About this course: Who is this course for? This course is designed for students, business analysts, and data scientists who want to apply statistical knowledge and techniques to business contexts. For example, it may be suited to experienced statisticians, analysts, engineers who want to move more into a business role. You will find this course exciting and rewarding if you already have a background in statistics, can use R or another programming language and are familiar with databases and data analysis techniques such as regression, classification, and clustering. However, it contains a number of recitals and R Studio tutorials which will consolidate your competences, enable you to play more freely with data and explore new features and statistical functions in R. With this course, you’ll have a first overview on Strategic Business Analytics topics. We’ll discuss a wide variety of applications of Business Analytics. From Marketing to Supply Chain or Credit Scoring and HR Analytics, etc. We’ll cover many different data analytics techniques, each time explaining how to be relevant for your business. We’ll pay special attention to how you can produce convincing, actionable, and efficient insights. We'll also present you with different data analytics tools to be applied to different types of issues. By doing so, we’ll help you develop four sets of skills needed to leverage value from data: Analytics, IT, Business and Communication. By the end of this MOOC, you should be able to approach a business issue using Analytics by (1) qualifying the issue at hand in quantitative terms, (2) conducting relevant data analyses, and (3) presenting your conclusions and recommendations in a business-oriented, actionable and efficient way. Prerequisites : 1/ Be able to use R or to program 2/ To know the fundamentals of databases, data analysis (regression, classification, clustering) We give credit to Pauline Glikman, Albane Gaubert, Elias Abou Khalil-Lanvin (Students at ESSEC BUSINESS SCHOOL) for their contribution to this course design.
Created by: ESSEC Business School
Taught by: Nicolas Glady , Associate professor, at ESSEC Business School
Marketing Department
| Basic Info | Course 1 of 4 in the Strategic Business Analytics Specialization |
| Commitment | 4 weeks of study, 2-3 hours/week |
| Language | English |
| How To Pass | Pass all graded assignments to complete the course. |
| User Ratings |
Syllabus
WEEK 1
Introduction to Strategic Business Analytics
In this module, we will introduce you to the course and instructional approach. You will learn that Strategic Business Analytics relies on four distinct skills: IT, Analytics, Business and Communication.
4 videos, 1 reading, 1 practice quiz
- Video: Welcome to the course
- Video: Becoming a Business Analytics expert
- Video: Why? It is all about value not data
- Video: How to leverage data for value - from data to insight
- Reading: Dataset for practice quiz
- Practice Quiz: Practice Quizz Module 1
Finding groups within Data
In this module, you will learn how identifying groups of observations enables you to improve business efficiency. You will then learn to create those groups in a business-oriented and actionable way. We will use examples to illustrate various concepts. The assessments will also provide you with opportunities to replicate these examples.
9 videos, 1 reading
- Video: Introduction: what’s the point of finding groups within data?
- Video: Basic clustering using ad-hoc techniques: the example of product management
- Video: Identifying groups within data: what's the intuition behind clustering? The example of HR Analytics
- Video: Introduction to Customer Segmentation
- Video: Presentation of Pauline Glikman
- Video: Recital M2 - SKU example
- Video: Recital M2 - HR example
- Video: Recital M2 - Telecom example
- Reading: Script and dataset files to replicate recitals
- Video: Wrap-up: identifying groups within data
Graded: Quiz - Module 2
WEEK 2
Factors leading to events
In this module, you will learn why using rigorous statistical methods to understand the relationship between different events is crucial.
We’ll cover two examples: first, using a credit scoring example, you will learn how to derive information about what makes an individual more or less likely to have a strong credit score? Then, in a second example drawn from HR Analytics, you will learn to estimate what makes an employee more or less likely to leave the company.
As usual, we invite you to replicate those examples thanks to the recital
and to use the assessments provided at the end of the module to strengthen your understanding of these concepts.
7 videos, 1 reading
- Video: Understanding causes and consequences: introduction
- Video: Why use Business Analytics to understand the relationship between causes and consequences
- Video: Understanding what distinguishes two categories
- Video: Beyond the regression estimates: reporting effects in a visual way
- Video: Recital M3 - Credit score example
- Video: Recital M3 - HR example
- Reading: Script and dataset files to replicate recitals
- Video: Wrap-up: identifying causes to effects
Graded: Quiz - module 3
WEEK 3
Predictions and Forecasting
In this module you will learn more about the importance of forecasting the future.
You will learn through examples from various sectors: first, using the previous examples of credit scoring and HR Analytics, you will learn to predict what will happen. Then, you will be introduced to predictive maintenance using survival analysis via a case discussion. Finally, we’ll discuss seasonality in the context of the first example discussed in this MOOC: using analytics for managing your supply chain and logistics better.
10 videos, 1 reading
- Video: Predictions & Forecasting: introduction
- Video: Predicting events: sales, defaults, risks, churn, etc.
- Video: Using classification and regression techniques to forecast
- Video: Predicting when an event will happen with survival analysis
- Video: Introduction to time series and seasonality
- Video: Recital M4 - Credit Score
- Video: Recital M4 - HR example
- Video: Recital M4 - Predictive maintenance example
- Video: Recital M4 - Chocolate Sales example
- Reading: Script and dataset files to replicate recitals
- Video: Wrap-up: forecasting events
Graded: Quiz Module 4
WEEK 4
Recommendation production and prioritization
So far, you’ve learnt to use Business Analytics to glean important information relevant to the success of your business. In this module, you’ll learn more about how to present your Business Analytics work to a business audience. This module is also important for your final capstone project presentation.You’ll learn that it is important to find an angle, and tell a story.Instead of presenting a list of results that are not connected to each other, you will learn to take your audience by the hand and steer it to the recommendations you want to conclude on.You’ll learn to structure your story and your slides, and master the most used visualization tips and tricks. The assessment at the end of this module will provide an opportunity for you to practice these methods and to prepare the first step of the capstone project.
6 videos, 2 readings
- Video: Reporting your results: introduction
- Video: It's all about the story
- Video: One slide / One idea
- Video: One picture is worth a thousand words
- Video: Recital M5 - How to present your findings
- Reading: Presentation Tips
- Video: Wrap-up: reporting your results
- Reading: Datasets for Peer Review Assignment
Graded: Peer Review
FAQs
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Coursework
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Creators
ESSEC Business School
For over a century, ESSEC has been developing a state-of-the-art educational program that gives the individual pride of place in its learning model, promoting the values of freedom, openness, innovation and responsibility. Preparing future managers to reconcile personal interests with collective responsibility, giving consideration to the common good in their decision-making, and weighing economic challenges against the social costs are some of the objectives ESSEC has set for itself. Its ultimate goal? To create a global world that has meaning for us all.
Pricing
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| Access to course materials | Available |
| Access to graded materials | Available |
| Receive a final grade | Available |
| Earn a shareable Course Certificate | Available |
Ratings and Reviews
V
Excellent
Great course. Good lectures & business examples.
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M
Very interesting course. Needs real statistic knowledge to understand and see the potential of this course. I recommand to learn R langage in parallele to complete this training. It's a good base to go ahead in this domain.