ata (geographic & time dimension) in a sufficient data quality exists, rendering the implementation feasible. The proposed high-level data model depicted in the figure, is a star schema with a number of fact tables surrounded by a set of common (or conformGovernment Finance Divisions manage the execution of the fiscal policy:

• management of the taxation and tax audit process
• management of the budget execution process

Within the taxation framework, each State aims to support its taxation policy:

• Support the efficient capture and processing of tax declarations
• Assure the collection of tax revenue according to plans
• Manage and reduce the risk of Citizen non-compliance: reduce tax evasion levels and fight financial crime
• Support the analysis of alternative future tax policies and relevant decision making, e.g. consequences of a change on State revenue
• Enhance the Citizen experience, during the tax compliance process (e.g. offer e-government services).

It is proposed that a ‘tax monitoring data mart’, be designed based on the dimensional model approach. A proposed high–level logical data model is depicted in the picture (check resource below), based on the assumption that a critical mass of data (geographic & time dimension) in a sufficient data quality exists, rendering the implementation feasible. The proposed high-level data model depicted in the figure, is a star schema with a number of fact tables surrounded by a set of common (or conformeion policy:

• Support the efficient capture and processing of tax declarations
• Assure the collection of tax revenue according to plans
• Manage and reduce the risk of Citizen non-compliance: reduce tax evasion levels and fight financial crime
• Support the analysis of alternative future tax policies and relevant decision making, e.g. consequences of a change on State revenue
• Enhance the Citizen experience, during the tax compliance process (e.g. offer e-government services).

It is proposed that a ‘tax monitoring data mart’, be designed based on the dimensional model approach. A proposed high–level logical data model is depicted in the picture (check resource below), based on the assumption that a critical mass of data (geographic & time dimension) in a sufficient data quality exists, rendering the implementation feasible. The proposed high-level data model depicted in the figure, is a star schema with a number of fact tables surrounded by a set of common (or conformcrime

Support the analysis of alternative future tax policies and relevant decision making, e.g. consequences of a change on State revenue

Enhance the Citizen experience, during the tax compliance process (e.g. offer e-government services).

It is proposed that a ‘tax monitoring data mart’, be designed based on the dimensional model approach. A proposed high–level logical data model is depicted in the picture (check resource below), based on the assumption that a critical mass of data (geographic & time dimension) in a sufficient data quality exists, rendering the implementation feasible. The proposed high-level data model depicted in the figure, is a star schema with a number of fact tables surrounded by a set of common (or conform. It is proposed that a ‘tax monitoring data mart’, be designed based on the dimensional model approach. A proposed high–level logical data model is depicted in the picture (check resource below), based on the assumption that a critical mass of data (geographic & time dimension) in a sufficient data quality exists, rendering the implementation feasible. The proposed high-level data model depicted in the figure, is a star schema with a number of fact tables surrounded by a set of common (or conformata (geographic & time dimension) in a sufficient data quality exists, rendering the implementation feasible. The proposed high-level data model depicted in the figure, is a star schema with a number of fact tables surrounded by a set of common (or conformed) dimensions. The fact tables are of the ‘accumulating snapshot’ type, meaning that they accumulate information throughout each individual taxation transaction lifecycle. Most taxation types have a yearly lifecycle (i.e. personal income tax). VAT involves more frequent transactions. This data modeling approach offers advantages, compared to the operational systems data models (usually normalized database schemas):· The model is quite simple and can be easily understood by business (non-IT) users · The model’s simplicity has also positive consequences to the performance of queries Based on this infrastructure which would monitor the taxation lifecycle of various taxes, the Government can produce information:· on a taxpayer’s holistic view (all transactions she / he made) and support the non-compliance risk scoring and general tax audit process · on tax collection time-series analysis· on the time it takes between reception of tax declarations & clearance· on the tax col