Payments Over €20,000 Q2 2019

Spending records

Payment date^*	Supplier	Description	Kind	Amount
28 Jun 2019	JEROME RYAN	RENT	Purchase Order	€25,000.00
26 Jun 2019	FDY CIVIL ENGINEERING & CONSTRUC	PROJECT 231	Purchase Order	€219,891.26
26 Jun 2019	DARWIN CONSTRUCTION LTD	BUILDING WORKS	Purchase Order	€32,661.35
07 Jun 2019	PAUL FLYNN CONSTRUCTION LTD	PROJECT NCP16	Purchase Order	€58,766.23
01 Jun 2019	KBR FOOD SERVICE EQUIPMENT	EQUIPMENT	Purchase Order	€180,237.46
01 Jun 2019	DOLPHIN ELECTRICAL	ELECTRICAL GOODS	Purchase Order	€152,280.28
22 May 2019	SKM MANUFACTURING TRADING AS SKM	PROJECT 239	Purchase Order	€37,076.44
22 May 2019	FDY CIVIL ENGINEERING & CONSTRUC	PROJECT 231	Purchase Order	€144,952.61
03 May 2019	PAUL FLYNN CONSTRUCTION LTD	PROJECT NCP16	Purchase Order	€51,942.97
03 May 2019	BRIAN MCCARTHY & ASSOCIATES	BUILDING WORKS	Purchase Order	€22,816.50
03 May 2019	BRICKMORE CONSTRUCTION LTD	PROJECT NO. 222	Purchase Order	€115,103.16
28 Apr 2019	RMC - RESTOR MANAGE CONSULT	BUILDING WORKS	Purchase Order	€69,650.00
18 Apr 2019	UNILIFT LTD	RENT	Purchase Order	€252,369.86
15 Apr 2019	FDY CIVIL ENGINEERING & CONSTRUC	PROJECT 231	Purchase Order	€129,178.52
12 Apr 2019	RMC - RESTOR MANAGE CONSULT	BUILDING WORKS	Purchase Order	€22,700.00

^* 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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