的模式的方法。你将看到图表如何用来传达概念或数据驱动的、声明性或探索性的信息，并学习使用不同的图表技术揭示数据模式。此外，我们还将探讨分析工具，RStudio是常用工具之一，我们会研究它的可视化能力。最后，我们将讨论一个框架，帮助分析师有效规划数据收集、分析与可视化。 4. 模块4：讲述你的故事 - 描述：本模块探索如何通过数据讲述与你的观众情感相连的故事，并回顾使概念易于理解的示例和图形。你将学习制作数据可视化的主要注意事项与禁忌以及清晰展示发现的规则。具体聚焦于Dona Wong的良好数据可视化和图表准则。在模块的最后，你将学习帮助改进可视化的三项测试以及McCandless方法，该五步流程可有效传达图形信息给你的观众。
Name:Course Introduction and Module 1: Pictures You See With Your Brain
Description:This module, will help you earn the foundation needed to become a good data communicator. After completion of this module, you will know the history of data visualizaiton, understand today’s dataviz tools, make connections with visuals, and evaluate the effectiveness of data visualizations.
Name:Module 2: Working Fast and Thinking Slow
Description:This module will walk you through various methods to access data. The data could be either publicly available or company internal. The module also reviews why it is important for analysts to define clear objectives for their analysis. You will also be introduced to frameworks that help guide digital marketing analysis and their importance to data visualization.
Name:Module 3: Finding Your Data Story
Description:In this module, you will learn an approach to finding patterns in data through visualization. You will see how charts can be used to communicate messages that can be conceptual or data driven and declarative or exploratory. Next, we will learn how to use different charting techniques to reveal data patterns. Visual aids play a major role in identifying ideas and, as a result, we will learn how to match the appropriate visual technique to the ideas we hope to expose. Next, we will explore analysis tools. RStudio is one of the most commonly used tools, and we will explore its visual capabilities. Finally, we will discuss a framework that will help analysts effectively plan for data collection, analysis, and, ultimately, visualization.
Name:Module 4: Getting Your Story Across
Description:This module explores telling stories, through data, that connect emotionally with your audience. It will also review examples and figures that make the concept easy to understand. You will learn the major do’s and don’ts of creating dataviz and rules that lead to the clear depiction of your findings. This unit specifically focuses on Dona Wong’s guidelines for good data visualization and charts. The last leg of Module 4 teaches the three tests that help you improve your visualization. In the final step of dataviz execution, you will learn the McCandless Method for presenting visualizations. This five-step process produces the most effective communication of the graphics to your audience.
This course introduces students to the science of business analytics while casting a keen eye toward the artful use of numbers found in the digital space. The goal is to provide businesses and managers with the foundation needed to apply data analytics to real-world challenges they confront daily in their professional lives. Students will learn to identify the ideal analytic tool for their specific needs; understand valid and reliable ways to collect, analyze, and visualize data; and utilize data in decision making for their agencies, organizations or clients.
