Purchase Orders Over €20,000 Q3 2014

Spending records

Payment date^*	Supplier	Description	Kind	Amount
30 Sep 2014	VIL (ECS)	Switches for 7/9 MR,	Purchase Order	€27,501.57
30 Sep 2014	Storm Technology	Sparepoint support Aug'14,	Purchase Order	€27,954.52
30 Sep 2014	Eolas Recruitment	Employment costs	Purchase Order	€25,916.10
30 Sep 2014	VIL (ECS)	4 x 5800's for Tull & 7-9,	Purchase Order	€28,709.38
30 Sep 2014	Price Waterhouse	Consulting 40 days May to Aug,	Purchase Order	€36,900.00
30 Sep 2014	Dell Computer	Dell s4810p switches,	Purchase Order	€21,863.25
30 Sep 2014	DQ Networks Ltd	Inv 15411 Re July'14,	Purchase Order	€20,579.38
30 Sep 2014	Storm Technology	Sharepoint Support July'14,	Purchase Order	€48,414.65
30 Sep 2014	Dell Computer	Equalogic ps6210 XV SAN,	Purchase Order	€23,029.29
30 Sep 2014	Dell Computer	Equalogic ps6210 xs SAN,	Purchase Order	€48,566.80
30 Sep 2014	Vodafone Irel. Limited	HP kit & filters Aurora Link,Filters,	Purchase Order	€233,200.12
30 Sep 2014	Queen's University	PS Reform Research Fellowship,	Purchase Order	€23,875.00
30 Sep 2014	Storm Technology	SharePoint Support for June'14,	Purchase Order	€49,083.27
30 Sep 2014	Public Appointments	Professional Services CIO,	Purchase Order	€24,600.00

^* 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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