Excel to MySQL_ Analytic Techniques for Business - Duke University _ Coursera

4/3/2017

Excel cel to MyS MySQL: Analyt lytic Techn chniqu iques for Busine iness - Duke Duke Univ Unive ersit rsity y | Cou Course rsera

Excel to MySQL: Analytic Techniques for Business Specialization

Started Apr 03

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Excel to MySQL: Analytic Techniques for Business Specialization Turn Data Into Value. Drive business process change by identifying & analyzing key metrics in 4 industry-relevant courses.

About This Specialization

Formulate data questions, explore and visualize large datasets, and inform strategic decisions. In this Specialization, you’ll learn to frame business challenges as data questions. You’ll use powerful tools and methods such as Excel, Tableau, and MySQL to analyze data, create forecasts and models, design visualizations, and communicate your insights. In the 铼nal Capstone Project, you’ll apply your skills to explore and justify improvements to a real-world business process. The Capstone Project focuses on optimizing revenues from residential property, and Airbnb, our Capstone’s o㊬cial Sponsor, provided input on the project design. Airbnb is the world’s largest marketplace connecting property-owner property-owner hosts with travelers to facilitate short-term rental transactions. 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.

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5 courses

Projects

Certi铼cates

Try for Free Enroll and get full access to access to every course in the Specialization for 7 days. Cancel any time. https://ww w.cour ser a.or g/speci al i zati ons/excel - m ysql

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Courses

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Beginner Specialization. No prior experience required.

COURSE 1

Business Metrics for Data-Driven Companies Current session: Apr 3 — May 7.

Commitment

4 weeks, 3-5 hours per week

Subtitles

English, Chinese (Simpli뀜ed)

About the Course In this course, you will learn best practices for how to use data analytics to make any company more competitive and more pro铼table. 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 di⸀erent 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 e⸀ectively 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. 

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WEEK 1

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 铼nal Capstone Project, where you will apply your skills to real-world business process. You will learn to perform sophisticated data-analysis 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 铼rst course of the specialization: Business Metrics for Data-Driven Companies, Companies, you will be able to: learn best practices for using data analytics to make any company more competitive and more pro铼table; learn to recognize the most critical business metrics and distinguish those from mere data; get a clear picture of the vital but di⸀erent 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 e⸀ectively 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!

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Video · About This Specialization

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Reading · Specialization Overview

https://ww w.cour ser a.or g/speci al i zati ons/excel - m ysql

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Video · Introduction

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Reading · Course Overview

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Reading · Feedback Survey Information

Introducing Business Metrics Welcome! This week we will explore business metrics - the critical numbers that help companies 铼gure 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 俦ow, pro铼tability, and online retail marketing metrics; distinguish revenue, pro铼tability 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 Co⸀ee, as a supplemental document, so be sure to review it carefully and refer to the glossary for key information.

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Video · Metrics Help Us Ask the Right Questions

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Video · Distinguishing Revenue, Profitability, and Risk Metrics

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Video · Distinguishing Traditional and Dynamic Metrics

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Reading · Egger's Roast Coffee Cash Flow and P&L Statements

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

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

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Video · Revenue Metrics – Traditional Enterprise Sales Funnel

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

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

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Video · Profitability/Efficiency Metrics: Inventory Management

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Video · Profitability/Efficiency Metrics: Hotel Room Occupancy Optimization

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Video · Risk Metrics: Leverage and Reputational Risk

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Quiz · Business Metrics

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Reading · Feedback Survey

WEEK 2

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 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 铼nd most appealing to work for.By the end of this week, you will be able to: di⸀erentiate among di⸀erent 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 di⸀erentiate how di⸀erent types of companies relate to big data culture, and rank any company according to a 20-item checklist. You will also learn to di⸀erentiate how di⸀erent 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. https://ww w.cour ser a.or g/speci al i zati ons/excel - m ysql

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Video · Roles and Companies as They Relate to Big Data

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Video · The Business Analyst

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Video · An Inte rview with Business Analyst Shambhavi Vashishtha

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Video · Distinguishing the Business Data Analyst and Business Analyst Roles

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Video · An Inte rview with Business Data Analyst Tiffany Yu

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Reading · Summary of Job Requirements for Data-Centric Roles

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Video · The Data Scientist

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Video · An Inte rview with Data Scientist Dai Li

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Video · The Senior Software Engineer

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Video · Overview of 5 Types of Companies as They Relate to Big Data

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Video · Traditional Strategic Business Consulting

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Video · Bricks-and-Mortar Companies

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Video · Barnes and Noble Case Study

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Reading · 20-Item Checklist for Evaluating A Business

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

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Video · Hardware and Software Companies

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Video · Digital Companies

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Quiz · Working in the Business Data Analytics Marketplace

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WEEK 3

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 铼nancial 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 铼nancial services companies. You’ll 铼nd additional website links that expand some of the course materials covered in this week’s video lectures.

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Video · Web Marketing - Metrics

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Video · Web Marketing - AdWord Metrics

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Video · Web Marketing - Segmentation

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Reading · Links Cited In AdWords Metric Video

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Video · Financial Services Metrics - Money Management and Investing

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Video · The Equivalence of Different Returns –The Sharpe Ratio


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Video · Four Types of Money Managers and Their Performance Metrics

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Video · Venture Capital and Private Equity Investors

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Quiz · Going Deeper into Business Metrics

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WEEK 4

Applying Business Metrics to a Business Case Study This week contains the 铼nal course assignment, a peer assessment 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.

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Reading · A Look Ahead

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Peer Review · Articulating Business Metrics in a Business Case Study

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Reading · Feedback survey

COURSE 2

Mastering Data Analysis in Excel Current session: Apr 3 — May 21.

Commitment


Subtitles

English

About the Course Important: The focus of this course is on math - speci铼cally, data-analysis concepts and methods - not on Excel for its own sake. We use Excel to do our calculations, and all math formulas are given as Excel Spreadsheets, but we do not attempt to cover Excel Macros, Visual Basic, Pivot Tables, or other intermediate-to-advance intermediate-to-advanced d Excel functionality. This course will prepare you to design and implement realistic predictive models based on data. In the Final Project (module 6) you will assume the role of a business data analyst for a bank, and develop two di⸀erent predictive models to determine which applicants for credit cards should be accepted and which rejected. Your 铼rst model will focus on minimizing default risk, and your second on maximizing bank pro铼ts. The two models should demonstrate to you in a practical, hands-on way the idea that your choice of business metric drives your choice of an optimal model. The second big idea this course seeks to demonstrate is that your data-analysis results cannot and should not aim to eliminate all uncertainty. uncertainty. Your role as a data-analyst is to reduce uncertainty for decision-makers decision-makers by a 铼nancially valuable increment, increment, while quantifying how much uncertainty remains. You will learn to calculate and apply to real-world examples the most important uncertainty measures used in business, including classi铼cation error rates, entropy of i nformation, and con铼dence intervals for linear regression. All the data you need is provided within the course, all assignments are designed to be done in MS Excel, and you will learn enough Excel to complete all assignments. The course will give you enough practice with Excel to become 俦uent in its most commonly used business functions, and you’ll be ready to learn any other Excel functionality you might need in the future (module 1).


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The course does not cover Visual Basic or Pivot Tables and you will not need them to complete the assignments. All advanced concepts are demonstrated in individual Excel spreadsheet templates that you can use to answer relevant questions. You will emerge with substantial vocabulary and practical knowledge of how to apply business data analysis methods based on binary classi铼cation (module 2), information theory and entropy measures (module 3), and linear regression (module 4 and 5), all using no software tools more complex than Excel. 

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WEEK 1

About This Course This course will prepare you to design and implement realistic predictive models based on data. In the Final Project (module 6) you will assume the role of a business data analyst for a bank, and develop two di⸀erent predictive models to determine which applicants for credit cards should be accepted and which rejected. Your 铼rst model will focus on minimizing default risk, and your second on maximizing bank pro铼ts. The two models should demonstrate to you in a practical, hands-on way the idea that your choice of business metric drives your choice of an optimal model.The second big idea this course seeks to demonstrate is that your data-analysis results cannot and should not aim to eliminate all uncertainty. Your role as a data-analyst is to reduce uncertainty for decision-makers by a 铼nancially valuable increment, while quantifying how much uncertainty remains. You will learn to calculate and apply to real-world examples the most important uncertainty measures used in business, including classi铼cation error rates, entropy of information, and con铼dence intervals intervals for linear regression. All the data you need is provided within the course, and all assignments are designed to be done in MS Excel. The course will give you enough practice with Excel to become 俦uent in its most commonly used business functions, and you’ll be ready to learn any other Excel functionality you might need in future (module 1). The course does not cover Visual Basic or Pivot Tables and you will not need them to complete the assignments. All advanced concepts are demonstrated in individual Excel spreadsheet templates that you can use to answer relevant questions. You will emerge with substantial vocabulary and practical knowledge of how to apply business data analysis methods based on binary classi铼cation (module 2), information theory and entropy measures (module 3), and linear regression (module 4 and 5), all using no software tools more complex than Excel.

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Video · About This Specialization

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Video · Introduction to Mastering Data Analysis in Excel

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Excel Essentials for Beginners In this module, will explore the essential Excel skills to address typical business situations you may encounter in the future. The Excel vocabulary and functions taught throughout this module make it possible for you to understand the additional explanatory Excel spreadsheets spreadsheets that accompany later videos in this course.

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Reading · Tips for Success

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Video · Introduction to Using Excel in this Course

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Video · Basic Excel Vocabulary; Intro to Charting

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Video · Arithmetic in Excel

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Video · Functions on Individual Cells

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Video · Functions on a Set of Numbers

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Video · Functions on Ordered Pairs of Data

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Video · Sorting Data in Excel

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Video · Introduction to the Solver Plug-in


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Practice Quiz · Excel Essentials Practice

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Quiz · Excel Essentials

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WEEK 2

Binary Classification Separating collections into two categories, such as “buy this stock, don’t but that stock” or “target this customer with a special o⸀er, but not that one” is the ultimate goal of most business data-analysis data-analysis projects. There is a specialized vocabulary of measures for comparing and optimizing the performance performance of the algorithms used to classify collections into two groups. You will learn how and why to apply these di⸀erent metrics, including how to calculate the all-important AUC: the area under the Receiver Operating Characteristic (ROC) Curve.

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Video · Introduction to Binary Classification

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Video · Bombers and Seagulls: Confusion Matrix

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Video · Costs Determine Optimal Threshold

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Video · Calculating Positive and Negative Predictive Values

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Video · How to Calculate the Area Under the ROC Curve

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Video · Binary Classification with More than One Input Variable

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Practice Quiz · Binary Classification (practice)

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Quiz · Binary Classification (graded)

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WEEK 3

Information Measures In this module, you will learn how to calculate and apply the vitally useful uncertainty metric known as “entropy.” In contrast to the more familiar “probability” that represents the uncertainty that a single outcome will occur, “entropy” quanti铼es the aggregate uncertainty of all possible outcomes. The entropy measure provides the framework for accountability in data-analytic work. Entropy gives you the power to quantify the uncertainty of future outcomes relevant to your business twice: using the best-available estimates before you begin a project, and then again after you have built a predictive model. The di⸀erence between the two measures is the Information Gain contributed by your work.

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Video · Quantifying the Informational Edge

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Video · Probability and Entropy

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Video · Entropy of a Guessing Game

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Video · Dependence and Mutual Information Information

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Practice Quiz · Using the Information Gain Calculator Spreadsheet (practice)

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Video · The Monty Hall Problem

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Video · Learning from One Coin Toss, Part 1


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Video · Learning From One Coin Toss, Part 2

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Quiz · Information Information Measures (graded)

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WEEK 4

Linear Regression The Linear Correlation measure is a much richer metric for evaluating associations than is commonly realized. You can use it to quantify how much a linear model reduces uncertainty. When used to forecast future outcomes, it can be converted into a “point estimate” plus a “con铼dence interval,” or converted into an information gain measure. You will develop a 俦uent knowledge of these concepts and the many valuable uses to which linear regression is put in business data analysis. This module also teaches how to use the Central Limit Theorem (CLT) to solve practical problems. The two topics are closely related because regression and the CLT both make use of a special family of probability distributions called “Gaussians.” You will learn everything you need to know to work with Gaussians in these and other contexts.

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Video · Introducing the Gaussian

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Video · Introduction to Standardization

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Video · Standard Normal Probability Distribution in Excel

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Video · Calculating Probabilities from Z-scores

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Video · Central Limit Theorem

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Video · Algebra with Gaussians

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Video · Markowitz Portfolio Optimization

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Practice Quiz · The Gaussian (practice)

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Video · Standardizing x and y Coordinates for Linear Regression

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Video · Standardization Simplifies Linear Regression

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Video · Modeling Error in Linear Regression

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Video · Information Gain from Linear Regression

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Practice Quiz · Regression Models and PIG (practice)

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Quiz · Parametric Models for Regression (graded)

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WEEK 5

Additional Skills for Model Building This module gives you additional valuable concepts and skills related to building high-quality models. As you know, a “model” is a description of a process applied to available data (inputs) that produces an estimate of a future and as yet unknown outcome as output. Very often, models for outputs take the form of a probability distribution. distribution. This module covers how to estimate probability distributions from data (a “probability histogram”), and how to describe and generate the most useful probability distributions used by data scientists. It also covers in detail how to develop a binary classi铼cation model with parameters optimized to maximize the AUC, and how to apply linear regression models when your input consists of multiple types of data for each event. The module concludes with an explanation explanation of “over-铼tting” which is the main reason that apparently apparently good predictive models often fail in real life business settings. We conclude with some tips for how you can avoid over-铼tting in you own predictive model for the 铼nal project – and in real life.


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Video · Describing Histograms and Probability Distributions Functions

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Video · Some Important and Frequently Encountered PDFs

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Reading · AUC Calculator Explanation and Spreadsheet

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Video · Linear Regression with More than One Input Variable

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Video · Understanding Why Over-fitting Happens

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Quiz · Probability, AUC, and Excel Linest Function

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WEEK 6

Final Course Project The 铼nal course project is a comprehensive assessment assessment covering all of the course material, and consists of four quizzes and a peer review assignment. For quiz one and quiz two, there are learning points that explain components of the quiz. These learning points will unlock only after you complete the quiz with a passing grade. Before you start, please read through the 铼nal project instructions. From past student experience, the 铼nal project which includes all the quizzes and peer assessment, takes anywhere from 10-12 hours.

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Reading · Final Project Information

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Video · Final Project Information: Part 1

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Quiz · Part 1: Building your Own Binary Classification Model

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Reading · Summary of Learning Points for Final Project: Quiz 1

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Video · Final Project Information: Part 2

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

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Reading · Summary of Learning Points for Final Project: Quiz 2

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

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Quiz · Part 4: Modeling Profitability Instead of Default

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Peer Review · Part 5: Modeling Credit Card Default Risk and Customer Profitability

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COURSE 3

Data Visualization and Communication with Tableau Current session: Apr 3 — May 14.

Commitment


Subtitles

English


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About the Course One of the skills that characterizes great business data analysts is the ability to communicate practical implications implications of quantitative analyses to any kind of audience member. member. Even the most sophisticated statistical 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-r elevant implicat ions 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 e㊬ciently using visualizations visualizations in Tableau, the most popular visualization program program in the business world. Using other Tableau features, features, you will be able to make e⸀ective 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 presenting business “data stories” that use these visualizations, capitalizing on business-tested methods and design principles. 

Hide Details

WEEK 1

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 铼nal Capstone Project, where you will apply your skills to a real-world business process. You will learn to perform sophisticated data-analysis 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, Tableau, you will learn how to communicate business-relevant business-relevant implications of data analyses. Speci铼cally, 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 e⸀ective 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 e㊬ciently using visualizations in Tableau, the most popular visualization program in the business world. Using other Tableau features, you will be able to make e⸀ective 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 business “data stories” that use these visualizations, capitalizing on business-tested methods and design principles by completing a 铼nal 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!

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Video · About this Specialization

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Video · Welcome to the Course!

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Reading · FAQ (Frequently Asked Questions)

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Reading · Special Thanks!

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Reading · About th e Course Team

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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 Remember to refer back to the Additional Resources 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!

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Video · Tips for Becoming a Data Analyst

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Video · Asking the Right Que stions

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Video · Rock Projects

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Video · S.M.A.R.T. S.M.A.R.T. Objectives

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Video · Listening to Stakeholders During Elicitation

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Video · Stakeholder Expectations Matter

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Reading · Week 1 Additional Resources

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Reading · SPAP Graphic

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Video · Using SPAPs to Structure Your Thinking, Part 1

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Video · Using SPAPs to Structure Your Thinking, Part 2

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Quiz · Week 1 Quiz

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WEEK 2

Data Visualization with Tableau Welcome to week 2! This week you'll install Tableau Desktop to learn how visualizing data helps you 铼gure out what your data mean e㊬ciently, and in the process of doing so, helps you narrow in on what factors you should take into consideration 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 铼nd, 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 speci铼c sample questions about salaries for certain data-related jobs across the United State. Then for graded exercises, you will use a di⸀erent 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 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. 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! https://ww w.cour ser a.or g/speci al i zati ons/excel - m ysql

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Video · Use Data Visualization to Drive Your Analysis

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Video · Why Tableau?

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Reading · Written Instructions to Install Tableau Desktop

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Video · Meet Your Salary Data

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Video · Meet Your Dognition Data

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Video · Our Analysis Plan

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Reading · Salary Data Set, Description, and Analysis Plan

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Reading · Dognition Data Set, Description, and Analysis Plan

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

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Video · Formatting and Exporting Your First Graph

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Video · Digging Deeper Using the Rows and Columns Shelves

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Reading · The Effects of Outliers Video

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Video · Understanding the Marks Card

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Video · Removing Outliers Using Scatterplot and Filtering and Groups

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Video · Analyzing Data- Related Salaries in Different States Using F iltering a nd Groups

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Video · When to Use Line Graphs

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Video · Dates as Hierarchical Dimensions or Measures

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Video · Analyzing Data- Related Salaries Over Time Using Date Hiera rchies

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

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

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Reading · Introduction to Linear Regression

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Reading · Week 2 Practice Exercises

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Quiz · Week 2 Quiz

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WEEK 3

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 铼nd, 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." https://ww w.cour ser a.or g/speci al i zati ons/excel - m ysql

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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!

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Video · Customizing and Sharing New Data in Tableau

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Reading · Data Sets Needed in Week 3

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Video · Tableau Calculation Types

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Video · How to Write Calculations

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Video · Calculations that Make Filtering More Efficient

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Video · Identifying Companies that Pay Less than the Prevailing Wage

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Video · Blending Price Parity Data with Our Salary Data

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Video · Adjusting Data- related Salaries for Cost of Living

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

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Video · Using Parameters to Define Top States

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

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

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Video · Visual Story Points in Tableau

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Reading · Week 3 Additional Resources: Examples of Tableau Dashboards and Stories

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Reading · Week 3 Practice Exercises

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Quiz · Week 3 Quiz

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WEEK 4

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 e⸀ective business presentations. If you intend to a⸀ect people’s decisions, you need to in俦uence 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 e⸀ective slide presentations to showcase your data story, and Deliver compelling business presentations presentations Remember Remember to refer back to the Study Guide: Designing and Delivering E⸀ective Presentations. You will also complete a graded quiz. As always, if you have any questions, post them to the Discussions. Discussions. To get started, please begin with the video “Using Visualization to In俦uence Business Business Decisions.”


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I hope you enjoy this week's materials!



Video · Using Visualization Science to Influence Business Decisions

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Video · The Storyboarding Hourglass

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Video · Making Your Data Story Come Alive

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Video · Storyboarding Your Presentation

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Video · The Best Stress-Testers are Teams

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Video · Overgeneralization and Sample Bias

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Video · Misinterpretations Due to Lack of Controls

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Video · Correlation Does Not Equal Causation

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Video · How Correlations Impact Business Decisions

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Video · Choosing Visualizations for Story Points

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

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Video · Misinterpretations Caused by Colorbars

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Video · Visual Contrast Directs Where Your Audience Looks

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Reading · Week 4 Additional Resources: Designing and Delivering an Effective Business Presentation

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Video · Formatting Slides to Communicate Data Stories

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Video · Formatting Presentations to Communicate Data Stories

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Video · Delivering Your Data Story

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Quiz · Week 4 Quiz

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WEEK 5

Final Project Welcome to week 5! This week you will complete your 铼nal 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 speci铼ed chart in Tableau. The 铼nal 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 Storyboarding skills Translating your story into a presentation presentation ready for the boardroom E⸀ective 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 铼nal course project is a comprehensive comprehensive assessment covering all of the course material and will take approximately 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 铼nal project!

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Reading · Background Information for Peer Review Assignment


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Peer Review · Recommendations for Dognition Business Process Change

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COURSE 4

Managing Big Data with MySQL Upcoming session: Apr 10 — May 21.

Commitment


Subtitles

English, Russian

About the Course This course is an introduction to how to use relational databases in business analysis. You will learn how relational databases work, and how to use entity-relationship entity-rel ationship diagrams to display the structure of the data held within them. This knowledge will help you understand how data needs to be collected in business contexts, and help you identify features you want to consider if you are involved in implementing new data collection e⸀orts. You will also learn how to execute the most useful query and table aggregation statements for business analysts, and practice using them with real databases. No more waiting 48 hours for someone else in the company to provide data to you – you will be able to get the data by yourself! 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 Businesses are collecting increasing amounts of i nformation 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. 

Hide Details

WEEK 1

About this Specialization and Course The Coursera Specialization, "Managing Big Data with MySQL" 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 铼nal Capstone Project, where you will apply your skills to a real-world business process. You will learn to perform sophisticated data-analysis data-analysis functions using powerful software tools such as Microsoft Excel, Tableau, and MySQL. To learn more about the specialization, please review the 铼rst lesson below, "Specialization Introduction: Introduction: Excel to MySQL: Analytic Techniques for Business." In this 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. Speci铼cally, you will: (1) Describe the structure of relational databases; (2) Interpret and create entity-relationship diagrams and relational schemas that describe the contents of speci铼c databases; (3) Write queries that retrieve and sort data that meet speci铼c criteria, and retrieve such data from real MySQL and Teradata business databases that contain over 1 million rows of data; (4) Execute practices that limit the impact of your queries on other coworkers; (5) Summarize rows of data using aggregate functions, and segment aggregations aggregations according to speci铼ed variables; (6) Combine and manipulate data from multiple tables across a database; (7) Retrieve records and compute calculations that are dependent on dynamic data features; (8) 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 understanding of how relational databases work and have a portfolio of queries you can show potential employers. Businesses Businesses are collecting increasing amounts of information with the hope that data will yield novel insights into how to improve businesses. 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 with this course, you can begin with, "Introduction to Managing Big Data with MySQL." Please take some time to not only watch the videos, but also read through the course overview as there is extremely important course information in the overview.

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Video · About this Specialization


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Video · Welcome to Managing Big Data with MySQL

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Video · What You Will Learn in This Course

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Reading · IMPORTANT FOR EVERY LEARNER

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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 querywriting 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 e㊬cient 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!

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

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Video · How Relational Databases Help Solve Those Problems

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

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Video · How Entity-Relationship Diagrams Work

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Video · Database Structures Illustrated by Entity-Relationship Diagrams

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Video · Relational Schemas

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Video · How to Make Entity-Relationship Diagrams using ERDPlus

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Reading · Entity-Relationship Written Exercises

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Reading · Entity-Relationship Written Exercises: Answer Key

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Video · How to Make Relational Schemas using ERDPlus

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Reading · Relational Schemas Written Exercises

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Reading · Relational Schemas Written Exercises: Answer Key

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Reading · Dognition Relational Schema Practice Exercise

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Reading · Dillard's Relational Schema Practice Questions


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Quiz · Week 1 Graded Quiz

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Reading · Week One Quiz: Answers and Feedback

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Video · Wrapping up Week 1

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Reading · Week 1 Feedback Survey

WEEK 2

Queries to Extract Data from Single Tables Welcome to week 2! This week, you will start interacting with business databases. 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:1. Use two di⸀erent database user interfaces2. interfaces2. Write queries to verify and describe all the contents of the Dognition MySQL database and the Dillard’s Teradata database3. Retrieve data that meet speci铼c criteria in a socially-responsible using SELECT, FROM, WHERE, LIMIT, and TOP clauses, and4. 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. Enjoy this week's materials!

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Video · Introduction to Week 2

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Video · Meet Your Dognition Data

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Reading · Dognition Database Information

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Video · Meet Your Dillard's Data

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Reading · Dillard's Database Information

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Video · Introduction to Query Syntax

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Video · How to Use Jupyter Notebooks

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Video · How to Use Your Jupyter Account

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Reading · How to Use Jupyter (Written Instructions)

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Other · Link to Your Jupyter Home Page

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Other · MySQL Exercise 1: Looking at Your Data

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Reading · MySQL Exercise 1: Answer Key

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Other · MySQL Exercise 2: Selecting Data Subsets using WHERE

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Other · MySQL Exercise 3: Formatting Selected Data

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Video · How to Use Teradata Viewpoint and SQL Scratchpad

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Reading · How to Login to and Use Teradata Viewpoint (Written Instructions)

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Reading · Week 2 Teradata Practice Exercises Guide


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Reading · Introduction to Teradata

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Reading · Read Before Starting Quiz 2

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Quiz · Week 2 Graded Quiz using Teradata

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Reading · Week 2 Quiz: Answers and Feedback

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

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WEEK 3

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 speci铼c 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 con铼gurations 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!

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Video · Welcome to Week 3

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Other · MySQL Exercise 4: Summarizing Your Data

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Video · Habits that Help You Avoid Mistakes

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Other · MySQL Exercise 5: Breaking Your Summaries into Groups

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Other · MySQL Exercise 6: Common Pitfalls of GROUP BY

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Reading · There is NO Answer Key for MySQL Exercise 6

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Video · What are Joins?

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Video · Joins with Many to Many Relationships and Duplicates

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Video · A Note about Our Join Examples

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Other · MySQL Exercise 7: Inner Joins

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Other · MySQL Exercise 8: Joining Tables with Outer Joins

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Reading · Week 3 Quiz: Answers and Feedback

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Video · No More Waiting to Retrieve Your Data

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WEEK 4

Queries to Address More Detailed Business Questions Welcome to week 4, the 铼nal 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 con铼dent 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. 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!

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Video · Welcome to Week 4

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Other · MySQL Exercise 9: Subqueries and Derived Tables

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Other · MySQL Exercise 10: Useful Logical Functions

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Video · Start with an Analysis Plan

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Reading · Dognition Structured Pyramid Analysis Plan (SPAP)

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

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

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

Reading · No Week Four Quiz


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


WEEK 5

Strengthen and Test Your Understanding This week contains the 铼nal ungraded Teradata exercises, and the 铼nal 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!

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

Reading · Special Note about the Week 5 Graded Quiz - Please Read

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Reading · Quiz 5: Answers and Feedback

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Video · Don't Be Afraid to Ask Questions!

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COURSE 5

Increasing Real Estate Management Pro铼ts: Harnessing Data Analytics Upcoming session: May 8 — Jul 2.

Commitment

8 weeks of study, 8-10 hours/week

Subtitles

English

About the Capstone Project In this 铼nal course you will complete a Capstone Project using data analysis to recommend a method for improving pro铼ts 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 pro铼ts. To do this, you will: (1) Elicit information about important 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 pro铼ts, while managing any new risks; (4) Create a Tableau dashboard dashboard to show Watershed executives executives the results of a sensitivity analysis; and (5) Articulate a signi铼cant and innovative business process change for Watershed based on your data analysis, that you will recommend to company executives. Airbnb, our Capstone’s o㊬cial 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." 

Hide Details


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Excel cel to MyS MySQL: Analyt lytic Techn chniqu iques for Busine iness - Duke Duke Univ Unive ersit rsity y | Cou Course rsera WEEK 1

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.

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Video · Introduction to the Capstone Project

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Reading · About th e Course Team

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Reading · FAQ (Frequently Asked Questions)

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Reading · Lesson Overview

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Reading · Elicitation Refresher

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Reading · Letter from Your Project Manager

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Reading · What are Project Managers, Anyway?

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Video · What Watershed Owners Care About

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Reading · Background about the Short-term Rental Industry

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Peer Review · Your Three Elicitation Interviews

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Video · Elicitation Interview with Your Project Manager

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Video · Elicitation Interview with Watershed's Marketing Director

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Video · Elicitation Interview with Watershed's Financial Director

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Reading · Outlining an SPAP

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Quiz · Elicitation

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Reading · Requirements and Assumptions

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WEEK 2

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 brie俦y in Tableau to get sense of what data you have.

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Video · Meet Your Data

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Reading · How to Meet and Retrieve Your Data

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

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Quiz · Verify You Have Extracted the Correct Data


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Reading · Visualize Your Data to Make Sure You Know What They Are

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Quiz · Make Sure You Understand What Your Data Mean

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WEEK 3

Modeling The goal of this week is for you to create a 铼nancial 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.

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Reading · Week 3 Learning Goals

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Reading · Single Workbook Containing Template Spreadsheets 1-3

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Reading · Single Workbook Containing Guide Spreadsheets

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

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Reading · Best Practices for Setting up an Excel Spreadsheet

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Reading · Using the First Best-Fit Line Template Spreadsheet

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Reading · First Best Fit Line Template (Spreadsheet 1)

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Quiz · First Best-Fit Line

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Video · Normalizing Rents to Improve Occupancy Forecasting

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Reading · Using the Normalized Data and Model Template Spreadsheet

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Reading · Normalized Data and Model Template (Spreadsheet 2)

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Video · Using the Dollars to Percentile Conversion Guide Spreadsheet

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Reading · Dollars to Percentile Conversion Guide Spreadsheet

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Quiz · Normalization

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Reading · Applying Norma lization to the Comparable Properties

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Quiz · Applying Norma lization to the Comparable Properties

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Video · Optimizing Rents to Maximize Revenues

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Video · Using the Solver Revenue Maximization Guide Spreadsheet

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Reading · Solver Revenue Maximization Guide Spreadsheet

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Quiz · Optimization Basics

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Reading · Optimizing Watershed Rents

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Reading · Solver Rent Optimization Template (Spreadsheet 3)

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Quiz · Optimizing Watershed Rents

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Reading · Alternative to Solver Template (Spreadshee t 4 )

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WEEK 4

Cash Flow and Profits The goal for this week is for you to use your projections about the Watershed properties to estimate cash 俦ows and pro铼ts Watershed would experience if it converted properties to short-term rentals.

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Reading · Week 4 Learning Goals

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Reading · Single Workbook Containing Template Spreadsheets 5-6

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Video · Estimating Watershed Cash Flow and Profits

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Reading · Using the Alternative to Solver Template Spreadsheet

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Quiz · Alternative to Solver

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Video · Distinguishing Cash Flow from Profits and Losses

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Reading · Using the Forecasting Cash Flow and Profits Template Spreadsheet

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Reading · Forecasting Cash Flow and Profits Template (Spreadsheet 5)

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Video · Using the Annual Cash Flows and Profits Spreadsheet

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Reading · Annual Cash Flows and Profits Guide Spreadsheet

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Reading · Using the Sorting by Profitability Template Spreadsheet

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Reading · Sorting by Profitability Template (Spreadsheet 6)

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Quiz · Profitability

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Reading · The Value of Considering Cash Flow Risk and Total Cash Required

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Quiz · Cash Flow Risk and Total Cash Required

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Reading · The Value of Financial Sensitivity Analysis in General

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

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WEEK 5

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.

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Video · Using Tableau to Perform Sensitivity Analysis

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Video · Dashboard for Analyst Use

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Video · Dashboard Modification for a Financial Audience

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Reading · How to Get Started Making Your Dashboard

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Reading · Additional char ts fo r your sensitivity analysis


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Video · Bar in Bar Graphs in Tableau

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Video · Histograms in Tableau

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Video · Tables in Tableau

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WEEK 6

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.

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Video · Preparing Your Dashboard for Decision-makers

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Video · Jittered Maps in Tableau

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Reading · How to Use Jittering to Depict Multiple Data Points in the Same Geographic Location

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Reading · Turning Your Sensitivity Analysis into a Recommendation

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Reading · Finalizing Your Dashboard

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Reading · Tableau Tricks to Try on Your Own (Including R Integration!)

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Quiz · Sensitivity Analysis

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WEEK 7

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.

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Video · Persuading Decision-makers to Follow Your Recommendations

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Reading · New Information from Your Project Manager!

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Reading · White Paper Background Information

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Quiz · A Very Imp ortant Question!

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Reading · About th e Final Project

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Reading · PART I: Tableau Dashboard Instructions

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Reading · PART 2: White Paper Instructions

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Reading · PART 3: Presentation Instructions

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Peer Review · Final Project Assignment Submission

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


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


Pricing

Try for free Enroll to start your 7-day free trial 

Unlimited access to all courses in the Specialization. Watch lectures, try assignments, participate in discussion forums, and more.



Cancel anytime. No penalties - simply cancel before the trial ends if it's not right for you.



Certi뀜cate when you complete. Share on your resume, LinkedIn, and CV.

Enroll

Creators

Duke University is consistently ranked as a top research institution, with graduate and professional schools among the leaders in their 铼elds.

Jana Schaich Borg Assistant Research Professor

Daniel Egger Executive in Residence and Director, Center for Quantitative Modeling

FAQs



What is the Capstone Project? A Capstone Project is a larger project designed to help you practice, apply, and showcase the skills you’ve learned.



What is the refund policy?


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We o⸀er a 7-day free trial, which you can cancel before the trial period ends to avoid being billed. We do not o⸀er refunds once you are billed. View the full refund policy.



Can I just enroll in a single course? I'm not interested in the entire Specialization. To enroll in an individual course, search for the course title in the catalog. When you subscribe to a course that is part of a Specialization, you will be automatically subscribed subscribed to the entire Specialization. If you are just interested in a single course, you will need to cancel your subscription after completing completing this course in order to stop the recurring monthly charge.



Is 铼nancial aid available? Yes, Coursera provides 铼nancial aid to learners who cannot a⸀ord the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be noti铼ed if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.

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How long does it take to complete the Excel to MySQL: Analytic Techniques for Business Specialization? Time to completion can vary based on your schedule, but most learners are able to complete the Specialization in 6-7 months.



How often is each course in the Specialization o⸀ered? Each course in the Specialization is o⸀ered on a regular schedule, with sessions starting about once per month. If you don't complete a course on the 铼rst try, you can easily transfer to the next session, and your completed work and grades will carry over.



What background knowledge is necessary? No prior experience with analytics or programming programming is required. This Specialization is intended for anyone with an interest in data analysis and its applications in business decision-making.

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Do I have to take the courses in this Specialization in a speci铼c order? We recommend taking the courses in the order presented, as each subsequent course will build on material from previous courses.



Will I earn university credit for completing the Excel to MySQL: Analytic Techniques for Business Specialization? Coursera courses and certi铼cates don't carry university credit, though some universities may choose to accept Specialization Certi铼cates for credit. Check with your institution to learn more.



What will I be able to do upon completing the Excel to MySQL: Analytic Techniques for Business Specialization? You will be able to frame practical business questions that can be answered with data, visualize analytical insights in an informative and compelling fashion, and translate and persuasively communicate insights into actionable recommendations for decisionmakers.

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What software will I need to complete the assignments?


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You will need access to Microsoft Excel 2007 (or a more recent version of Microsoft Excel). We will be using the free Solver plugin for optimization problems, and this functionality is not available in alternative online tools such as Google Sheets. The Specialization will also make use of freely-downloadable software packages such as Tableau.

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Will I be able to succeed in this class if I have never taken a statistics, computer computer science, or programming class? Yes! We will teach you all the analytical and software tools you need to succeed not only in this class, but also as a business analyst.

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Will I be able to succeed in this class if I have never had a job in a business-related business-related 铼eld? Yes. Our goal is to give you tools to help you navigate business data analyses of all kinds, even if you have never worked with that type of data before or do not have experience with the associated type of business.



Will I learn anything new in this class if I have a graduate degree in statistics, computer science, science, or math? Yes. In fact, chances are high that you have never seen the majority of the content in this class. Applying quantitative skills to business contexts requires software, skills, and domain knowledge you are not likely to have been exposed to in graduate school.

More questions? Visit the Learner Help Center.


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Excel to MySQL_ Analytic Techniques for Business - Duke University _ Coursera

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