Did you know that, along with the latest development of EU legislation, efficient data governance becomes a legal requirement for artificial intelligence and a necessity for the implementation of new data sources?
PwC invite you to a webinar with specialists in data management, AI, and automation tools. Along with guests, PwC will focus on the development of EU legislation in this area which affects the needs and requirements regarding data governance and use within companies.
PwC will show you specific practical examples from the energy sector and other industries. Furthermore, they will share with you several technical tools that may help companies with their data governance and use.
Date: 15 June 2022, ONLINE 3.00 p.m. – 4.30 p.m
Presenters of the event:
• Tomáš Kuča, Partner at PwC, CEE Risk Assurance Leader
• Vladimír Jaroš, Directorat PwC, Digital Enablement Leader
• Impact of latest EU legal regulations on digital technologies, Patrik Meliš-Čuga – Data Management Leader at PwC, Christina Hitrova – AI Expert at PwC How will the pending EU regulation affect monetisation and data sharing?
- We will be discussing the possibilities of data sharing and access without additional costs associated with the latest requirements concerning risk management with respect to GDPR, AI and IoT regulations.
• Presentation of the latest EU legislation and examples of its practical application in companies, Tomáš Náhlovský – Data Analytics Leader at PwC, Lukáš Kozlík – Data Management Consultant at PwC How will the latest EU regulation affect the area of AI, automation, data analytics or forecasting?
- We will show you practical examples of using data machine learning and forecasting for the energy sector and other industries.
• Technologies supporting digitalisation and data strategy, Ján Andrš – VP of Marketing at MANTA, Lukáš Kozlík – Data Management Consultant at PwC Why do we need to know our data, data flow, and impact of changes on reporting and business decision-making?
- We will present to you examples of digitalisation tools for data lines, data analytics process and data quality monitoring and their benefits.