Big Data
Strategy
Albrecht Wirthmann
ESS TF Big Data
Strategy: Introduction
• Big Data Action Plan and Roadmap
• Short term goals
• Medium term goals
• Long term objectives
• Big Data Strategy according to BD Action Plan and
Roadmap
• "A strategy for big data in official statistics should be
embedded into overall government strategies at national as
well as at EU level."
• Big Data Strategy focusing on long term objectives
Organization of work
Subgroup of ESS Big Data Task Force:
Rein Ahas (EE)
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Stefano Bertolo (CNECT)
Barteld Braaksma (NL)
Carola Carstens (CNECT)
Loredana Di Consiglio (ESTAT)
Paolo Righi (IT)
Lara Wiengarten (DE)
Albrecht Wirthmann ESTAT)
Markus Zwick (DE)
Collaboration platform: wiki
Outline of the BD strategy
document
 Scope
 Background
 Stakeholders
 Skills
 Opportunities and risks
 New roles and
 Actions
Scope
 Long term Horizon (beyond 2020)
 Topics
 What is Big data
 Addressees
Aims
Create focus, imply choices, common understanding
Implementation actions
Communication tool
Background
 Data revolution
 Framework for Official Statistics
 ESS Code of Practice
 Statistical Process
Stakeholders
 Statistical Offices, ESS
 Government and other public organisations (authorities)
 Data protection authorities
 Regulators in different sectors, e.g. telecommunication
 Academia, Universities
 Private businesses
 Non-profit organisations active in digital services (open
software community)
 Media
 General public / citizens
Skills
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New skills and competencies are necessary
Skills in statistics, data analytics and IT
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Big data team level competencies
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Big Data team leader
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Teamwork
Interpersonal + communication skills
Innovative and contextual awareness
Specialist knowledge and expertise
Statistics
IT
Data analysis and visualisation
Leadership and strategic direction
Building relationships and communication
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Skills
• Approach
 Define and describe learning outcomes
 Curricular to link courses
 Harmonisation of training instruments
• Elaborate comprehensive education concept > 2020
• New tools
 Platform for Massive Open Online Courses (MOOC)
 Partnerships with stakeholders
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Universities
Central Banks
International Organisations
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Opportunities and Risks
• Efficiency and resources
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Decrease cost
Lower burden
Improve statistical processes with big data analytics
Reinforce move to multisource-multipurpose statistical
production
• Quality
 Improve specific quality dimensions
 Increase product portfolio
• Privacy and Image
 Use of advanced analytical methods
 Commitment to privacy
New roles and actions
• Statistical Offices as
• Data Integrators
Blending of data sources
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Analytical service providers
Flash estimates: nowcasting -> forecasting
Short term policy support
Information Broker
Certification authority of processes / methods
ensuring defined quality levels
New roles and actions
• Actions
 Market watch
 Concept for matrix oriented structure
 Multisource-multipurpose statistical production
 Concept for integrated training programs
 Access to data
 Approach for creating and maintaining
partnerships
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Discussion
 What is the scope of the strategy?
 Mandate of the group
 What is the right level of flexibility?
 Needs of official statistics
 In contrast to general government needs
 In common with general government needs
 What is in the data revolution for official statistics?
 What new roles for official statistics should be
included into the strategy document?
 What actions should be proposed?