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Data Warehous ing at STC

Data Warehous ing at STC. MSIS 2007 Geneva, May 8-10, 2007 Karen Doherty Director General Informatics Branch Statistics Canada. Table of Contents. Canadian Systems of National Accounts SNA Warehouse Data Warehouse Framework Lessons Learned. System of National Accounts.

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Data Warehous ing at STC

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  1. Data Warehousing at STC MSIS 2007Geneva, May 8-10, 2007 Karen DohertyDirector General Informatics BranchStatistics Canada

  2. Table of Contents • Canadian Systems of National Accounts • SNA Warehouse • Data Warehouse Framework • Lessons Learned

  3. System of National Accounts • The SNA provides a conceptually integrated framework of statistics and analysis for studying the state and behaviour of the Canadian economy • The accounts are centered on the measurement of activities associated with production of goods and services, the sales of goods and services in final markets, the supporting financial transactions, and the resulting wealth positions

  4. System of National Accounts • Input-Output Division (now the Industry Accounts Division) • produces the output, input, and final demand tables for each provincial and territorial jurisdiction • the tables are linked through an interprovincial flows table that shows imports and exports between jurisdictions • covers all economic activities (persons, businesses, government and non-profit organizations, and external entities that generate imports or exports (interprovincially or internationally) • The I-O tables represent the most detailed accounting of the Canadian economy available and thus serve as benchmarks to the Canadian System of National Accounts

  5. I-O Re-engineering • Project Impetus • aging production systems and work processes • no tools for data verification and table balancing imposed a heavy burden on staff • lack of integration and standardization of processes and procedures impeded the division’s ability to handle the growing amount of input data • Project Objectives • maximize knowledge retention and reuse through the introduction of software to specify derivation and balancing methodologies • maximize operational integration potential of the various divisions of the SNA through the introduction of a data management system to integrate data and meta-data • facilitate data reconciliation between I-O and other SNA divisions • maximize analytical potential through the introduction of main stream analytical tools to detect problems in the I-O Tables and source data

  6. Solution • A data warehouse with three components: • user-supplied micro and aggregate data to facilitate data confrontation • aggregate (macro) data to support data reconciliation with the GDP outputs from system divisions • tools for analysts • standard statistical functions • tools to calculate industry and commodity specific ratios

  7. System Capabilities • Analysts can: • compare data from different sources, ensuring consistency of estimates by making dissimilar classifications comparable • reconcile information across divisions in the SNA and make effective decisions during the annual production cycle • compare statistics in terms of ratios, proportions, growth rates, by region and in chronological series • review the metadata and information on how the data was established, concepts and definitions, classifications and concordances and best practices with respect to processing or analytical procedures • create reports which are automatically updated whenever they are opened • perform graphics-based analysis

  8. Results • Phase 1 – I-O Division • standardization of the analytical process • enhanced data coherency • standardized and normalized analytical procedures which allows the division to operate with less experience staff • more transparent, repeatable and efficient analysis of data • Phase 2 – SNA • the success in I-O led to an SNA-wide warehouse

  9. I-O Data WarehouseArchitecture

  10. Data WarehouseFramework

  11. Technology • Microsoft Data Warehouse Framework for SQLServer 2000 • currently working on the SQL Server 2005 version • includes the MS Enterprise Manager, Data Transformation Services (DTS) and Analysis Services • fully integrated with Microsoft Excel XP

  12. Technology • Cubes • based on the OLAP standard • Data Transformations • any Extract, Load, Transform (ETL) product can be used but the team has standardized on the Microsoft product • API • XML for Analysis standard • uses Microsoft’s MDX query language

  13. Technology • Reporting and End-user Tools • EzWeb OLAP Report Browser and EzWeb OLAP Report Designer • developed by the Data Warehouse Web team at STC • provides a web like interface that conforms to the Government of Canada’s Look and Feel Standard • Microsoft Office Web Components (OWC) Pivot Table provides OLAP functionality • can navigate from one OLAP report to another • Data Marts provide users with a customized subset of data and reports • Excel XP • Business Intelligence tools, Data Mining tools, etc. • STCWiki (in pilot mode) • implemented using MediaWiki (product used by Wikipedia) • two-way communications with STC’s Integrated Metadata database

  14. Lessons Learned • Technical • standardized framework greatly reduces development costs • loosely connected customized data marts are more effective: • partitions the effort involved in harmonization and the management of security and access rights • allows users to customize their personal portal to list only those sources which are of business interest to them • appropriate for any type of data (operational, data processing, analysis of published data, etc.)

  15. Lessons Learned • Business • the real challenge lies with how data should be processed, analysed and classified (data harmonization) • value gained by harmonization usually results in modified working procedures • start by having good analytical tools to allow business units to detect problems and improve and adapt the methods used to ensure that the data is of high quality

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