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Re-engineering of the business statistics A knowledge database

Re-engineering of the business statistics A knowledge database Identifying the needs : which information for whom Output Input Needs Institutions Register Administrative Data Profiling Surveys Variables Applications or statistics An integrated approach Statistics EU Business

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Re-engineering of the business statistics A knowledge database

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  1. Re-engineering of the business statistics A knowledge database

  2. Identifying the needs : which information for whom Output Input Needs Institutions Register Administrative Data Profiling Surveys Variables Applications or statistics

  3. An integrated approach Statistics EU Business Statistics Indicators Micro-data Variables Statistics OECD Statistics UN Statistics FSO Others

  4. Harmonizing the metadata Vertical harmonizing Sources of information Format Observation Unit Definitions VARIABLES Reference Year Dimensions (Geography, time, etc..) Periodicity Quality Methods (e.g. Missing values) Other classifications Economic Activity horizontal harmonizing

  5. How to go further with these metadata : Clustering Periodicity Definitions Variables Observation unit Economic Activity

  6. Collecting the data Clusters Sources of information Blocks for collecting the data • Optimizing • the use of registers • the use of administrative data • the processes of data collection • the consistency and quality of data • Minimizing • the statistical burden on enterprises • the costs of statistics

  7. Data Model

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