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BDV Skills Accreditation - Role of certification to deliver quality services in Digital transformation

The objective of the workshop is to highlight the need for a pan European level skill recognition for Big Data that stimulates mobility and fulfils the definition of overarching Learning Objectives & Overarching Learning Impacts. It is also meant to get feedback on the formats that are being prepared namely, usage of Badges, Label and EIT Label for professionals.

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BDV Skills Accreditation - Role of certification to deliver quality services in Digital transformation

  1. 1. The role of certification to deliver quality services in digital transformation A perspective on data skills Artur Romão Director, Innovation and Development Lead TF8.SG1 (SMEs and start-ups) September 17, 2020
  2. 2. Data skills as a European strategic asset “Over the last few years, digital technologies have transformed the economy and society, affecting all sectors of activity and the daily lives of all Europeans. Data is at the centre of this transformation and more is to come. […] Currently, big data and analytics are top of the list of critical skills shortages. […] Moreover, general data literacy in the workforce and across the population is relatively low and participation gaps exist […]. If it is not addressed, the shortage in data experts and the lack of data literacy will affect the EU’s capacity to master the challenges of the data economy and society.” A European strategy for data, European Commission, 2020 The issue of skills related to the growing pervasiveness of data in business and society is twofold: • Data experts must be capable of putting data to good use, beyond the scientific and technical challenges • Non-expert users must be able to make good use of data, and become active players in the data value chain
  3. 3. Challenges Combination of data expertise with domain knowledge and functional skills • Data scientists need to understand business needs and how to use data on them • Governance, ethics and ethical use of data, best practices, privacy compliance The need for operational skills for data processing will certainly increase as data volumes, reliability, interoperability, and security concerns grow Openness (data, software, access to knowledge) for data skills development, taking into account European values, guaranteeing gender, age, and sector balance Key stakeholders: • Academia, research institutions, new online learning platforms • Large companies, SMEs and start-ups • Governments, including regional and local, supporting organizations engaged in data skills development programs to reach citizens and companies
  6. 6. Actions Promote vocational education and training as an enabler for skilling, reskilling and upskilling • Setup wide scale enterprise training programmes • Include training as core component of funded projects • Setup training programs for domain expert users on data and data-based systems Develop data business-orientation by fostering: • Business skills education for data specialists • Specific training for SMEs and start-ups to capture value from data Promote a Euro-wide data science skills strategy, including: • A common framework for skills development and certification on data • Identify major skillset gaps in the workforce, devise reskilling and upskilling roadmaps • Match market needs with skills in junior profiles to assess gaps to be addressed in curricular education Ensure data skills development in alignment with the European Commission: • European Skills Agenda • ESCO and Europass platforms • Digital Education Action Plan
  7. 7. Role of certification Certification of expertise in data and data-driven solutions (on the supply-side), to vouch for: • Ability to deliver high quality solutions and services (from a technical perspective) • Compliance with standards and regulations, especially data privacy, sovereignty, and ethics • Domain knowledge, to extract and add more value from data Also relevant on the demand-side, to vouch for: • Ability to understand and take advantage of the value from data • Compliance with regulations, especially in what relates to data privacy and sovereignty, ethics and the ethical use of data For individuals, to provide: • Upskilling and competitiveness in the labour market
  8. 8. Thank you! Feedback?