This course aims to provide basic knowledge and hand-on experience for practitioners and VET trainers on the Big Data technologies and Data Management, which are considered as key factors in digital transformation of the enterprises of the future.
- Provide a general overview of the necessary competences and skills for data handling in maritime sector.
- Reviewing the best practices in teaching Big Data technologies and Data Management, discussion on the specific for maritime sector tasks and requirements.
- Learn about new technologies and tools used for data collection and handling.
Technicians and VET teachers/trainers interested in Big Data and Data Management best practices and applications for maritime and offshore energy. MATES partners and MATES TG experts. Women will be prioritized.
Attendees should have a basic knowledge of computer systems, office and Internet applications. Familiarity with one of programming languages python or Java is beneficial.
Option 1: Virtual
Option 2: University of Amsterdam, Science Park Amsterdam.
TA01. Big Data Technologies: Introduction, Reference Architecture, Big Data algorithms
TA02. Big Data Platforms for Data Analytics, Big Data service providers, Hadoop platform overview
TA03. Data Management and Governance, DAMA Architecture. Data Management Plan (DMP)
TA04. Case Study: Research Data Management
Registration link: http://bit.ly/MATES-BD
Deadline for registration: 5th October 2020
- Understand how to establish effective Data Management and Data Science team at their organisation to gradually build capacity.
- Understand basic concepts of Big Data and related technologies to analyse general and organisational use cases.
- Specify requirements and make informed decision on assessing different options for the enterprise Big Data infrastructure and Data Analytics services implementation.
- Outline the major components and processes of the enterprise Data Governance Architecture and corresponding organisational roles; develop the company’s Data Management Plan (DMP).
Each of 4 sessions will include lectures, practice and interactive discussions. Practice will include working with cloud based tools for data handling.