Data Science and Visualization for Business

IE Business School

IE Business School


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Who should attend

  • Individuals at all stages of their careers who are eager to embrace technology and recognize the increasing and immediate importance of data analytics in business decision-making.
  • Professionals who want to apply an understanding of data-driven models to their own business solutions.
  • Professionals keen to upskill in technical areas, changing the way they make decisions in uncertain work environments.
  • Those interested in a career in data science or any field requiring a foundation in data .

About the course

Professionals from all sectors are identifying, analyzing, preparing and leveraging data to make smarter decisions on a daily basis. In this course, participants discover the basics of data science through data insights and visualization. Gain real-time guidance, feedback and professional insights from professors and experts from Google, Amadeus and McKinsey. With their help, students apply statistical concepts underlying data analytics to create meaningful displays that improve decision-making.

Module 1: Breaking the ice: Exploring data

Students are introduced to the importance of data science through two real-life examples: the Space Shuttle Challenger and Starbucks Tech in a Cup. They will learn basic data science terminology, processes and definitions. Later, they will get hands-on experience with data by working on a data set involving concession sales. This will allow them to develop their skills on Excel, learning useful functions and commands using a concession data set.

Module 2: Data visualization: The basics

A graph often gives you a better understanding of a variable than looking at raw data. Students will learn the importance of data visualization, and how to build and interpret graphs for categorical and quantitative variables. With Excel, they will summarize data and see how different types of data and variables entail different organization/visualization methods. The module’s video uses Halloween data collected from trick-or-treaters in Cincinnati, OH.

Module 3: Turning data into numerical information: The science of statistics

Students will study how to accurately describe three key features of univariate data sets. They will learn how to identify and evaluate the impact of missing data and outliers. Some measures of bivariate data will be introduced. The problem of “lying with numbers” will be discussed. At this point, students will have acquired the knowledge necessary to identify situations in which statistics were used to misleadingly.

Module 4: Taking visualization to the next level: Tableau

In the fourth module, students will learn how to create professional and interactive visualizations using Tableau software. This is a very practical module in which students will be introduced to the Tableau interface, in order to build sophisticated charts and create calculated fields using the US_flights data set, which involves U.S. airline flights from 2010 and 2011.

Module 5: The art of data science: Dashboards and storytelling

Students will learn about dashboards and all they imply. They will learn how to create an interactive dashboard, and asked to evaluate different types and identify their key characteristics. The second part of this module is dedicated to the art of storytelling. Here, Tableau is used to create story points for particular messages. A full description of the final assignment is also provided.

Why this program?

Visualizing data techniques

Demonstrate the key design principles and techniques for visualizing data.

Statistical concepts

Appraise the fundamental statistical concepts required for effective data summary and presentation.

Data visualization tools

Develop competency in the use of several available software tools for data visualization.

Project-based visualizations

Produce project-based opportunities to identify, understand, analyze, prepare and present visualizations on a variety of topics.

Cleaning and transforming data techniques

Apply techniques in acquiring, cleaning, transforming and visualizing data.


Create and publish basic dashboards to track, analyze and display key performance indicators (KPIs).


Rafif Srour Daher

Rafif Srour Daher has fourteen years of experience in teaching, analytical and empirical research, consultancy and data analysis. She has consistently proven her ability to work in international and multicultural environments, with experience in Lebanon, the U.S. and Spain. She considers herself ...

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Data Science and Visualization for Business at IE Business School

From  1950 EUR$2,362

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