Data Strategies

TEACHER / PROFESSOR

• Pr. Martine George

Short Description of the course

In today’s business world companies have large amounts of data at their disposal. This material represents a unique lever to improve their performance and reputation. But most companies are not using this data to their advantage by lack of understanding of the available tools and their business potential.

With this program, you will:

• Discover and practice the various aspects of data strategies and business analytics (technical, analytical, the strategic and tactical business facets, storytelling, and evaluation)
• Analyze the challenges inherent in business analytics and therefore put into place a data-driven value chain within your organisation.
• Generate new ideas and develop convincing arguments in the area of business analytics for your organization

course Programme / detailed overview

Day 1: Data Analytical Thinking & Data Science Solutions

• Lecture 1: Data analytical thinking
  This lecture will introduce the basic concepts of data science, data mining, why it is important to understand data science, data engineering and processing, big data, data-driven decision-making, data science capability as a strategic asset and data scientist as a new role. It will also help the participants to become familiar with various applications and uses of data science.
• Lecture 2: From Domain Problem to data science Solutions -This lecture will help the participants to view domain problems from a data-analytics perspective. This will include data terminology, data science tasks, models and processes. Each topic will be supported by a balance between theoretical concepts and practical exercises.
• Workshop 1: Your Data Ecosystem – identify and understand the sources of available data

DAY 2: Data Gathering, Data Visualization and Descriptive Analytics

• Lecture 3: Data gathering & Experiments – This module will explore what data you need and how to get it, depending on the problem to be solved. The module begins by providing a list of questions to ask for a targeted data search.
• Lecture 4: Data Visualization – This module will zoom into the art and science of data visualization through a balanced approach combining principles and concrete practices.
• Lecture 5: Descriptive Analytics – This module will explore Descriptive Analytics tasks such as clustering, association analysis, profiling, in different domain contexts. The main principles will be presented and illustrated by real applications.
• Workshop 2: A concrete application of Descriptive analytics in an industrial/service context

DAY 3: Predictive Analytics

• Lecture 6: Predictive analytics – This module will explore what is predictive analytics modeling and will deep dive into regression and classification models in different domain contexts. The main principles will be presented and illustrated by real applications combining data, methodologies and algorithms.
• Lecture 7: Performance and Evaluation – This session will explain how to evaluate the performance of predictive models and will define and illustrate the underlying metrics.
• Workshop 3: A concrete application of Predictive analytics in an industrial/service context

TARGET students

The program is designed to deliver a multi-disciplinary approach to the challenges and opportunities related to data management and analytics. It is particularly relevant for profiles such as:

• Brand or Marketing managers who would like to deepen their expertise of concepts such as Marketing Return on Investment, Customer Retention & Churn Management
• Sales & Customer relationship managers who wish to develop their skills in areas such as Sales Service & Customer Relationship, Sales Talent Analytics, Promotion Analytics, Pricing Analytics
• General Managers who would like to enhance their strategy and tactics with an active use of data and business analytics
• The programme is designed for participants with a minimum of 3 years of professional experience and who demonstrate proficiency in English.

Learning outcomes

• A deeper knowledge, understanding and practice of the tools and concepts to lead successful data management
• A clear and actionable approach to data management and business analytics practices, supported by real-life examples
• First-person learning with case studies, debating sessions, rich media, simulations … At the Solvay Brussels School of Economics and Management, we like to place you at the heart of learning − utilizing the immersive approach to make the content of the training more stimulating and directly applicable to real conditions.