1 / 11

Why a Integrated Statistical Information System (SIS)

Why a Integrated Statistical Information System (SIS). Dr. Bertrand Loison Swiss Federal Statistical Office. S tatistical I nformation S ystem SIS. Objectives of SIS. Enables the elaboration and production of Integrated Statistics Meets the requirements of data protection (privacy)

gordonchavez
Download Presentation

Why a Integrated Statistical Information System (SIS)

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Why a Integrated Statistical Information System (SIS) Dr. Bertrand Loison Swiss Federal Statistical Office

  2. Statistical Information System SIS Objectives of SIS • Enables the elaboration and production of Integrated Statistics • Meets the requirements of data protection (privacy) • Provides full retraceability (auditing) of all statistical data ever produced • Fully supports the production value chain of SFSO

  3. 4.10.09 1.04.10 The overall SIS schedule 1.04.09 1.06.10 . . . End of '11

  4. The overall SIS structure SIS System SIS Core Working Area Register Register Apps Channel Local DB Channel Access layer Statistical Warehouse Databases

  5. Where to do what The production process is performed here Data flow SIS System SIS Core Working Area Register Register Internet Apps Channel Local DB Channel Access layer Statistical Warehouse Databases Product diffusion Logistics and monitoring of data collection All persistent data – statistical and meta – are stored here

  6. Number Crunching, Business Intelligence (ETL, SAS) Business Intelligence, Desktop Publishing (tbd) The technologies used SIS System SIS Core Data processing Analysis Publication Register Register Apps Channel Local DB Channel Access layer Statistical Warehouse Databases Specific Applications (DotNet) Warehouse Infrastructure(ETL, Relational DB Oracle) 21. Jan. 09

  7. For internal use only,as few technical and privacy restrictions as possible Accessible to the public The Strategies Used SIS System SIS Core Working Area Register Register Apps Channel Local DB Channel Access layer Statistical Warehouse Databases Accessible for external authorized data suppliers Strict access control, privacy protection, versioning and registration (metadata-based)

  8. Functions in SIS GWR Data Supplier Management Samples Management Archived Statistics Client Management (CRM) BUR Data Collection Management Anonymisation / Pseudonymisation Monitoring Production Management BR SHIS DS Channels Analysis SDAP (EDIMBUS) (EWR) Crossmedia Production Diffusion Channels Information “Clients” Paper Interact. Data collection/ updating DL Information Management Historisation Printing Online Macro data Processing Micro dataProcessing InitialProcessing Internet Phone Metadata updating Analysis /Interpretation Editorial Management Individual File Metadata Usage (Variables, Classifications etc.) Metadata Management (Variables, Classifications etc.) GWR Register of Buildings and Appartments BUR Register of Enterprises SHIS Swiss Universitarian Information System EWR Register of Inhabitants (only temporarily) BR Other federal registers DL Data Suppliers SDAP Statistical Data Preparation Prozess Pervasive function blocksprocess related function blocks

  9. Impacts of SIS to ICT Governance: System Architecture SIS runs on the ICT infrastructure of the Swiss ICT Office. Usually, there are three environments: BusinessOrientedDevelopmentalong withProduction(SAS, BI/Publ) Development Acceptance Production Since the users of SIS develop and continuously adapt their statistics themselves, they need the possibility to do so:

  10. Impacts of SIS on ICT Governance: Sourcing Sourcing  SoftwareSIS enforces standardizing of tools lower licensing costs, lower training costs Sourcing  People SIS expects the statisticians to develop/maintain their statistic specific applications themselves = criterion for hiring Sourcing  Organization SIS intends/is expected to offer internal consultancy in terms of statistical/development support org unit + specialists needed

  11. Lessons learned by SIS - so far… Business driven Development of SIS is strictly optimized for minimum „time to market“: First full census to be run starting in 2011 Enteprise Architecture Two substantially different kinds of statistics:- standard indexes and reports: programmed ETL apps- ever changing / one shot statistics: scripted „lab“ apps- interactive data collection to invite data suppliers Development Methods - Conventional (DotNet) programming for standard apps- Flexible scripting for „lab“ apps- Requires a special system configuration Business Engineering Statisticians have been taught and now work successfully with BPMN and Use Cases to describe their processes and workflows Risk Management Finances tighter and tighter limitsPeople skilled people are difficult to obtainDeadlines everything is flexible except the deadlinesStandardization takes longer than Quick&Dirty… 21. Jan. 09

More Related