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National Data Centre and Financial Statistics Office: A Conceptual Design for Public Data Management

Author

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  • Cakir, Murat

Abstract

Data processes run by states, governments and the like have been a great deal and as old as the modern human history. Data had always been important. Tons were collected and siloed, but never in the past had its importance been felt as much as it had been when the last crisis broke out in 2008. Because these tons of data either, as some were redundant and occupying large spaces with huge storage costs, were not useful given the processing power and due to outdated mind-sets, or were not even the tiniest portion of the data necessary to do analysis , the experts realised. With the advances in the digital world dealing with data has become easier. Combined with the urgent needs and demands from the bottom up and top down there now is more enlightened and educated perception of data and whatever its extensions are, and its / their potential use, though a little bit late. In the late 90s, however, things were not as computerised and DataeXve was not as Big as it is today, and manual operations dominated the automated ones. There were definitely inefficiencies in DataeXve. Still, even then, there were efforts to improve these processes. This work focuses on one of those early efforts.

Suggested Citation

  • Cakir, Murat, 2014. "National Data Centre and Financial Statistics Office: A Conceptual Design for Public Data Management," MPRA Paper 53869, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:53869
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    File URL: https://mpra.ub.uni-muenchen.de/74410/9/MPRA_paper_74410.pdf
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    Cited by:

    1. repec:bis:bisifc:45-06 is not listed on IDEAS
    2. Murat Cakir, 2017. "A conceptual design of "what and how should a proper macro-prudential policy framework be?" A globalistic approach to systemic risk and procuring the data needed," IFC Bulletins chapters,in: Bank for International Settlements (ed.), Uses of central balance sheet data offices' information, volume 45 Bank for International Settlements.

    More about this item

    Keywords

    Data management; Data Centralisation; Big Data and Systemic Risk Diagnosis;

    JEL classification:

    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • C89 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • E01 - Macroeconomics and Monetary Economics - - General - - - Measurement and Data on National Income and Product Accounts and Wealth; Environmental Accounts
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation
    • Y1 - Miscellaneous Categories - - Data: Tables and Charts

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