PowerPoint Presentation · o Advanced data analytics o Decentralized computing o Metadata...
Transcript of PowerPoint Presentation · o Advanced data analytics o Decentralized computing o Metadata...
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Eurostat benchmarking project
Eurostat unit B1
Warsaw, 21-22/11/018
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Where Do We Come From? What Are We? Where Are We Going?
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• 2016 – Best Practice Case Template - 16 open-ended questions
• 2017 – GARTNER – Benchmark of MS architecturesand IT organisation
Where Do We Come From ?
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• What Are We ?
• Where Are We Going?
Eurostat benchmarking project
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• The "Eurostat benchmarking project" covers Validation, ESBRs, "Data
Services" and Linked Open Data (LOD);
• The objective of the project is to provide Eurostat and the ESS partners
with tangible and actionable information about the statistical production
landscape (processes and tools);
• The project team (Eurostat project managers and contractor) analyses
ESS and Eurostat documentation, designs and carries out online
surveys (with the EU-Survey tool) as well as conducts interviews with
statisticians and IT professionals in the NSIs;
• The findings and recommendations will be collated in reports for
member states and Eurostat.
Scope of the project
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Example of benchmarking question (data validation)
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Combining a backwards and forward looking perspective
• Provide a constructive and open channel to assess what has been done across
the ESS partners;
• Collect feedback on what was successful to date and where there is room for
improvement;
• Gather a combined picture of the upcoming priorities of NSIs in the field of
statistical data/metadata management and data analysis in the light of the
expected trends (big data, AI, IoT,…);
Benchmarking approach
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Achievements and feedback
• Analyse what has been achieved across the ESS partners;
• Collect feedback on the work of the last few years to identify which initiatives
added the highest value;
• NSIs can rate the effectiveness of the different projects and share their own
achievements with the ESS as a whole;
• Countries can outline how they collaborated with other member states;
• Analyse how NSIs selected technology platforms for their pilots and POCs.
Benchmarking approach
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Priorities for the next years
• Establish which projects are ongoing at the NSIs and their main objectives;
• Analyse investment plans into new technologies;
• Confirm if mid- and long-term technology roadmaps exist;
• Establish the technology priorities across the ESS with a focus on statistical data
management and data analytics;
• Help to highlight common priorities, plans and collaboration potential between
NSIs in the member states.
Benchmarking approach
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• One of the objectives of this benchmarking
project is to help the ESS to make effective
investment decisions based on past projects
and potential future synergies;
• Implement: Plan – Do – Check – Act;
• In a global data ecosystem enabled by the
internet, big data, IoT etc. it will be even more
important to consider practices like continuous
feedback and continuous improvement and to
integrate those with existing processes in the
future.
Measuring outcomes
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• The proposal is to focus the benchmarking on the following technologies:
o Data virtualization and the logical statistical data warehouse
o Advanced data analytics
o Decentralized computing
o Metadata management
o New data sources management
• Validate what has been tested by NSIs, what was working well and what not so
well;
• Analyse how technology platforms were selected – including vendor and open
source solutions – to help share lessons learned and best practices;
• Lay the foundation for a technology solution catalogue;
• Establish how much appetite there is to collaborate across member states in
structure like CoE;
New technologies
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• Based on previous experience with data validation a limited number of
questions to sketch an overal profile with tentative follow up telephone interview.
• The questionnaires would address cross-functional S-DWH teams at NSIs. The
questionnaire will be elaborated in coordination with the CoE on DWH
• The aim is to conduct the benchmarking in February 2019 and communicate the
findings by the end of March 2019.
• The online questionnaire will be at least available for three weeks in February
after which the analysis will start.
Benchmarking method and high-level timeline
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• Online survey carried out via the
EU-Survey tool;
• Creation of a dynamic
questionnaire for the respective
questionnaire in case not all NSIs
have cross-functional S-DWH
teams;
• Creation of an analysis
presentation and a report with a
detailed analysis and
recommendations.
Execution of the benchmarking
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Where Are We Going?
Data
Information
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Importance of other topics
Access to raw data? ELT instead of ETL?
Self-BI
Data governance
Trainings
Visualization
Security
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Thank you for your attention!