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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/business-analytics-executive-overview
课程评论：没有评论
课程名称：商业分析执行概述 课程概述：当今企业依赖数据，而数据在没有分析的情况下价值有限。通过分析数据来预测个人或市场行为、诊断系统或情境，以及为人们或流程提供行动建议的能力推动了商业的发展。越来越多的企业力求成为“数据驱动的”，即主动依赖信息和先进算法，而非直觉或缓慢反应。 本课程主要聚焦于理解关键的分析概念及其广泛的可能性。课堂上，我们将探索多个行业和商业职能中的真实分析问题及解决方案。课程还将涉及分析技术、架构及角色，包括商业智能、数据科学、数据仓库和数据湖。最后，我们将讨论分析趋势与未来。 课程大纲： 1. 课程概述与模块1：超越电子表格的分析 本模块将阐述从大数据到数据仓库，再到自然语言查询等关键数据和分析概念。我们将探讨各种分析技术、可视化类型和分析解决方案，并识别分析角色和组织结构，包括首席数据官、数据科学家及优秀分析中心等。还将讨论外包和众包等替代直接招聘的方法，并分析分析趋势与未来。 2. 模块2：行业和商业职能分析 本模块将演示各组织如何在类似的商业职能中相似地使用数据和分析。您将意识到，要真正成为数据驱动的企业，不仅要借鉴自己行业的实例，还要学习和应用其他领域组织的分析概念。 3. 模块3：分析的人员配备与组织 本模块将介绍一系列重要的分析角色和新兴角色，以及从C级职位到各种分析师角色的发展。您将了解职位描述和责任，并站在求职者或招聘者的角度，审视哪些技能最为重要，哪个职位最适合自己。例如，介绍数据科学家的三项核心技能以及成功数据科学家所需的软技能。 4. 模块4：今天和明天的分析成功 本模块探讨如何通过数据讲述情感故事，与受众产生共鸣。将回顾易于理解的示例和数据，使概念令人信服。您将学习创建数据可视化的主要注意事项和规则，以及如何清晰地展示发现。该模块特别关注Dona Wong的有效数据可视化和图表指南，最后将教授帮助您改善可视化的三项测试。在数据可视化执行的最后一步，您将学习McCandless方法，该五步过程能够高效地传达图形信息给受众。
Name:Course Overview & Module 1 Analytics Beyond the Spreadsheet
Description:This first module exposes and explains key data and analytics concepts from Big Data to data warehousing to natural language query, and everything in-between. Next we will explore various analytic techniques, types of visualizations, and types of analytics solutions. The course will continue with identifying and learning about key data and analytics roles and organization structures, including chief data and analytics officers, data scientists, and analytics centers of excellence. Alternatives to direct hiring, such as outsourcing and crowdsourcing, will also be covered. Finally, the course will scrutinize analytic trends and futures.
Name:Module 2 Industry and Business Function Analytics
Description:Over the course of the module, you will also see how data and analytics in each of these organizations can be used in similar ways, in similar business functions. Accordingly, you will appreciate that to be truly data-driven, you need not only look to examples in your own industry, but, also learn and apply analytics concepts from organizations in other fields.
Name:Module 3 Staffing and Organizing for Analytics
Description:In this module you will learn a bunch of crucial analytical roles and the emergence of new roles in organizations from the C-suite down to various analyst roles. You will take a brief look at the job descriptions and the responsibilities. You will also put yourself in either a job seeker’s or a recruiter’s shoes to see what kind of skill sets are the most important and which position fits you the best. For example, it will introduce you to the three core skills of the data scientist and the crucial soft skills required to be a successful data scientist.
Name:Module 4 Analytics Success Today and Tomorrow
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.
Businesses run on data, and data offers little value without analytics. The ability to process data to make predictions about the behavior of individuals or markets, to diagnose systems or situations, or to prescribe actions for people or processes drives business today. Increasingly many businesses are striving to become “data-driven”, proactively relying more on cold hard information and sophisticated algorithms than upon the gut instinct or slow reactions of humans. This course will focus on understanding key analytics concepts and the breadth of analytic possibilities. Together, the class will explore dozens of real-world analytics problems and solutions across most major industries and business functions. The course will also touch on analytic technologies, architectures, and roles from business intelligence to data science, and from data warehouses to data lakes. And the course will wrap up with a discussion of analytics trends and futures.
