FINANCIAL ANALYTICS

LEARNING OBJECTIVES

The digitalization of companies brings along a tremendous amount of data. Efficient interpretation and analysis of this data can give your company the competitive advantage it needs. This module will explore the world of BI and AI.

Many companies are swimming in data, and they are spending millions to collect more. But even with new tools and algorithms to analyze and make predictions based on data, it’s often still not being used effectively. Poor master data costs companies handsful of money, users are frustrated and systems get blocked! Reports are incorrect. Solid master data is thus considered as a competitive advantage. 

Artificial intelligence and machine learning could be rocket fuel for your business, adding tremendous value to the entire enterprise, but only if you know how to harness and leverage them. With AI and machine learning reshaping the business landscape for numerous industries, there is increasingly high demand to bring data to life, going beyond the raw numbers to link them to strategic business initiatives.

This module will sharpen your analytics mindset, enabling you to bridge any knowledge gap that may exist between your data science and the C-suite. Here you will learn how to convert model-based recommendations into actionable insights and better managerial decisions.

 

In this module you will

• understand the challenges and limits associated to the big data phenomena in a business and economic context

• analyse large-scale data using machine learning, data mining and text mining concepts in order to solve complex problems in business or economics.

• learn how to answer business questions with analytical and predictive techniques

• take a deep dive into using predictive analysis with unstructured data and network data

DAY 1

Session 1 – Data management

• The big data revolution and its impact

• How to manage structured data?

• How to manage large-scale unstructured data ?

 

Session 2 – Data analytics 

• Introduction to machine learning principles

• Descriptive analytics: extraction of patterns and data structure

• Predictive analytics: making predictions using data

• Application of analytics

ABOUT THE FACULTY

PIERRE DEVILLE

Pierre is the Head of Data Science and Analytics at the Bisnode Group Analytics. He acts as a big data expert for large companies through executive programs in Business Analytics. Pierre Deville holds a MSc in Computer Science Engineer in Artificial Intelligence and a PhD in Applied Mathematics from the University of Louvain. 

MORE INFO

HOW TO GET THE MOST OUT OF YOUR TRAINING

Combine this module with the module "Enterprise Performance Management"

Solvay Brussels School

Franklin Rooseveltlaan 42

1050 Brussels

 

The Solvay building is located in the green heart of Brussels, on the edge of the beautiful Ter Kameren forest and a 15-minute walk (or 5 minutes by public transport) from the bustling center of Brussels. If desired, there are numerous
accommodation options (hotels and (air) bnb) in the neighborhood and in the center of the city. Need help?  Do not hesitate to contact us.

1.650 euro, excl VAT

Other price formulas: 

  • You can choose to follow this module in the context of the EMF programme. If you complete all 15 modules in a period of 15 subsequent months, then you pay € 16.000. If you spread it over a period of 3 years, then you pay € 18.000. 

  • Five Module package: 7500 euro / 5x2 modules of your choice. 

  • In-company:  This training personalized as part of your in company: good idea! Call us. 

NEXT TRAINING DATES

MAY 2020 14-15

 

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