Sessions
Discover the next sessions of our open program in data innovation, privacy & risks below. Click on the session you are interested in to obtain its full calendar.
About
Download the flyerThis short program addresses data thinking and data-driven innovation as well as privacy, ethical and other risks associated with an increasing use of data. Useful tools and canvases to support data thinking will be presented and applied. Managerial blindness, ethical issues and other traps of Data Science are risks that need to be managed effectively to create a robust data-driven oriented business.
We will discuss the challenges of data sharing and data sovereignty in value-added services and ecosystems. We will conclude by providing ideas on how to make use of external and open data such as crowdsourcing.
Learning objectives
- Apply useful tools and canvases to support data thinking and identify use cases for data-driven innovation.
- Analyze data sharing needs and data sovereignty in ecosystems and identify the data platforms needed.
- Identify and manage the risks (managerial, organizational and ethical) that come with data-driven decision making.
Target audience
- Identify and manage the risks (managerial, organizational and ethical) that come with data-driven decision making.
- Business intelligence (BI) and data managers, data engineers and data architects who want to manage successful data-driven transformation.
- Data champions and executives in business lines (HR, Marketing, Operations, …) who want to become more data and analytics-savvy.
Program
This short program data innovation, privacy & risks was built for professionals seeking to learn about fundamental concepts and then practice them trough practical exercises. There is a strong emphasis on practical application supported by academic excellence, with the use of exercises and break-out groups, industry examples and guest speakers. The fundamental notions will be presented beforehand, then supplemented and illustrated by numerous practical exercises based on real cases .
This approach will allow the participants to deploy the concepts presented during the course as well as forging a strong analytical mindset to tackle future challenges they might face on .
Modalities
admission criteria
MotivationWe offer quality programs accessible to all professionals who have decided to develop new skills.
ParticipationThis short program requires your presence and participation
PrerequisitesFollow blocks 1, 2 and 3 of the CAS in Data science & management
study rulesPayment terms
Price: 5 000 CHFAll expenses related to continuing education are, except in exceptional cases, tax deductible .
Discount (10%): -500 CHFA discount is offered to Alumni HEC or Alumni EPFL (non cumulative offer).
Payment terms
