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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/analytics-business-metrics
课程评论：没有评论
本课程名称为《数据驱动企业的商业指标》。在本课程中，您将学习最佳实践，如何利用数据分析使任何公司在竞争中更具优势并获得更高利润。您将能够识别最关键的商业指标，并将其与普通数据区分开来。 课程还将清楚地阐述商业分析师、商业数据分析师和数据科学家在不同类型公司中的重要但不同的角色，以及成功应聘和在这些高需求职位中的必要技能。 最后，课程提供的检查清单将帮助您评估一家企业在大数据文化接受度上的有效性。亚马逊、优步和爱彼迎等数字企业通过创新的数据使用正在改变整个行业。您将理解这些公司为何如此具有颠覆性，并学习它们如何利用数据分析技术来优于传统公司。 课程大纲包括： 1. 商业指标概述：探索关键商业指标，区分商业数据与指标，识别现金流、盈利能力等重要指标。 2. 商业数据分析市场：了解不同工作角色与数据的关系，识别必要技能，并通过检查清单评估公司的大数据文化。 3. 深入商业指标：研究网络营销的关键指标，特别是在金融服务行业中的应用。 4. 应用商业指标于案例研究：进行同伴评估，识别有趣的商业指标并提出相关的业务流程改进建议。 该课程结合实际案例，旨在为参与者提供在数据驱动的商业环境中获得成功的技能与知识。
Name:About This Specialization and Course
Description:This Coursera Specialization: Excel to MySQL: Analytic Techniques for Business, is about how 'Big Data' interacts with business, and how to use data analytics to create value for businesses. This specialization consists of four courses and a final Capstone Project, where you will apply your skills to real-world business process. You will learn to perform sophisticated data-analysis functions using powerful software tools such as Microsoft Excel, Tableau, and MySQL. To learn more, watch the video and review the specialization overview document we provided. In the first course of the specialization: Business Metrics for Data-Driven Companies, you will be able to learn best practices for using data analytics to make any company more competitive and more profitable; learn to recognize the most critical business metrics and distinguish those from mere data; understand the vital but different roles business analysts, business data analysts, and data scientists each play in various types of companies; and know exactly the skills required to be hired for, and succeed at, these high-demand jobs. Finally, using a 20-item checklist for evaluating a business, you'll be able to score any company on how effectively it is embracing big data culture. Digital companies like Amazon, Uber and Airbnb are transforming entire industries through their creative use of big data. You’ll understand why these companies are so disruptive, and how they use data-analytics techniques to out-compete traditional companies.To get started, please begin with the video 'About This Specialization.'I hope you enjoy this week's materials!
Name:Introducing Business Metrics
Description:Welcome! This week we will explore business metrics - the critical numbers that help companies figure out how to survive and thrive. Inside every pile of data is a vital metric trying to get out! By the end of this week, you will be able to: distinguish business metrics from mere business data; identify critical business metrics such as cash flow, profitability, and online retail marketing metrics; distinguish revenue, profitability and risk metrics; and distinguish traditional from dynamic metrics. Included in this week’s course materials is a Cash Flow and P&L statement for Egger’s Roast Coffee, as a supplemental document, so be sure to review it carefully and refer to the glossary for key information.
Name:Working in the Business Data Analytics Marketplace
Description:Welcome! This week, we will meet some great people - all former students of mine - now working at super-interesting and exciting jobs as business analysts, business data analysts, or data scientists. We’ll explore what they do, how their role relates to big data, and the skills they needed to get hired! Our hope is this information will give you a better understanding of the type of data-related job you might apply for once you've completed this specialization, and a sense of the type of company you would find most appealing to work for. By the end of this week, you will be able to: differentiate among different job roles within a company that work with data; identify how each role works with data; and describe the skills required to perform each job role. You will differentiate how different types of companies relate to big data culture, and rank any company according to a 20-item checklist. You will also learn to differentiate how different types of companies relate to big data culture. Included in this week’s materials is a 20-item checklist to rank companies. This week also includes in-video polls so you can see how others are ranking their businesses.
Name:Going Deeper into Business Metrics
Description:Welcome! This week we’re going to go deeper into the critically-important metrics for web marketing - metrics every type of business needs to understand in order to survive. We’ll dive into the 'vertical' market of financial services - where digital companies are threatening to take away the market from traditional 'brick-and- mortar' companies.By the end of this week, you will be able to: Identify critical business metrics for all companies engaged in web-based marketing; and identify critical business metrics for financial services companies. You’ll find additional website links that expand some of the course materials covered in this week’s video lectures.
Name:Applying Business Metrics to a Business Case Study
Description:This week contains the final course assignment, a peer assessment in which you will identify business metrics of interest in a case example, describe those metrics, and propose a business process change that could be supported by the metric chosen.
In this course, you will learn best practices for how to use data analytics to make any company more competitive and more profitable. You will be able to recognize the most critical business metrics and distinguish them from mere data. You’ll get a clear picture of the vital but different roles business analysts, business data analysts, and data scientists each play in various types of companies. And you’ll know exactly what skills are required to be hired for, and succeed at, these high-demand jobs. Finally, you will be able to use a checklist provided in the course to score any company on how effectively it is embracing big data culture. Digital companies like Amazon, Uber and Airbnb are transforming entire industries through their creative use of big data. You’ll understand why these companies are so disruptive and how they use data-analytics techniques to out-compete traditional companies.
