Purchase Orders Over €20,000 Q4 2018

Spending records

Payment date^*	Supplier	Description	Kind	Amount
31 Dec 2018	OFFICE OF PUBLIC WORKS	Office Premises Expenses	Purchase Order	€30,000.00
31 Dec 2018	DOMINO PEOPLE LTD	ICT Software Maintenance	Purchase Order	€98,358.76
31 Dec 2018	KEFRON CONSULTING	Outsourcing Data Entry Census Pilot	Purchase Order	€102,336.00
31 Dec 2018	ALEMBA LTD	ICT Software Maintenance	Purchase Order	€25,038.57
31 Dec 2018	SURESKILLS	ICT Software Maintenance	Purchase Order	€43,657.50
31 Dec 2018	NEOPOST IRELAND LTD	ICT Equipment	Purchase Order	€24,764.82
31 Dec 2018	ORACLE EMEA LTD	ICT Software Maintenance	Purchase Order	€54,076.05
31 Dec 2018	LOCAL GOVERNMENT MANAGEMENT	ICT Services	Purchase Order	€29,435.00
31 Dec 2018	DEPT OF PUBLIC EXPENDITURE AND	Shared Service Charges	Purchase Order	€27,128.00
31 Dec 2018	GEO DIRECTORY	ICT Software Maintenance	Purchase Order	€28,905.00
31 Dec 2018	SPINNAKER SUPPORT LTD	ICT Software Maintenance	Purchase Order	€23,616.00
31 Dec 2018	SAS INSTITUTE LTD.	ICT Software Maintenance	Purchase Order	€867,546.06
31 Dec 2018	MICROMAIL LTD.	ICT Software Maintenance	Purchase Order	€72,451.35
31 Dec 2018	MICROMAIL LTD.	ICT Software Maintenance	Purchase Order	€38,896.68
31 Dec 2018	EIR (LAN COMMUNICATIONS)	ICT Software Maintenance	Purchase Order	€22,924.72
31 Dec 2018	CLUB TRAVEL LTD.	Travel Services	Purchase Order	€22,979.36

^* Payment date may be the end of the reporting quarter when the entity does not publish an exact date.

How to read these figures

These are reported values from published purchase order and payment records — not verified cash paid, and not total spending by this organisation. A row may be a purchase order, a payment, or another reported transaction; the source files often do not say which.

Coverage and quality vary. Some fields are blank, supplier names are free text (the same firm can appear under many labels), and descriptions are inconsistent rather than a controlled taxonomy. An amount alone says nothing about value for money and it may or may not include VAT.

Records are retrieved from each organisation’s published files such as spreadsheets, PDFs, and other formats of uneven quality. Extraction techniques (including automated parsing) can introduce gaps, misreads, or incomplete rows when source layout or quality is poor. Treat the data as a starting point for investigation, not a definitive ledger.

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