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Integrated Statistical Production System WITH GSBPM

Integrated Statistical Production System WITH GSBPM. Rahul Kumthekar & Philip Bakos 17 September 2019. FIS Integrated Statistical Data Production System. Organize workflows and reporting tools available within MAP Enterprise. Users. C. Out-of-the-Box Development and User Interfaces.

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Integrated Statistical Production System WITH GSBPM

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  1. Integrated Statistical Production System WITH GSBPM Rahul Kumthekar & Philip Bakos 17 September 2019

  2. FIS Integrated Statistical Data Production System Organize workflows and reporting tools available within MAP Enterprise Users C Out-of-the-Box Development and User Interfaces Desktop Tools & Connectors Applications FAME Data Loading Toolkit with SDMX Data Model FEDM – SDMX Dashboard Data Loaders Web Services • FAME Data Warehouse • Time Series Storage • Advanced Time Series Analytics • SDMX Data Model BI Web Reports Onsite Data Server Optional Managed Data Services SQL Access • MySQL Server • MetadataManagement MarketMap Analytical Platform

  3. FIS Integrated Statistical Data Production Framework Implements 6 of the critical 8 processes identified in the General Statistical Business Process Model via combined software and services

  4. FIS ISDP Workflow To showcase FIS Integrated Statistical Data Production and to highlight implementation of the Generic Statistical Business Process Model (GSBPM) BOP Current & Financial Accounts

  5. GSBPM Recommended Database InfrastructureSDMX driven metadata management in SQL with statistical data persistence in FAME ADBMS B-Tree Data Data is stored in Discrete Objects rather than rows and columns. Objects can be combined, aggregated and disaggregated. Data can also be statistically modelled over time via FAME’s built in 4GL FAME has automatic frequency conversion built-in. Statistical Data is stored in B-Tree vector format with attributes about statistical Data stored in headers

  6. Upload SDMX DSD DESIGN & Build

  7. Upload DSD via FEDM Data ExchangeProduction of object dimension names, codes and code lists to assist in collection, building and analyzation phases of statistical data production

  8. Classify and Code objects via SDMX Key Families SDMX Attributes to FAME Object Attributes

  9. Database Infrastructure Collect

  10. MarketMap Analytic Data Loading & Collection Multi-threaded metadata driven data loading toolkit with loaders to map content from a variety of sources MADL UPD File Loader Converter Target Databases Data Files Profile Metadata Generator UPD Metadata Match Metadata Raw Metadata Split Metadata Logical Metadata Metadata Files

  11. Data Validations Applied Process & Analyse

  12. Process step with GSBPM This step of the GSBPM is mainly to classify, review, validate, calculate weight and to finalise the data files. FEDM can complete the GSBPM Process step in numerous ways • Data Browsing in Tree Format • Data Validation: Individual data validations or pre-set validation rules before uploading of data • Notifications when validation rule is not met – Triggers fail alert • Validation rules can be set as hard, soft or a custom validation equation • Golden copy of data can be created effortlessly with FEDM’s Data Promotion option

  13. Graphs Graphs can be viewed online in FEDM or downloaded into Excel or PDF format Graphs can also be created or viewed by using metadata parameters

  14. Online Web Reporting Dissemination

  15. Time Intelligent interactive Reporting Design reports which has seamless access to data objects, formulas and functions. • Communicate date orientated parameters and custom inputs via interactive prompts • Export FEDM reports to PDF, Excel or CSV

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