Purchase Orders Over €20,000 Q4 2022

Spending records

Payment date^*	Supplier	Description	Kind	Amount
31 Dec 2022	OILIUNA TRAINING LTD	Medical Administration	Purchase Order	€103,917.78
31 Dec 2022	OILIUNA TRAINING LTD	Community Health Services Tallaght TC	Purchase Order	€61,396.89
31 Dec 2022	OILIUNA TRAINING LTD	Workplace & Facilities Management L3	Purchase Order	€32,803.90
31 Dec 2022	KT BUSINESS SKILLS LTD	Warehouse Operative	Purchase Order	€60,113.40
31 Dec 2022	HARTLEY PEOPLE LTD	ICT Software Developer	Purchase Order	€113,975.35
31 Dec 2022	HARTLEY PEOPLE LTD	KICK START YOUR OWN BUSINESS	Purchase Order	€43,309.40
31 Dec 2022	C T CREATIVE TRAINING LTD	QQI Domestic BER course	Purchase Order	€51,499.88
31 Dec 2022	C T CREATIVE TRAINING LTD	Advanced Bicycle Technican Certificate	Purchase Order	€51,325.36
31 Dec 2022	OILIUNA TRAINING LTD	Python Programming - Route 1	Purchase Order	€64,255.80
31 Dec 2022	OILIUNA TRAINING LTD	CompTIA Cybersecurity Analyst - Route 1	Purchase Order	€33,825.75
31 Dec 2022	C T CREATIVE TRAINING LTD	Aircraft Spray Painting	Purchase Order	€70,516.73
31 Dec 2022	OILIUNA TRAINING LTD	Health Services Supervisory Mgt Skills	Purchase Order	€65,421.74
31 Dec 2022	OILIUNA TRAINING LTD	Intellectual Disability Health Systems	Purchase Order	€108,081.74

^* 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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