将数据化作价值签名认证

将数据化作价值

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将数据化作价值

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开始时间:2017-04-17

持续时间:4.0周/每周3.0-5.0小时

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课程

初级专项课程。 无需相关经验。

第 1 门课程
数据驱动型公司的业务指标
当前班次:Apr 17 — May 22。
课程学习时间
该课程为 4 周长 估计需要每周学习 3-5 个小时


课程概述
在该课程中 您将学习使用数据分析使公司更好的盈利且更具竞争力的最佳实践 您将能够识别最关键的业务指标 并将其与单纯的数据区分开来 你将会对至关重要但不同角色的业务分析师 业务数据分析师和数据科学家在不同公司的角色扮演有个清晰的概念 并且 将了解这些高需求的职位被雇佣和成功所需要的技能 最后 您将能够使用该课程提供的一个清单 对每个公司如何有效地接受大数据文化给予评分 像亚马逊(Amazon)优步(Uber)和空中食宿(Airbnb)等数码公司正在通过创造性地利用大数据转换整个行业 你将了解为何这些公司如此具有破坏性 他们如何使用数据分析方法超越传统公司


第 1 周
About This Specialization and Course
The 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;
  • 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
  • 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 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!

视频 · About This Specialization

阅读材料 · Specialization Overview


视频 · Introduction

阅读材料 · Course Overview

阅读材料 · FAQ

阅读材料 · Course Glossary

阅读材料 · About the Course Team

阅读材料 · Feedback Survey Information



Introducing Business Metrics
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. You will also complete a graded quiz. As always, if you have any questions, post them to the Discussions. To get started, please begin with the video 'Metrics Help Us Ask the Right Questions.' I hope you enjoy this week's materials!

视频 · Metrics Help Us Ask the Right Questions

视频 · Distinguishing Revenue, Profitability, and Risk Metrics

视频 · Distinguishing Traditional and Dynamic Metrics


阅读材料 · Egger's Roast Coffee Cash Flow and P&L Statements

视频 · Egger’s Roast Coffee Case Study Part 1 – Definitions

视频 · Egger’s Roast Coffee Case Study Part 2 – How a Profitable, Growing Company can go Bankrupt


视频 · Revenue Metrics – Traditional Enterprise Sales Funnel

视频 · Revenue Metrics - Amazon.com as a Leading Example of Use of Dynamic Metrics - Part 1

视频 · Revenue Metrics - Amazon.com as a Leading Example of Use of Dynamic Metrics - Part 2

视频 · Profitability/Efficiency Metrics: Inventory Management

视频 · Profitability/Efficiency Metrics: Hotel Room Occupancy Optimization

视频 · Risk Metrics: Leverage and Reputational Risk


测验 · Business Metrics

阅读材料 · Feedback Survey



第 2 周
Working in the Business Data Analytics Marketplace
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. Remember to refer back to the glossary as a supplemental document, and to review it carefully. You will also complete a graded quiz. As always, if you have any questions, post them to the Discussions. To get started, please begin with the video Roles and Companies as They Relate to Big Data.

视频 · Roles and Companies as They Relate to Big Data

视频 · The Business Analyst

视频 · An Interview with Business Analyst Shambhavi Vashishtha

视频 · Distinguishing the Business Data Analyst and Business Analyst Roles

视频 · An Interview with Business Data Analyst Tiffany Yu

阅读材料 · Summary of Job Requirements for Data-Centric Roles


视频 · The Data Scientist

视频 · An Interview with Data Scientist Dai Li

视频 · The Senior Software Engineer


视频 · Overview of 5 Types of Companies as they relate to Big Data

视频 · Traditional Strategic Business Consulting

视频 · Bricks-and-Mortar Companies

视频 · Barnes and Noble Case Study

阅读材料 · 20-Item Checklist for Evaluating A Business


视频 · Strategic Business Consulting - Focus on Software/IT Systems Integration

视频 · Hardware and Software Companies

视频 · Digital Companies


测验 · Working in the Business Data Analytics Marketplace

阅读材料 · Feedback Survey



第 3 周
Going Deeper into Business Metrics
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. Remember to refer back to the glossary as a supplemental document, and to review it carefully.You will also complete a graded quiz. Looking ahead, next week you’ll work on a final course assignment, a peer assessment applying business metrics to a business case study. As always, if you have any questions, post them to theDiscussions. To get started, please begin with the video 'Web Marketing: Metrics.' I hope you enjoy this week's materials!

视频 · Web Marketing: Metrics

视频 · Web Marketing: AdWords

视频 · Web Marketing: Segmentation

阅读材料 · Links Cited In AdWords Video


视频 · Introduction To Return Measures

视频 · The Sharpe Ratio

视频 · Passive and Active Equity Managers

视频 · Venture Capital Investors and Hedge Funds


测验 · Going Deeper into Business Metrics

阅读材料 · Feedback Survey



第 4 周
Applying Business Metrics to a Business Case Study
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. This final peer review assignment will allow you to review, and to provide feedback to your classmates. Don’t forget to consult the course glossary to help you with the peer assessment. If you have questions on the peer assessment, please post them to the discussions. We anticipate the peer assessment will take you no more than 3-5 hours, including writing your own assignment and reviewing your peers (but not including any review you may need to do as you work on your assignment). Looking ahead, once you’ve completed the peer assessment and the course, we hope you’ll join us in the next course offered in the specialization:Mastering Data Analysis in Excel, where you will master the Microsoft Excel techniques successful business analysts and business data analysts rely on every day to extract actionable information from business data. Starting with basic Excel functions (it’s ok if you’ve never used Excel before), you will import and work with real world data sets, display your results in charts and graphs, then solve more advanced problems using Excel’s built-in data functions and the Solver plugin. Along the way, you will learn the essential data modeling and predictive analytics concepts that will give you the power to ask the right questions of data and extract the most useful answers.As always, if you have questions about the peer assessment, please post them in the discussion forum. We look forward to your active engagement in the course community! Once you’ve completed the peer assessment, share your feedback on the course by completing the Feedback Survey.

同学互评 · Articulating Business Metrics in a Business Case Study

阅读材料 · Feedback survey




不显示详细信息


第 2 门课程
Mastering Data Analysis in Excel
当前班次:Apr 17 — Jun 5。
课程学习时间
6 weeks, 3 - 5 hours per week


课程概述
In business, data and algorithms create economic value when they reduce uncertainty about financially important outcomes. This course teaches the concepts and mathematical methods behind the most powerful and universal metrics used by Data Scientists to evaluate the uncertainty-reduction – or information gain - predictive models provide. We focus on the two most common types of predictive model - binary classification and linear regression - and you will learn metrics to quantify for yourself the exact reduction in uncertainty each can offer. These metrics are applicable to any form of model that uses new information to improve predictions cast in the form of a known probability distribution – the standard way of representing forecasts in data science. In addition, you will learn proper methodology to avoid common data-analytic pitfalls when forecasting – such as being “fooled by randomness” and over-fitting “noise” as if it were “signal.” Uniquely among data-analytics offerings, this course empowers you to understand and apply quite advanced information theory methods – Bayesian Logical Data Analysis - in business practice, without needing any calculus or matrix algebra, or any knowledge of Matlab or R or software programming. You will be able to answer all homework and quiz questions either by using basic algebra, or with the special custom Microsoft Excel Templates provided. Nor is any prior experience with Excel required; we will cover in detail at the beginning everything you need to know about using Excel to succeed in the course itself. If you already know Excel, you can skip that part. Be aware that this is not a broad general Excel skills course; it focuses on use of Excel to calculate information-related metrics, and to solve real business problems, such as developing your own predictive analytics model for which credit card applicants a bank should accept and which reject as too risky. Real problems are complicated! Personally I think learning to solve real problems is also a great way to learn Excel. We use specific tools in the Excel toolbox to build something useful, and you can always go back and learn more tools in the toolbox – more Excel functions – if and when you ever need them. This course requires some mathematical background: you should already know how to solve for an unknown using algebra; and have a basic familiarity with sigma (summation) notation; the concept of logarithms and working with bases other than base 10 (including base 2, and the natural logarithm and base “e”); and probability theory concepts such as calculating conditional, product, and joint probabilities. These concepts are assumed in the course rather than taught. All the “new” math taught in the course is summarized in a downloadable PDF document - "Mathematical Supplement" – please refer to it to decide if the difficulty level of this course seems right for you.


第 1 周
About this Specialization and Course
The 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.The second course of the specialization: Mastering Data Analysis in Excel, is organized around a few big ideas: real-world businesses always decide what actions to take under conditions of partial uncertainty; data analysts seek to reduce uncertainty for decision-makers; finally, data analysts can and should quantify for decision-makers both how much can be learned from available data and how much uncertainty remains. In this second course of the specialization, you will be introduced to the realistic Credit Card Business Case Study that will track the key learning points in the course; analyze both historical credit card customer default data, and customer profit and loss data; learn to design two different predictive models (in essence, one that minimizes risk, and an alternative that maximizes profits); and make recommendations to decision-makers about which model should be used for future applicants and why.

视频 · About This Specialization

阅读材料 · Specialization Overview


阅读材料 · Course Overview

视频 · Introduction to Mastering Data Analysis in Excel

阅读材料 · Final Course Project

阅读材料 · About the Course Team

阅读材料 · Feedback Survey Information


阅读材料 · FAQ (Frequently Asked Questions)

阅读材料 · Mathematical Supplement

阅读材料 · Glossary from Course 1



Excel Essentials for Beginners
Welcome! This week we will explore the essential Excel skills to address typical business situations you may encounter in the future. Working side by side with the lesson videos using Excel templates, you will develop the Excel skills needed to complete the Week 1 graded quiz and the Credit Card Business Case Study (Final Course Project). The Excel vocabulary and functions taught this week make it possible for you to understand the additional explanatory Excel spreadsheets that accompany later videos in this course, and are used to demonstrate and practice key course formulas and methods. Important note: Learners who already have intermediate Excel skills may skip over this module (by not watching the videos) but must still pass the Week 1 graded quiz. Before you attempt the quiz, we recommend you review the list of required Excel skills presented in the video below (Introduction to Using Excel in this Course), and make sure you can pass the ungraded practice quiz.

视频 · Introduction to Using Excel in this Course

阅读材料 · Excel Workbooks for Excel Essentials for Beginners

视频 · Basic Excel Vocabulary; Intro to Charting

视频 · Arithmetic in Excel

视频 · Functions on Individual Cells


视频 · Functions on a Set of Numbers

视频 · Functions on Ordered Pairs of Data

视频 · Sorting Data in Excel

视频 · Introduction to the Solver Plug-in

练习测验 · Week 1 Practice Quiz

测验 · Week 1 Graded Quiz

阅读材料 · Hints and Help for Quiz 1

阅读材料 · Feedback Survey



第 2 周
Binary Classification
Welcome! This week we will focus on models that divide data into two groups - Binary Classification. You will get a deep understanding of the quantitative metrics by which binary classification models are evaluated, and how the best model for a certain purpose is generally chosen. You will start to appreciate the different business situations that call for optimizing which classification metrics. The Credit Card Business Case Study (Final Course Project) gives you an opportunity to experiment with combining relevant input variables into a credit card default risk score in various ways. You will then rank-order historical outcomes based on their scoring method, and optimize their method so as to maximize two different but equally critical binary classification metrics – the area under the ROC curve (AUC), and the model’s cost per event.

阅读材料 · Excel Workbook for Binary Classification

视频 · Introduction to Binary Classification

视频 · Bombers and Seagulls: Confusion Matrix

视频 · Costs Determine Threshold

视频 · Bombers and Seagulls: Excel Application

视频 · Calculating Positive and Negative Predictive Values

视频 · Binary Classification with More than One Input Variable

练习测验 · Week 2 Practice Quiz

测验 · Week 2 Graded Quiz

阅读材料 · Feedback Survey



第 3 周
Information Measures
Welcome! Business situations requiring decision-making under uncertainty are best characterized as probabilistic. This week we will learn about the vitally useful Information metric known as “entropy.” In contrast to the more familiar “probability” that represents the uncertainty that a single outcome will occur, “entropy” quantifies the aggregate uncertainty of a full probability distribution of possible outcomes. Entropy measures, combined with Bayes’ theorem, allow businesses to quantify exactly how much information they can extract from certain data, and how much uncertainty remains. Information measures provide the framework for accountability in data-analytic work. In the Credit Card Business Case Study (Final Course Project), you will re-characterize their own binary classification models for default. An effective model offers customized probabilities of default/no default based on each applicant’s different data. These probabilities informed by data, taken as a whole, have less uncertainty on average than the “base rate” probability of default in the applicant population. The reduction in uncertainty offered by the learner's model-plus-data is known as information gain. It is possible to calculate the exact financial value of new information – in this case, a credit score offered for sale by a predictive analytics firm. This week you will learn how to calculate both the potential information gain from the new data and its cost savings– in effect, determining the incremental financial value to the credit card issuer per bit of information purchased.

阅读材料 · Excel Workbook for Information Measures

视频 · Quantifying the Informational Edge

视频 · Probability and Entropy

视频 · Entropy of a Guessing Game

练习测验 · Practice - Using the Information Calculator Spreadsheet


视频 · Dependence and Mutual Information

视频 · The Monty Hall Problem

视频 · Learning from One Coin Toss, Part 1

视频 · Learning From One Coin Toss, Part 2

测验 · Week 3 Graded Quiz

阅读材料 · Note: There is No Practice Quiz for Information Measures

阅读材料 · Feedback Survey



第 4 周
Linear Regression
Welcome! This week you will be introduced to the most widely used parametric model - in which both signal and noise have a standard, Gaussian probability distribution. Together we will explore the many elegant and useful features of Gaussian parameters, including using them to show the deep relationship between the residual error in a best-fit regression line, the linear correlation measure R, and the “mutual information” between X and Y - how much knowledge of X reduces uncertainty about Y. You will be able to characterize a linear regression estimate as either a “point estimate” or a probability distribution with defined confidence intervals.The Credit Card Business Case Study (Final Course Project) introduces a new output variable – instead of default/no default, the bank is now concerned with the historical profits and losses associated with each customer. Faced with continuous rather than binary outputs, a linear regression model is more appropriate. You will apply multivariate linear regression in Excel to develop a best-fit model for future applicants’ profits and losses. That model has a known error, or uncertainty, and you will place individual forecasts using it in a 90% confidence interval.

阅读材料 · Excel Workbook for Linear Regression

视频 · Introducing the Gaussian

视频 · Introduction to the Gaussian Probability Distribution, Part 1

视频 · Introduction to the Gaussian Probability Distribution, Part 2

视频 · Central Limit Theorem

视频 · Algebra with Gaussians

视频 · Markowitz Portfolio Optimization


视频 · Introduction to Standardization

视频 · Standardization and Linear Regression

视频 · Confidence Intervals for Linear Regression Models

视频 · Linear Regression with More than One Input Variable

视频 · Differential Entropy and Information Gain from Linear Regression

练习测验 · Week 4 Practice Quiz

测验 · Week 4 Graded Quiz

阅读材料 · Feedback Survey



第 5 周
Samples and Random Variables
Welcome! Did you know that data are often gathered into “bins” to form histograms? This week you’ll learn how to generate histograms with various bin sizes in Excel, and understand how and why histograms can be characterized as “probability histograms”. You will learn the most common ways that probability distributions are described, and the characteristics of the most common standard probability distribution functions. Data often appear to be coming from a process that fits one of these standard forms, whether Gaussian, uniform discrete, or uniform continuous. Together we will further explore the distinction between the apparent correlation for a set of ordered pairs and the idea of the “true” correlation or dependency between underlying processes. All of these ideas are relevant to establishing a model from data samples of limited size.

阅读材料 · No Excel Workbook for Samples and Random Variables

视频 · Describing Histograms and Probability Distributions Functions (PDFs)

视频 · Some Important and Frequently Encountered PDFs

视频 · Apparent Correlations in Random Draws

测验 · Week 5 Graded Quiz

阅读材料 · Feedback Survey



第 6 周
Final Course Project
Week 6 contains the Final Course Project and related supplemental materials necessary to successfully complete the project. The Final Course Project consists of four quizzes and a peer review assignment. We recommend that you attempt each of the quizzes after the weeks in which the content first appears, and do the peer review assignment at the end of the course.

阅读材料 · Final Project Instructions

阅读材料 · Excel Workbook for Final Course Project

视频 · Final Project Information: Part 1

视频 · Final Project Information: Part 2

测验 · Part 1: Building your Own Binary Classification Model

阅读材料 · Model Answers for Final Project Quiz 1

测验 · Part 2: Should the Bank Buy Third-Party Credit Information?

阅读材料 · Answers for Final Project Quiz 2

测验 · Part 3: Comparing the Information Gain of Alternative Data and Models

阅读材料 · Model and Exact Answers for Final Project Quiz 3

测验 · Part 4: Modeling Profitability Instead of Default

阅读材料 · Exact Answers for Final Project Quiz 4

同学互评 · Part 5: Modeling Credit Card Default Risk and Customer Profitability

阅读材料 · Feedback Survey




不显示详细信息


第 3 门课程
使用 Tableau 展示可视化数据
当前班次:Apr 17 — May 29。
课程学习时间
5 weeks, 3 - 5 hours per week


课程概述
One of the skills that characterizes great business data analysts is the ability to communicate practical implications of quantitative analyses to any kind of audience member. Even the most sophisticated statistical analyses are not useful to a business if they do not lead to actionable advice, or if the answers to those business questions are not conveyed in a way that non-technical people can understand. In this course you will learn how to become a master at communicating business-relevant implications of data analyses. By the end, you will know how to structure your data analysis projects to ensure the fruits of your hard labor yield results for your stakeholders. You will also know how to streamline your analyses and highlight their implications efficiently using visualizations in Tableau, the most popular visualization program in the business world. Using other Tableau features, you will be able to make effective visualizations that harness the human brain’s innate perceptual and cognitive tendencies to convey conclusions directly and clearly. Finally, you will be practiced in designing and persuasively presenting business “data stories” that use these visualizations, capitalizing on business-tested methods and design principles.


第 1 周
About this Specialization and Course
The 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 a 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 third course of the specialization: Data Visualization and Communication with Tableau, you will learn how to communicate business-relevant implications of data analyses.
Specifically, you will:

  • craft the right questions to ensure your analysis projects succeed;
  • leverage questions to design logical and structured analysis plans;
  • create the most important graphs used in business analysis and transform data in Tableau;
  • design business dashboards with Tableau;
  • tell stories with data;
  • design effective slide presentations to showcase your data story; and
  • deliver compelling business presentations.

By the end of this course, you will know how to structure your data analysis projects to ensure the fruits of your hard labor yield results for your stakeholders. You will also know how to streamline your analyses and highlight their implications efficiently using visualizations in Tableau, the most popular visualization program in the business world. Using other Tableau features, you will be able to make effective visualizations that harness the human brain’s innate perceptual and cognitive tendencies to convey conclusions directly and clearly. Finally, you will be practiced in designing and persuasively presenting business “data stories” that use these visualizations, capitalizing on business-tested methods and design principles by completing a final peer assessed project recommending a business process change.
To get started, please begin with the video 'About This Specialization.'
I hope you enjoy this week's materials!


视频 · About this Specialization

阅读材料 · Specialization Overview


视频 · Welcome to the Course!

阅读材料 · Course Overview

阅读材料 · FAQ (Frequently Asked Questions)

阅读材料 · Special Thanks!

阅读材料 · About the Course Team

阅读材料 · Feedback Survey Information



Asking The "Right Questions"
Welcome! This week, you will learn how data analysts ask the right questions to ensure project success. By the end of this week, you will be able to:

  • Craft the right questions to ensure your analysis projects succeed
  • Leverage questions to design logical and structured analysis plans

Remember to refer back to the Additional Resources reading: Identifying and Eliciting Information from Stakeholders). In addition, you will complete a graded quiz.
As always, if you have any questions, post them to the Discussions.
To get started, please begin with the video “Tips for Becoming a Data Analyst.”
I hope you enjoy this week's materials!


视频 · Tips for Becoming a Data Analyst

视频 · Asking the Right Questions


视频 · Rock Projects

视频 · S.M.A.R.T. Objectives


视频 · Listening to Stakeholders During Elicitation

视频 · Stakeholder Expectations Matter

阅读材料 · Week 1 Additional Resources


阅读材料 · SPAP Graphic

视频 · Using SPAPs to Structure Your Thinking, Part 1

视频 · Using SPAPs to Structure Your Thinking, Part 2

测验 · Week 1 Quiz

阅读材料 · Feedback Survey



第 2 周
Data Visualization with Tableau
Welcome to week 2! This week you'll install Tableau Desktop to learn how visualizing data helps you figure out what your data mean efficiently, and in the process of doing so, helps you narrow in on what factors you should take into consideration in your statistical models or predictive algorithms. Over the next two weeks, we’re going to learn how to use Tableau to implement this type of visualization and to help you find, and communicate, answers to business questions, as well as work with the Tableau functions that all data analysts should be familiar with. You will learn to install Tableau Desktop and learn to use the program by working with two data sets. In addition, through a series of practice exercises, you will use a data set to do example analyses and to answer specific sample questions about salaries for certain data-related jobs across the United State. Then for graded exercises, you will use a different data set to work out analyses and questions that will require you to directly apply the Tableau skills you have acquired through practice. By the end of this week, you will be able to:

  • Create the most important graphs used in business analysis and transform data in Tableau

Once you have watched the "Why Tableau" video, review the "Written Instructions to install Tableau Desktop" and install the software. Remember to refer back to the Salary Data Set and to the Dognition Data Set resources posted on the course site this week. You will also complete a graded quiz at the end of the week.
As always, if you have any questions, post them to the Discussions.
To get started, please begin with the video “Use Data Visualization to Drive Your Analysis" and then review the "Written Instructions to install Tableau Desktop.
I hope you enjoy this week's materials!


视频 · Use Data Visualization to Drive Your Analysis

视频 · Why Tableau?

阅读材料 · Written Instructions to Install Tableau Desktop


视频 · Meet Your Salary Data

视频 · Meet Your Dognition Data

视频 · Our Analysis Plan

阅读材料 · Salary Data Set, Description, and Analysis Plan

阅读材料 · Dognition Data Set, Description, and Analysis Plan


视频 · Salaries of Data-Related Jobs: Your First Graph

视频 · Formatting and Exporting Your First Graph

视频 · Digging Deeper Using the Rows and Columns Shelves

阅读材料 · The Effects of Outliers Video


视频 · Understanding the Marks Card


视频 · Removing Outliers Using Scatterplot and Filtering and Groups

视频 · Analyzing Data-Related Salaries in Different States Using Filtering and Groups


视频 · When to Use Line Graphs

视频 · Dates as Hierarchical Dimensions or Measures

视频 · Analyzing Data-Related Salaries Over Time Using Date Hierarchies

视频 · Analyzing Data-Related Salaries Over Time Using Trend Lines

视频 · Analysing Data-Related Salaries Over Time Using Box Plots

阅读材料 · Introduction to Linear Regression


阅读材料 · Week 2 Practice Exercises

测验 · Week 2 Quiz

阅读材料 · Feedback Survey



第 3 周
Dynamic Data Manipulation and Presentation in Tableau
Welcome to week 3! This week you'll continue learning how to use Tableau to answer data analysis questions. You will learn how to use Tableau to both find, and eventually communicate answers to business questions. You'll learn about the process of elicitation, and learn how to ensure your data story is not undermined by overgeneralization or bias and how to format your data charts to begin creating a compelling data story. By the end of this week, you will be able to:

  • Write calculations and equations in Tableau
  • Publish online business dashboards with Tableau.

Remember to refer to the additional resources for this week: “Examples of Tableau Dashboards and Stories” and "Using Tableau Dashboards When You Don't Have To."
You will also complete a graded quiz.
As always, if you have any questions, post them to the Discussions.
To get started, please begin with the video “Customizing and Sharing New Data in Tableau.”
I hope you enjoy this week's materials!


视频 · Customizing and Sharing New Data in Tableau


阅读材料 · Data Sets Needed in Week 3

视频 · Tableau Calculation Types

视频 · How to Write Calculations

视频 · Calculations that Make Filtering More Efficient

视频 · Identifying Companies that Pay Less than the Prevailing Wage


视频 · Blending Price Parity Data with Our Salary Data

视频 · Adjusting Data-related Salaries for Cost of Living


视频 · Calculating Which States Have the Top Adjusted Salaries within Job Subcategories

视频 · Using Parameters to Define Top States


视频 · Calculating Which Companies Have the Top Adjusted Salaries within Job Subcategories

视频 · Designing a Dashboard to Determine Where You should Apply for Data-related Job

视频 · Visual Story Points in Tableau

阅读材料 · Week 3 Additional Resources: Examples of Tableau Dashboards and Stories


阅读材料 · Week 3 Practice Exercises

测验 · Week 3 Quiz

阅读材料 · Feedback Survey



第 4 周
Your Communication Toolbox: Visualizations, Logic, and Stories
Welcome to week 4! This week you will become a master at getting people to agree with your data-driven business recommendations as you learn to deliver a compelling business presentation. You’ll learn about the insight from the intersection of visualization science and decision science, and what this means for you as a data analyst, who seeks to design a compelling and effective business presentations. If you intend to affect people’s decisions, you need to influence where they look. This week we will review a set of tools and concepts you can use to optimize your visualizations and your presentation style. You will soon be a master at getting people to agree with your data-driven business recommendations! By the end of this week, you will be able to:

  • Tell stories with data
  • Design effective slide presentations to showcase your data story, and
  • Deliver compelling business presentations

Remember to refer back to the Study Guide: Designing and Delivering Effective Presentations. You will also complete a graded quiz.
As always, if you have any questions, post them to the Discussions.
To get started, please begin with the video “Using Visualization to Influence Business Decisions.”
I hope you enjoy this week's materials!


视频 · Using Visualization Science to Influence Business Decisions


视频 · The Storyboarding Hourglass

视频 · Making Your Data Story Come Alive

视频 · Storyboarding Your Presentation


视频 · The Best Stress-Testers are Teams

视频 · Overgeneralization and Sample Bias

视频 · Misinterpretations Due to Lack of Controls

视频 · Correlation Does Not Equal Causation

视频 · How Correlations Impact Business Decisions


视频 · Choosing Visualizations for Story Points

视频 · The Neuroscience of Visual Perception Can Make or Break Your Visualization

视频 · Misinterpretations Caused by Colorbars

视频 · Visual Contrast Directs Where Your Audience Looks

阅读材料 · Week 4 Additional Resources: Designing and Delivering an Effective Business Presentation


视频 · Formatting Slides to Communicate Data Stories

视频 · Formatting Presentations to Communicate Data Stories

视频 · Delivering Your Data Story


测验 · Week 4 Quiz

阅读材料 · Feedback Survey



第 5 周
Final Project
Welcome to week 5! This week you will complete your final project. This assignment requires you to submit a recording of yourself giving a 4-5 minute presentation in which you present a data-driven business process change proposal to Dognition company management about how to increase the numbers of tests users complete. Students will give a short, peer-reviewed business presentation that uses a specified chart in Tableau. The final project will assess your mastery of the following:

  • Demonstrated understanding the Tableau functions discussed in this course
  • Adapting visualizations to make them maximally communicative
  • Storyboarding skills
  • Translating your story into a presentation ready for the boardroom
  • Effective presentation delivery
  • Evaluating business presentations

Remember to refer to the Background Information for Peer Review Assignment on the course web site before you begin. This final course project is a comprehensive assessment covering all of the course material and will take approximately 6-8 hours to complete.
As always, if you have any questions, post them to the Discussions. Thank you for your contributions to this final project!


阅读材料 · Background Information for Peer Review Assignment

同学互评 · Recommendations for Dognition Business Process Change

阅读材料 · Feedback Survey




不显示详细信息


第 4 门课程
用MySQL管理大数据
即将开课的班次:Apr 24 — Jun 5。
课程学习时间
每周3-5小时,共5周


课程概述
本课程致力于介绍如何在商业分析中运用关系数据库。你将会学到关系数据库是如何工作的,以及如何运用实体-联系图来展示数据结构。这将会帮助你理解商业环境下数据需要怎样被收集,而且如果你的工作涉及到完成新数据的归类,此课程也会帮助你


第 1 周
About this Specialization and Course
The 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 a 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 fourth course of this specialization "Managing Big Data with MySQL” you will learn how relational databases work and how they are used in business analysis. Specifically, you will:

  • Describe the structure of relational databases
  • Interpret and create entity-relationship diagrams and relational schemas that describe the contents of specific databases
  • Write queries that retrieve and sort data that meet specific criteria, and retrieve such data from real MySQL and Teradata business databases that contain over 1 million rows of data
  • Execute practices that limit the impact of your queries on other coworkers
  • Summarize rows of data using aggregate functions, and segment aggregations according to specified variables
  • Combine and manipulate data from multiple tables across a database
  • Retrieve records and compute calculations that are dependent on dynamic data features, and
  • Translate data analysis questions into SQL queries that accommodate the types of anomalies found in real data sets.

By the end of this course, you will have a clear understanding of how relational databases work and have a portfolio of queries you can show potential employers. Businesses are collecting increasing amounts of information with the hope that data will yield novel insights into how to improve businesses. Analysts that understand how to access this data – this means you! – will have a strong competitive advantage in this data-smitten business world.
To get started, please begin with the video 'About This Specialization.'
I hope you enjoy this week's materials!


视频 · About this Specialization

阅读材料 · Specialization Overview


视频 · Welcome to Managing Big Data with MySQL

视频 · What You Will Learn in This Course, and Why

阅读材料 · Course Overview

阅读材料 · FAQ (Frequently Asked Questions)

阅读材料 · Special Thanks!

阅读材料 · About the Course Team

阅读材料 · Feedback Survey Information



Understanding Relational Databases
Welcome to week 1! This week you will learn how relational databases are organized, and practice making and interpreting Entity Relationship (ER) diagrams and relational schemas that describe the structure of data stored in a database. By the end of the week, you will be able to:

  • Describe the fundamental principles of relational database design
  • Interpret Entity Relationship (ER) diagrams and Entity Relationship (ER) schemas, and
  • Create your own ER diagrams and relational schemas using a software tool called ERDPlus that you will use to aid your query-writing later in the course.

This week’s exercises are donated from a well-known Database Systems textbook, and will help you deepen and strengthen your understanding of how relational databases are organized. This deeper understanding will help you navigate complicated business databases, and allow you to write more efficient queries. At the conclusion of the week, you will test your understanding of database design principles by completing the Week 1 graded quiz.
To get started, please begin with the video “Problems with Having a Lot of Data Used by a Lot of People.”
As always, if you have any questions, post them to the Discussions.
I hope you enjoy this week's materials!


视频 · Problems with Having a Lot of Data Used by a Lot of People

视频 · How Relational Databases Help Solve Those Problems


视频 · Database Design Tools That Will Help You Learn SQL Faster

视频 · How Entity-Relationship Diagrams Work

视频 · Database Structures Illustrated by Entity-Relationship Diagrams

视频 · Relational Schemas


视频 · How to Make Entity-Relationship Diagrams using ERDPlus

阅读材料 · Entity-Relationship Written Exercises

阅读材料 · Entity-Relationship Written Exercises: Answer Key


视频 · How to Make Relational Schemas using ERDPlus

阅读材料 · Relational Schemas Written Exercises

阅读材料 · Relational Schemas Written Exercises: Answer Key


阅读材料 · Dognition Relational Schema Practice Exercise

阅读材料 · Dillard's Relational Schema Practice Questions

测验 · Week 1 Graded Quiz

阅读材料 · Correct Answers for Week 1 Quiz

视频 · Wrapping up Week 1

阅读材料 · Week 1 Feedback Survey



第 2 周
Queries to Extract Data from Single Tables
Welcome to week 2! This week, you will start interacting with business databases. You will write SQL queries that query data from two real companies. One data set, donated from a local start-up in Durham, North Carolina called Dognition, is a MySQL database containing tables of over 1 million rows. The other data set, donated from a national US department store chain called Dillard’s, is a Teradata database containing tables with over a hundred million rows.
By the end of the week, you will be able to:

  • Use two different database user interfaces
  • Write queries to verify and describe all the contents of the Dognition MySQL database and the Dillard’s Teradata database
  • Retrieve data that meet specific criteria in a socially-responsible using SELECT, FROM, WHERE, LIMIT, and TOP clauses, and
  • format the data you retrieve using aliases, DISTINCT clauses, and ORDER BY clauses.

Make sure to watch the instructional videos about how to use the database interfaces we have established for this course, and complete both the MySQL and the Teradata exercises. At the end of the week, you will test your understanding of the SQL syntax introduced this week by completing the Week 2 graded quiz.
To get started, please begin with the video “Introduction to Week 2.” As always, if you have any questions, post them to the Discussions.
I hope you enjoy this week's materials!


视频 · Introduction to Week 2

视频 · Meet Your Dognition Data

阅读材料 · Dognition Database Information

视频 · Meet Your Dillard's Data

阅读材料 · Dillard's Database Information


视频 · Introduction to Query Syntax

视频 · How to Use Jupyter Notebooks

视频 · How to Use Your Jupyter Account

阅读材料 · How to Use Jupyter (Written Instructions)

其它 · Link to Your Jupyter Home Page


其它 · MySQL Exercise 1: Looking at Your Data

阅读材料 · MySQL Exercise 1: Answer Key


其它 · MySQL Exercise 2: Selecting Data Subsets using WHERE

阅读材料 · MySQL Exercise 2: Answer Key


其它 · MySQL Exercise 3: Formatting Selected Data

阅读材料 · MySQL Exercise 3: Answer Key


视频 · How to Use Teradata Viewpoint and SQL Scratchpad

阅读材料 · How to Login to and Use Teradata Viewpoint (Written Instructions)

阅读材料 · Week 2 Teradata Practice Exercises Guide


阅读材料 · Special Note about Week 2 Graded Quiz - Please Read

测验 · Week 2 Graded Quiz using Teradata

视频 · You Have Already Become a Different Level of Business Analyst

阅读材料 · Week 2 Feedback Survey



第 3 周
Queries to Summarize Groups of Data from Multiple Tables
Welcome to week 3! This week, we are going to learn the SQL syntax that allows you to segment your data into separate categories and segment. We are also going to learn how to combine data stored in separate tables.
By the end of the week, you will be able to:

  • Summarize values across entire columns, and break those summaries up according to specific variables or values in others columns using GROUP BY and HAVING clauses
  • Combine information from multiple tables using inner and outer joins
  • Use strategies to manage joins between tables with duplicate rows, many-to-many relationships, and atypical configurations
  • Practice one of the slightly more challenging use cases of aggregation functions, and
  • Work with the Dognition database to learn more about how MySQL handles mismatched aggregation levels.

Make sure to watch the videos about joins, and complete both the MySQL and the Teradata exercises. At the end of the week, you will test your understanding of the SQL syntax introduced this week by completing the Week 3 graded quiz.
We strongly encourage you to use the course Discussions to help each other with questions.
To get started, please begin with the video 'Welcome to Week 3.’
I hope you enjoy this week’s materials!


视频 · Welcome to Week 3

其它 · MySQL Exercise 4: Summarizing Your Data

阅读材料 · MySQL Exercise 4: Answer Key

视频 · Habits that Help You Avoid Mistakes


其它 · MySQL Exercise 5: Breaking Your Summaries into Groups

阅读材料 · MySQL Exercise 5: Answer Key

其它 · MySQL Exercise 6: Common Pitfalls of GROUP BY

阅读材料 · There is NO Answer Key for MySQL Exercise 6


视频 · What are Joins?

视频 · Joins with Many to Many Relationships and Duplicates

视频 · A Note about Our Join Examples


其它 · MySQL Exercise 7: Inner Joins

阅读材料 · MySQL Exercise 7: Answer Key


其它 · MySQL Exercise 8: Joining Tables with Outer Joins

阅读材料 · MySQL Exercise 8: Answer Key


阅读材料 · Week 3 Teradata Practice Exercises Guide


阅读材料 · Special Note about Week 3 Graded Quiz - Please Read

测验 · Week 3 Graded Quiz using Teradata

视频 · No More Waiting to Retrieve Your Data

阅读材料 · Week 3 Feedback Survey



第 4 周
Queries to Address More Detailed Business Questions
Welcome to week 4, the final week of Managing Big Data with MySQL! This week you will practice integrating the SQL syntax you’ve learn so far into queries that address analysis questions typical of those you will complete as a business data analyst.
By the end of the week, you will be able to:

  • Design and execute subqueries
  • Introduce logical conditions into your queries using IF and CASE statements
  • Implement analyses that accommodate missing data or data mistakes, and
  • Write complex queries that incorporate many tables and clauses.

By the end of this week you will feel confident claiming that you know how to write SQL queries to create business value. Due to the extensive nature of the queries we will practice this week, we have put the graded quiz that tests your understanding of the SQL strategies you will practice in its own week rather than including it in this week’s materials.
Make sure to complete both the MySQL exercises and the Teradata exercises, and we strongly encourage you to use the course Discussions to help each other with questions.
To get started, please begin with the video 'Welcome to Week 4.’
I hope you enjoy this week’s materials!


视频 · Welcome to Week 4

其它 · MySQL Exercise 9: Subqueries and Derived Tables

阅读材料 · MySQL Exercise 9: Answer Key


其它 · MySQL Exercise 10: Useful Logical Functions

阅读材料 · MySQL Exercise 10: Answer Key


视频 · Start with an Analysis Plan

阅读材料 · Dognition Structured Pyramid Analysis Plan (SPAP)

其它 · MySQL Exercise 11: Queries that Test Relationships Between Test Completion and Dog Characteristics

阅读材料 · MySQL Exercise 11: Answer Key


其它 · MySQL Exercise 12: Queries that Test Relationships Between Test Completion and Testing Circumstances

阅读材料 · MySQL Exercise 12: Answer Key

阅读材料 · A Note about This Week's Quiz

阅读材料 · Week 4 Feedback Survey



第 5 周
Strengthen and Test Your Understanding
This week contains the final ungraded Teradata exercises, and the final graded quiz for the course. The exercises are intended to hone and build your understanding of the last important concepts in the course, and lead directly to the quiz so be sure to do both!

阅读材料 · Week 5 Teradata Practice Exercises Guide


阅读材料 · Special Note about the Week 5 Graded Quiz - Please Read

测验 · Week 5 Graded Quiz using Teradata

视频 · Don't Be Afraid to Ask Questions!

阅读材料 · Week 5 Feedback Survey
第 5 门课程
从 Excel 到 MySQL:商业分析技术毕业项目
即将开课的班次:May 8 — Jul 3。
课程学习时间
8 weeks of study, 8-10 hours/week

字幕
English

毕业项目介绍
In this final course you will complete a Capstone Project using data analysis to recommend a method for improving profits for your company, Watershed Property Management, Inc. Watershed is responsible for managing thousands of residential rental properties throughout the United States. Your job is to persuade Watershed’s management team to pursue a new strategy for managing its properties that will increase their profits. To do this, you will: (1) Elicit information about important variables relevant to your analysis; (2) Draw upon your new MySQL database skills to extract relevant data from a real estate database; (3) Implement data analysis in Excel to identify the best opportunities for Watershed to increase revenue and maximize profits, while managing any new risks; (4) Create a Tableau dashboard to show Watershed executives the results of a sensitivity analysis; and (5) Articulate a significant and innovative business process change for Watershed based on your data analysis, that you will recommend to company executives. Airbnb, our Capstone’s official Sponsor, provided input on the project design. The top 10 Capstone completers each year will have the opportunity to present their work directly to senior data scientists at Airbnb live for feedback and discussion. "Note: Only learners who have passed the four previous courses in the specialization are eligible to take the Capstone."


第 1 周
Introduction
The goal for this week is to learn about the Capstone Project you are tasked with, acquire background about the business problem, and begin to outline the steps of your analysis.

视频 · Introduction to the Capstone Project

阅读材料 · Course Overview

阅读材料 · Special Thanks!

阅读材料 · About the Course Team

阅读材料 · FAQ (Frequently Asked Questions)

阅读材料 · Feedback Survey Information


阅读材料 · Lesson Overview

阅读材料 · Elicitation Refresher

阅读材料 · Letter from Your Project Manager

阅读材料 · What are Project Managers, Anyway?

视频 · What Watershed Owners Care About

阅读材料 · Background about the Short-term Rental Industry

同学互评 · Your Three Elicitation Interviews


阅读材料 · Lesson Overview

视频 · Elicitation Interview with Your Project Manager

视频 · Elicitation Interview with Watershed's Marketing Director

视频 · Elicitation Interview with Watershed's Financial Director

阅读材料 · Outlining an SPAP

测验 · Elicitation

阅读材料 · Requirements and Assumptions

阅读材料 · Feedback Survey



第 2 周
Data Extraction and Visualization
The goal of this week is for you to extract the relevant data from the MySQL database you are given access to, and to look at it briefly in Tableau to get sense of what data you have.

视频 · Meet Your Data

阅读材料 · How to Meet and Retrieve Your Data

其它 · How to Meet and Retrieve Your Data (Jupyter notebook)

测验 · Verify You Have Extracted the Correct Data


阅读材料 · Visualize Your Data to Make Sure You Know What They Are

测验 · Make Sure You Understand What Your Data Mean

阅读材料 · Feedback Survey



第 3 周
Modeling
The goal of this week is for you to create a financial model using Excel to analyze the data you extracted from the database, and to start to predict short-term rents for some of Watershed's existing properties.

阅读材料 · Week 3 Learning Goals

阅读材料 · Single Workbook Containing Template Spreadsheets 1-3

阅读材料 · Single Workbook Containing Guide Spreadsheets

视频 · Creating a Predictive Model for Short-term Rental Rates

阅读材料 · Best Practices for Setting up an Excel Spreadsheet

阅读材料 · Using the First Best-Fit Line Template Spreadsheet

阅读材料 · First Best Fit Line Template (Spreadsheet 1)

测验 · First Best-Fit Line


视频 · Normalizing Rents to Improve Occupancy Forecasting

阅读材料 · Using the Normalized Data and Model Template Spreadsheet

阅读材料 · Normalized Data and Model Template (Spreadsheet 2)

视频 · Using the Dollars to Percentile Conversion Guide Spreadsheet

阅读材料 · Dollars to Percentile Conversion Guide Spreadsheet

测验 · Normalization

阅读材料 · Applying Normalization to the Comparable Properties

测验 · Applying Normalization to the Comparable Properties


阅读材料 · Lesson Overview

视频 · Optimizing Rents to Maximize Revenues

视频 · Using the Solver Revenue Maximization Guide Spreadsheet

阅读材料 · Solver Revenue Maximization Guide Spreadsheet

测验 · Optimization Basics

阅读材料 · Optimizing Watershed Rents

阅读材料 · Solver Rent Optimization Template (Spreadsheet 3)

测验 · Optimizing Watershed Rents

阅读材料 · Alternative to Solver Template (Spreadsheet 4)

阅读材料 · Feedback Survey



第 4 周
Cash Flow and Profits
The goal for this week is for you to use your projections about the Watershed properties to estimate cash flows and profits Watershed would experience if it converted properties to short-term rentals.

阅读材料 · Week 4 Learning Goals

阅读材料 · Single Workbook Containing Template Spreadsheets 5-6

视频 · Estimating Watershed Cash Flow and Profits

阅读材料 · Using the Alternative to Solver Template Spreadsheet

测验 · Alternative to Solver


视频 · Distinguishing Cash Flow from Profits and Losses

阅读材料 · Using the Forecasting Cash Flow and Profits Template Spreadsheet

阅读材料 · Forecasting Cash Flow and Profits Template (Spreadsheet 5)

视频 · Using the Annual Cash Flows and Profits Spreadsheet

阅读材料 · Annual Cash Flows and Profits Guide Spreadsheet

阅读材料 · Using the Sorting by Profitability Template Spreadsheet

阅读材料 · Sorting by Profitability Template (Spreadsheet 6)

测验 · Profitability


阅读材料 · The Value of Considering Cash Flow Risk and Total Cash Required

测验 · Cash Flow Risk and Total Cash Required

阅读材料 · The Value of Financial Sensitivity Analysis in General

测验 · Sensitivity Analysis: Measuring Cutoffs at 40% Transaction Fee

阅读材料 · Feedback Survey



第 5 周
Data Dashboard
The goal of this week and next week is to build an analytical dashboard in Tableau using the data models and assumptions you have discovered in prior weeks.

视频 · Using Tableau to Perform Sensitivity Analysis

视频 · Dashboard for Analyst Use

视频 · Dashboard Modification for a Financial Audience


阅读材料 · How to Get Started Making Your Dashboard


阅读材料 · Additional charts for your sensitivity analysis

视频 · Bar in Bar Graphs in Tableau

视频 · Histograms in Tableau

视频 · Tables in Tableau

阅读材料 · Feedback Survey



第 6 周
Dashboard for Decision-makers
This week complete your dashboard and add design elements so the dashboard is ready for stakeholders (Watershed executives, for example) to use it to test your model's assumptions.

视频 · Preparing Your Dashboard for Decision-makers

阅读材料 · Lesson Overview

视频 · Jittered Maps in Tableau

阅读材料 · How to Use Jittering to Depict Multiple Data Points in the Same Geographic Location


阅读材料 · Turning Your Sensitivity Analysis into a Recommendation


阅读材料 · Finalizing Your Dashboard

阅读材料 · Tableau Tricks to Try on Your Own (Including R Integration!)

测验 · Sensitivity Analysis

阅读材料 · Feedback Survey



第 7 周
Final Project
This week, design and give a presentation for Watershed executives with your business recommendations, and complete a white paper template. Evaluate 3 peer's dashboards, white papers and presentations.

视频 · Persuading Decision-makers to Follow Your Recommendations

阅读材料 · New Information from Your Project Manager!

阅读材料 · White Paper Background Information


测验 · A Very Important Question!

阅读材料 · About the Final Project

阅读材料 · PART I: Tableau Dashboard Instructions

阅读材料 · PART 2: White Paper Instructions

阅读材料 · PART 3: Presentation Instructions


同学互评 · Final Project Assignment Submission

视频 · Congratulations on Joining the Exciting Field of Data Analytics!

阅读材料 · Feedback Survey





毕业项目
从 Excel 到 MySQL:商业分析技术毕业项目
即将开课的班次:8月 29 — 10月 24。
课程学习时间
8 weeks of study, 5 hours/week


毕业项目介绍
In this final course you will complete a Capstone Project using data analysis to recommend a method for improving profits for your company, Watershed Property Management, Inc. Watershed is responsible for managing thousands of residential rental properties throughout the United States. Your job is to persuade Watershed’s management team to pursue a new strategy for managing its properties that will increase their profits. To do this, you will: (1) Elicit information about important variables relevant to your analysis; (2) Draw upon your new MySQL database skills to extract relevant data from a real estate database; (3) Implement data analysis in Excel to identify the best opportunities for Watershed to increase revenue and maximize profits, while managing any new risks; (4) Create a Tableau dashboard to show Watershed executives the results of a sensitivity analysis; and (5) Articulate a significant and innovative business process change for Watershed based on your data analysis, that you will recommend to company executives. Airbnb, our Capstone’s official Sponsor, provided input on the project design. The top 10 Capstone completers each year will have the opportunity to present their work directly to senior data scientists at Airbnb live for feedback and discussion. "Note: Only learners who have passed the four previous courses in the specialization are eligible to take the Capstone."


第 1 周
Introduction
The goal for this week is to learn about the Capstone Project you are tasked with, acquire background about the business problem, and begin to outline the steps of your analysis.

视频 · Introduction to the Capstone Project

阅读材料 · Course Overview

阅读材料 · Special Thanks!

阅读材料 · About the Course Team

阅读材料 · FAQ (Frequently Asked Questions)

阅读材料 · Feedback Survey Information


阅读材料 · Lesson Overview

阅读材料 · Elicitation Refresher

阅读材料 · Letter from Your Project Manager

阅读材料 · What are Project Managers, Anyway?

视频 · What Watershed Owners Care About

阅读材料 · Background about the Short-term Rental Industry

同学互评 · Your Three Elicitation Interviews


阅读材料 · Lesson Overview

视频 · Elicitation Interview with Your Project Manager

视频 · Elicitation Interview with Watershed's Marketing Director

视频 · Elicitation Interview with Watershed's Financial Director

阅读材料 · Outlining an SPAP

测验 · Elicitation

阅读材料 · Requirements and Assumptions

阅读材料 · Feedback Survey



第 2 周
Data Extraction and Visualization
The goal of this week is for you to extract the relevant data from the MySQL database you are given access to, and to look at it briefly in Tableau to get sense of what data you have.

视频 · Meet Your Data

阅读材料 · How to Meet and Retrieve Your Data

其它 · How to Meet and Retrieve Your Data (Jupyter notebook)

测验 · Verify You Have Extracted the Correct Data


阅读材料 · Visualize Your Data to Make Sure You Know What They Are

测验 · Make Sure You Understand What Your Data Mean

阅读材料 · Feedback Survey



第 3 周
Modeling
The goal of this week is for you to create a financial model using Excel to analyze the data you extracted from the database, and to start to predict short-term rents for some of Watershed's existing properties.

阅读材料 · Week 3 Learning Goals

阅读材料 · Single Workbook Containing Template Spreadsheets 1-3

阅读材料 · Single Workbook Containing Guide Spreadsheets

视频 · Creating a Predictive Model for Short-term Rental Rates

阅读材料 · Best Practices for Setting up an Excel Spreadsheet

阅读材料 · Using the First Best-Fit Line Template Spreadsheet

阅读材料 · First Best Fit Line Template (Spreadsheet 1)

测验 · First Best-Fit Line


视频 · Normalizing Rents to Improve Occupancy Forecasting

阅读材料 · Using the Normalized Data and Model Template Spreadsheet

阅读材料 · Normalized Data and Model Template (Spreadsheet 2)

视频 · Using the Dollars to Percentile Conversion Guide Spreadsheet

阅读材料 · Dollars to Percentile Conversion Guide Spreadsheet

测验 · Normalization

阅读材料 · Applying Normalization to the Comparable Properties

测验 · Applying Normalization to the Comparable Properties


阅读材料 · Lesson Overview

视频 · Optimizing Rents to Maximize Revenues

视频 · Using the Solver Revenue Maximization Guide Spreadsheet

阅读材料 · Solver Revenue Maximization Guide Spreadsheet

测验 · Optimization Basics

阅读材料 · Optimizing Watershed Rents

阅读材料 · Solver Rent Optimization Template (Spreadsheet 3)

测验 · Optimizing Watershed Rents

阅读材料 · Alternative to Solver Template (Spreadsheet 4)

阅读材料 · Feedback Survey



第 4 周
Cash Flow and Profits
The goal for this week is for you to use your projections about the Watershed properties to estimate cash flows and profits Watershed would experience if it converted properties to short-term rentals.

阅读材料 · Week 4 Learning Goals

阅读材料 · Single Workbook Containing Template Spreadsheets 5-6

视频 · Estimating Watershed Cash Flow and Profits

阅读材料 · Using the Alternative to Solver Template Spreadsheet

测验 · Alternative to Solver


视频 · Distinguishing Cash Flow from Profits and Losses

阅读材料 · Using the Forecasting Cash Flow and Profits Template Spreadsheet

阅读材料 · Forecasting Cash Flow and Profits Template (Spreadsheet 5)

视频 · Using the Annual Cash Flows and Profits Spreadsheet

阅读材料 · Annual Cash Flows and Profits Guide Spreadsheet

阅读材料 · Using the Sorting by Profitability Template Spreadsheet

阅读材料 · Sorting by Profitability Template (Spreadsheet 6)

测验 · Profitability


阅读材料 · The Value of Considering Cash Flow Risk and Total Cash Required

测验 · Cash Flow Risk and Total Cash Required

阅读材料 · The Value of Financial Sensitivity Analysis in General

测验 · Sensitivity Analysis: Measuring Cutoffs at 40% Transaction Fee

阅读材料 · Feedback Survey



第 5 周
Data Dashboard
The goal of this week and next week is to build an analytical dashboard in Tableau using the data models and assumptions you have discovered in prior weeks.

视频 · Using Tableau to Perform Sensitivity Analysis

视频 · Dashboard for Analyst Use

视频 · Dashboard Modification for a Financial Audience


阅读材料 · How to Get Started Making Your Dashboard


阅读材料 · Additional charts for your sensitivity analysis

视频 · Bar in Bar Graphs in Tableau

视频 · Histograms in Tableau

视频 · Tables in Tableau

阅读材料 · Feedback Survey



第 6 周
Dashboard for Decision-makers
This week complete your dashboard and add design elements so the dashboard is ready for stakeholders (Watershed executives, for example) to use it to test your model's assumptions.

视频 · Preparing Your Dashboard for Decision-makers

阅读材料 · Lesson Overview

视频 · Jittered Maps in Tableau

阅读材料 · How to Use Jittering to Depict Multiple Data Points in the Same Geographic Location


阅读材料 · Turning Your Sensitivity Analysis into a Recommendation


阅读材料 · Finalizing Your Dashboard

阅读材料 · Tableau Tricks to Try on Your Own (Including R Integration!)

测验 · Sensitivity Analysis

阅读材料 · Feedback Survey



第 7 周
Final Project
This week, design and give a presentation for Watershed executives with your business recommendations, and complete a white paper template. Evaluate 3 peer's dashboards, white papers and presentations.

视频 · Persuading Decision-makers to Follow Your Recommendations

阅读材料 · New Information from Your Project Manager!

阅读材料 · White Paper Background Information


测验 · A Very Important Question!

阅读材料 · About the Final Project

阅读材料 · PART I: Tableau Dashboard Instructions

阅读材料 · PART 2: White Paper Instructions

阅读材料 · PART 3: Presentation Instructions


同学互评 · Final Project Assignment Submission

视频 · Congratulations on Joining the Exciting Field of Data Analytics!

阅读材料 · Feedback Survey





毕业项目是什么?


毕业项目是一次特别设计的作业,让您能够应用和展示在专项课程中所学的技能。每门专项课程结束前,学生都要完成毕业项目。



退款政策是怎样规定的?


您可以在支付课程费用之日后两周以内,或者独立课程或专项课程在平台开课之日后两周以内申请退款,具体时间以两者中的较早日期为准。但是一旦您获得课程证书,将不能够退款,即使您在两周内获得了课程证书。
如果您预付了整个专项课程的费用,从支付费用之日或专项课程在平台上开课之日开始计算,您有一年时间来完成包括毕业项目在内的全部课程,并获得课程证书。如果时间允许,您可以反复参加课程的多个班次。
如果您只支付了一门课程,您必须在支付费用之日,或者课程在平台上开课之日后180天内,获得课程证书。如果时间允许,您可以重复参加课程的多个班次。请查看完整的退款政策



我可以只注册学习一门课程吗?我对整个专项课程没有兴趣。


可以,如果您想要注册学习某一特定课程,可以在课程目录中搜索该课程的名称。向下滚动屏幕到所有相关专项课程的下方的“课程”区域,找到并选中该课程。



我可以申请助学金吗?


是的,Coursera 为无法承担费用的学生提供了助学金。通过点击左侧“注册”按钮下的“助学金”可以申请助学金。您可以根据屏幕提示来申请助学金,并在申请被批准后收到通知。您需要为专项课程中每门课程申请奖学金,包括毕业项目。了解更多



完成《从 Excel 到 MySQL:商业分析技术》专项课程需要多少时间?


完成时间将根据您的学习计划而异,但是大部分学生能够在 6-7 个月内完成此专项课程。



专项课程中的各门课程多长时间开班一次?


此专项课程中的各门课程均定期开班,约每月一期。如果您未能在第一次完成某课程,您可轻松转至下期,已完成的作业和取得的成绩将一同转移。



我需要哪些背景知识?


无需数据分析或编程相关经验。只要您对数据分析及其在商业决策中的应用感兴趣,就可参加本课程。



>我需要按指定顺序学习专项课程中各门课吗?


由于后续课程将采用之前课程的材料,我们建议按照指定顺序学习各门课程。



完成《从 Excel 到 MySQL:商业分析技术》专项课程后,能够获得大学学分吗?


Coursera课程和证书并未包含大学学分,但部分大学可能会将Coursera专项课程证书纳入学分体系。具体信息请咨询您所在的学校。



完成《从 Excel 到 MySQL:商业分析技术》专项课程后,我能够掌握哪些技能?


您能学会如何将实际商业问题转化为数据问题,如何将自己的分析结果用具体数据表达出来,提供令人信服的参考,学会将想法转化为可执行的建议并清晰有力地传达给决策者。



完成课程作业需要什么软件?


您需要使用微软Excel 2007(或更新版本)。我们将使用免费插件Solver解决优化问题,其他的在线表格工具,如谷歌Sheets无法使用该功能。同时此专项课程将使用Tableau等可以免费下载的软件包。



如果没学过统计学、计算机、编程,能够顺利通过本课程考试吗?


可以。我们教授的分析方法和软件工具,不仅助您完成本课程,更助您成为一名商业分析师。



如果从未从事过商业相关工作,能够顺利通过本课程考试吗?


是的。我们旨在为您提供工具,帮助您掌握各种类型的商业数据分析,即便您从未接触过相关数据,没有行业相关经验,也能理解相关数据。



如果我已经获得过统计学、计算机科学或数学硕士学位,我能够在这门课程中学到新知识吗?


是的。您很可能从未接触过课程中的大部分内容。将数据量化分析能力应用于商业活动中,这需要软件、技能及专业知识的支持,您在研究生院可能很难接触到这些。



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