Purchase Orders in Excess of €20,000 Q4 2018

Spending records

Payment date^*	Supplier	Description	Kind	Amount
19 Dec 2018	Media Com	Purchase order	Purchase Order	€65,000.00
18 Dec 2018	Davy Target Investments c/o Bannon (RENT)	Purchase order	Purchase Order	€28,982.19
17 Dec 2018	ESRI	Purchase order	Purchase Order	€75,000.00
12 Dec 2018	Neo Post Postal Credit	Purchase order	Purchase Order	€35,000.00
10 Dec 2018	CWSI	Purchase order	Purchase Order	€37,050.00
15 Nov 2018	KILKENNYEDUCATIONCENTRE	Purchase order	Purchase Order	€66,864.00
15 Nov 2018	CDW Limited	Purchase order	Purchase Order	€90,611.67
05 Nov 2018	Mediavest t/a Spark Foundry	Purchase order	Purchase Order	€65,811.15
30 Oct 2018	UNITY TECHNOLOGY SOLUTIONS	Purchase order	Purchase Order	€24,000.00
30 Oct 2018	MICROMAIL LTD	Purchase order	Purchase Order	€49,101.71
25 Oct 2018	NOVOSCO LTD	Purchase order	Purchase Order	€89,444.22
22 Oct 2018	Road Safety Authority (RSA)	Purchase order	Purchase Order	€62,093.47
10 Oct 2018	Arkphire Ireland Limited	Purchase order	Purchase Order	€47,359.04
10 Oct 2018	VERSION1SOFTWARE	Purchase order	Purchase Order	€36,623.25
03 Oct 2018	HODSONBAYHOTEL	Purchase order	Purchase Order	€26,500.00

^* 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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