| Enterprise Architecture (EA) for official statistics | |
| Course Leader | Nadia Mignolli |
| Target Group | Business architects; IT managers responsible for the design of new processes and innovative IT systems; Statistical survey managers; Statisticians and Technicians involved in statistical production processes. |
| Entry Qualifications | - Trainees should have a sound command of English and should be able to make short interventions and to participate in discussions actively, sharing experiences and best practices.
- Trainees should be able to illustrate examples from their respective experiences, with a focus on Trusted Smart Statistics in their NSIs.
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| Objective(s) | This Course aims at: - defining the reference framework of data generated by smart devices, technologies, networks and their relations with official statistics, also comparing NSIs’ different situations (different level of integration, etc.);
- introducing the main concepts, frameworks and artefacts to carry out Enterprise Architecture for official statistics;
- focussing on the Business Architecture Model/Activity model within NSIs, orientating it to ongoing modernisation changes and related mainly to innovative data sources, Big Data, new data;
- explaining how to apply and map GAMSO to new business models for official statistics, innovative sources and Big Data;
- explaining how to map GSBPM to the statistical processes related to innovative data sources;
- providing an overview of the main statistical and technical guidelines, best practices, and standards as pre-requisites for the implementation of EA and BREAL;
- focussing on the context of Big data REference Architecture and Layers – BREAL;
- providing theoretical training to develop BREAL;
- promoting group discussions on topics such as setting up a capability assessment and roadmaps for acquiring and benefiting from ESS shared investments.
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| Contents | The course will focus on essentials of EA approaches covering the following topics: - Definition of the reference framework of data generated by smart devices, technologies, networks and their relations with official statistics.
- Business-outcome driven Enterprise Architecture: why and how.
- Enterprise Architecture layers in brief:
- Business Architecture;
- Information Architecture;
- Application Architecture;
- Technology Architecture.
- Introduction to the ArchiMate modelling structures and their practical usages.
- Business Architecture (BA) concepts and components, focussing on modernisation changes related mainly to innovative data sources, Big Data, new data:
- BA Business Lines;
- BA Activity Model.
- GAMSO shared infrastructures and guiding principles:
- instrument for standardisation, quality enhancing and modernisation; - mapping new business models for official statistics, innovative sources and Big Data;
- sharing experiences in using architectural frameworks
- Generic Statistical Business Process Model (GSBPM): standard model and use case.
- GSIM: introduction and use case.
- Common Statistical Production Architecture (CSPA): overview and templates for sharing services.
- The ESS EA Reference Framework (EARF) for Trusted Smart Statistics.
- BREAL (Big data REference Architecture and Layers):
- Business layer;
- Application and Information layers;
- Examples of solution architectures.
- Enterprise Architecture: open challenges and perspectives for official statics and trusted smart statistics.
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| Expected Outcome | At the end of the Course, trainees will be able to: - propose the adoption of EA and BREAL within their respective organisations;
- facilitate the development of an EA compliant with the ESS EA Reference Framework;
- understand some best practices, standards and guidelines that facilitate modernisation processes and the change of paradigm represented by Trusted Smart Statistics.
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| Training Methods | - Power point presentations and lectures
- Exchange of views/experiences on national practices
- Comments and discussion on schemes and other digital materials
- Exercises
- Work in pairs and in small sub-groups
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| Required Reading | None |
| Suggested Reading | https://ec.europa.eu/eurostat/cros/content/trusted-smart-statistics-motivations-and-principles_en https://statswiki.unece.org/display/GAMSO/Generic+Activity+Model+for+Statistical+Organizations https://statswiki.unece.org/display/GSBPM/Generic+Statistical+Business+Process+Model https://ec.europa.eu/eurostat/cros/content/ess-enterprise-architecture-reference-framework_en https://statswiki.unece.org/display/CSPA/Common+Statistical+Production+Architecture http://www.opengroup.org/archimate/ http://www.archimatetool.com/ |
| Required Preparation | Trainees should be able to illustrate examples from their respective experiences and practices, with a focus on Trusted Smart Statistics in their NSIs. |
Trainer(s)/
Lecturer(s) | Nadia Mignolli; Mauro Bruno; Mauro Scanu; Giorgia Simeoni, Donato Summa (all from Istat). |
