Foundations of Strategic Business Analytics (in Python)

% by ESSEC Business School
% Instructor: Nicolas Glady

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.

In this repo you'll find the python version of the case studies and exercises from the MOOC: Foundations of strategic business analytics, as taught by Nicolas Glady on coursera.

Syllabus

Week 1: Finding Groups Within Data

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 such as:

• Basic clustering using ad-hoc techniques: the example of product management
• Customer Segmentation
• HR Analytics

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:

1. 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?
2. 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.

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.