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MtS-ISL-SUD -SDNS. Statistical Data Collection and Processing System MtS-ISL-SUD -SDNS. The Czech National Bank, September 2009. Jindra Ivanovova and Irena Zamecnikova Information Systems Department, Monetary and Statistics Department. Contents.
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MtS-ISL-SUD-SDNS StatisticalData Collection and ProcessingSystem MtS-ISL-SUD-SDNS The Czech National Bank, September 2009 Jindra Ivanovova and Irena Zamecnikova Information Systems Department, Monetary and Statistics Department
Contents • Introduction of the System for data collection and processing at the CNB • Basic features of the solution • Architecture of the system • The organizational arrangement and operation
The Areas of the System Usage • The data collection for : • statistics (Monetary and financial statistics, Balance of payments statistics, National accounts statistics, Security - by - Security ) • supervision (Banks, Insurance industry, Capital market, Pension scheme industry, Credit Unions ) • Wide range of information for the core CNB´s activities (monetary policy, financial stability policy, financial market supervision, national accounts, statistics, etc.) • The group of our respondents : Banks , Funds, Investment companies, Pension funds, Insurance companies, Brokers, Credit Unions, Other financial intermediaries, Non-financial institutions.
The Architecture of MtS-ISL-SUD-SDNSto be continued Reporting agent CNB STRUKT Excel, SQL,... Information service Organizational model Database IC Information model EDI Users‘ outputs Internet Analytical tools Datapreparation sw Database SUD
The Basic Features of the System • No programming during the implementation of new statements and changes • The unified description of statements by using metadata • The fully automatic data processing controlled by metadata • One data warehouse only (Data and Metadata)
The Methodology • What does the methodology contain : • Methodical specification of data (contents of data and reports = WHAT ) • Reporting duties ( WHO and WHEN ) • Validation rules (for quality - checking ) • Semantic data description (No tables) • The unified principle of methodical description in all business areas • The basic phases of methodology (creation, validation, presentation..) • Particularity – an update of one object implies automatically changes of the dependent objects
The Data Warehouse • Basic principle • Multidimensional cube • The definition of data is included • The semantic description of the data • D1 = IP1 ( P1.a,P2.b,P3.b) • Time series from 1993 • The history of statements (all data including canceled data are accessible to users ) • New data, correction and cancelation • On-line users‘ access
Variable Variable values data ofrespondent X as of 30 June2009 Occurence values Data warehouse –to be continued Liabilities Liabilities in CZK General variable Currency Variable dimension Respondent, Time period 512345.05 (Other dimension )
Communication and Solution on the Respondents‘ Sideto be continued • EDI solution: • Interfaces defined by the CNB : data, communication and security • Detailed procedural and organizational rules defined by the CNB • The CNB´s application and the respondents‘ applications based on the similar principles • A high level of security: electronic signature and possible encryption
Communication and Solution on the Respondents‘ Side • Internet solution (SDNS) • On-line reporting • Secure logon (PKI Entrust certificate or user‘s name & password) • Electronic signature (based on PKI Entrust certificate or on the qualified certificates), encrypted communication • Web services solution (SDNS-Web-Services) • Ten Web-Services for methodological and operating information retrieval defined by the CNB • Web-Service for sending data defined by the CNB • Secure logon (user‘s name & password) • Electronic signature (based on the qualified certificates) , encrypted communication
The Internet Application SDNS • Public access • Presentation of methodologies for all business areas in structured form • Registered access • Presentation of methodology of all respondent-related statements • Presentation of data transmitting schedule • Data input • Data typing supported by detailed methodological description • File upload in the xml format prepared by the suitable application • Possibility to compute summary values from detailed values • Possibility of preliminary checks • Data sending • Presentation of processing results
The Automated processing– to be continued • The basic phases of data processing: collection, quality checking, storing, sending response • Operation is controlled via metadata: • What kind of information: described by methodology • What kind of checks: described by methodology • What kind of activity: described by operational metadata • Operational parameters: • Statement priority • Number of currently running batches • Maximum duration of one batch processing • Time limit for sending processing results to respondents, etc.
The Automated processing Some facts: • Messages received per year : about 40 000 • Processing results and reminders sent per year: about 50 000 • Daily received messages in the peak: about 500 • Daily sent messages in the peak: about 700 • Time limit between receiving messages and sending processing results: 20 min. at least for 95% messages received in a month
Organizational Arrangement to be continued • Matter-of-fact administration • Methodical supervision of all business area methodologies • Administration of shared objects: dimensions (parameters), code lists , hierarchic classifications, data types,… • Technical administration • Administration of system and operational parameters • Monitoring of data processing • Users‘ support
Organizational Arrangement • Users – methodical designer • Design of a statement methodological description with the aid of the system rules, objects and tools • Users • Data selection and data aggregation • Numerical series (time, respondents) • Information about the data quality at the users‘ disposal • Users – programmer • Design and programming of output applications
Basic Feature at the Outset • The conception of the whole system at the outset • The system has been outsourced (larger expenses but saved personnel resources - thousands of man-days) • The users used the same methods, tools: prescribed (limited)rules increased the efficiency
Summary • Advantage for respondents • one system for all reporting to the CNB • no software is needed („small“ reporting extent) • possibility to check data before transmitting • quick result response • Advantage for the CNB • one system for all reporting agents (large, small, financial, non-financial, ..) • no software distribution • increasing data quality
Finally Thank you for your attention ! Any questions? • The web-side of the internet application SDNS (in Czech only) https://wsn.cnb.cz/ewi/