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Central Warehousing Work Session of Friends of the Chair Group Bern, Switzerland 6 – 8 June 2007 Marie Brodeur/Michel Girard Statistics Canada.

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Presentation on theme: "Central Warehousing Work Session of Friends of the Chair Group Bern, Switzerland 6 – 8 June 2007 Marie Brodeur/Michel Girard Statistics Canada."— Presentation transcript:

1 Central Warehousing Work Session of Friends of the Chair Group Bern, Switzerland 6 – 8 June 2007 Marie Brodeur/Michel Girard Statistics Canada

2 Overview Categories of warehouses Categories of warehouses Data and analysis Data and analysis Business Intelligence softwareBusiness Intelligence software Comparing data from various sourcesComparing data from various sources Characteristics of data warehouses Characteristics of data warehouses Examples Examples

3 Integration Suite of centralized tools Collection – Processing – Analysis Collection – Processing – Analysis PIPES – Improving provincial statistics PIPES – Improving provincial statistics Improving consistencyImproving consistency Improving coherenceImproving coherence Story using data from various sources Story using data from various sources Coherence among surveys, entities… Coherence among surveys, entities… Breadth and depth of business survey data Breadth and depth of business survey data

4 Integration Statistical agencies Ability to validly compare data and aggregate statistics across industries and/or institutional sectors and/or other aspects of economic interest Ability to validly compare data and aggregate statistics across industries and/or institutional sectors and/or other aspects of economic interest Rely on standardization Rely on standardization Standard unitsStandard units Standard classificationsStandard classifications Common analytical frameworkCommon analytical framework

5 Warehouse Link with source data at the cell level Link with source data at the cell level Even at the micro levelEven at the micro level Common classifications/concordances Common classifications/concordances Source data are treated according to same concepts and definitions Source data are treated according to same concepts and definitions Promote integration not only reconciliation Promote integration not only reconciliation Capacity to show adjustments Capacity to show adjustments

6 Warehousing Evolution of the concept Unified Survey Tracking, Analysis and Retrieval Tool (U-START) Unified Survey Tracking, Analysis and Retrieval Tool (U-START) SNA Analytical Warehouse (SNA AW) SNA Analytical Warehouse (SNA AW) CANSIM (STC Dissemination) CANSIM (STC Dissemination) Tabulations and metadataTabulations and metadata Focus is on aggregate dataFocus is on aggregate data Issue with comparabilityIssue with comparability

7 U-START Philosophy Philosophy Contains survey and administrative dataContains survey and administrative data Feeding CSNA from one central pointFeeding CSNA from one central point Coherence of analysis Coherence of analysis Residential construction/wood productionResidential construction/wood production Feeding CSNA analytical outputFeeding CSNA analytical output

8 U-START  Point and click access to data and metadata Collection, edit, imputation and estimation phaseCollection, edit, imputation and estimation phase A data/document querying tool A data/document querying tool Including questionnaire imageIncluding questionnaire image Quick access to user defined static report Quick access to user defined static report Frequency reports, grouped tabulations, contribution reportsFrequency reports, grouped tabulations, contribution reports Ability to summarize large databases Ability to summarize large databases Drill down - macro to micro and navigation Drill down - macro to micro and navigation Exporting tool: off-the-shelf software/databases Exporting tool: off-the-shelf software/databases Links to analytical outputs/survey notes or information (Corporate knowledge) Links to analytical outputs/survey notes or information (Corporate knowledge)

9 SNA Warehouse Being implemented… Accessing source data and metadata Accessing source data and metadata Common way to manipulate the data Common way to manipulate the data Not a place to process Not a place to process Excellent to compute consistently derived statistics Excellent to compute consistently derived statistics Analytical tool Analytical tool Promoting common judgmentPromoting common judgment Dealing with new staffDealing with new staff Facilitate integration not only reconciliationFacilitate integration not only reconciliation

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16 U-START and SNA Warehouse Quick access to data Quick access to data Learning tool Learning tool Consistency of derived statistics Consistency of derived statistics Capacity to analyze data at various stages of production Capacity to analyze data at various stages of production Adjustments Adjustments Promote coherence Promote coherence Must work on documentation aspects Must work on documentation aspects


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