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Data mining construction project information to aid project management
Thesis (MEng)--Stellenbosch University, 2018.
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| Format: | Thesis |
| Language: | en_ZA |
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Stellenbosch : Stellenbosch University
2018
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| _version_ | 1867613814970646528 |
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| access_status_str | Open Access |
| author | Botha, Louis Johan |
| author2 | Wium, Jan |
| author_browse | Botha, Louis Johan Wium, Jan |
| author_facet | Wium, Jan Botha, Louis Johan |
| author_sort | Botha, Louis Johan |
| collection | Thesis |
| dc_rights_str_mv | Stellenbosch University |
| description | Thesis (MEng)--Stellenbosch University, 2018. |
| format | Thesis |
| id | oai:scholar.sun.ac.za:10019.1/105088 |
| institution | Stellenbosch University (South Africa) |
| language | en_ZA |
| last_indexed | 2026-06-10T12:42:07.859Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository |
| publishDate | 2018 |
| publishDateRange | 2018 |
| publishDateSort | 2018 |
| publisher | Stellenbosch : Stellenbosch University |
| publisherStr | Stellenbosch : Stellenbosch University |
| record_format | dspace |
| source_str | SUNScholar — Stellenbosch University Repository |
| spelling | oai:scholar.sun.ac.za:10019.1/105088 Data mining construction project information to aid project management Botha, Louis Johan Wium, Jan Stellenbosch University. Faculty of Engineering. Dept. of Civil Engineering. Data Mining Construction -- Management Project management Construction Industry UCTD Thesis (MEng)--Stellenbosch University, 2018. ENGLISH ABSTRACT: Internationally, the popularity of data mining and its use in a business context has grown rapidly in many sectors. The organisations that utilise data mining have experienced significant gains in efficiency, productivity and profitability. The utilisation of data mining within the construction industry has however lagged behind other sectors, especially in South Africa. Data mining to aid project management has seen limited application. The leader in applying data mining to improve project management has been the software development sector as it is plagued by project cost and time overruns and a high number of failed projects. The construction industry in South Africa suffers from similar cost and time overruns, yet data mining in the construction sector has been limited. Few applications exist of data mining to improve the management of construction projects. The process followed to implement a data mining application has been largely focused on the specific statistical and technical details of the data preparation and the data mining model. These details are inherently application specific and do not provide a general data mining process. Guides that define and demonstrate the general data mining process are limited or outdated, with no such guide existing for data mining in the construction sector. The research examines the application of data mining to the construction sector and to the improvement of project management in the software development sector. From these sources and a discussion of construction projects in South Africa, a comprehensive data mining process is synthesised. The data mining process is discussed in the context of the construction sector in South Africa and construction sector personnel with limited experience of data mining. A number of user-friendly, yet rigorous, data mining resources are presented. A selection of these resources are applied to a real project dataset obtained from the Western Cape Government’s Department of Public Works’ internal project database. A data mining application is developed by adhering to the data mining process defined within the research. The results were discussed along with several salient lessons learned. AFRIKAANSE OPSOMMING: Internasionaal het die gewildheid van data-ontginning en die gebruik daarvan in 'n besigheidskonteks vinnig in baie sektore gegroei. Die organisasies wat data-ontginning gebruik, het aansienlike winste in doeltreffendheid, produktiwiteit en winsgewendheid ervaar. Die gebruik van data-ontginning in die konstruksiebedryf het veral in Suid-Afrika agterweë gebly. Data-ontginning om projekbestuur te help, het beperkte toepassing gesien. Die leier in die toepassing van data-ontginning om projekbestuur te verbeter, was die sagtewareontwikkelingsektor aangesien dit gepla word deur projekkoste en tydoorskrydings en 'n groot aantal mislukte projekte. Die konstruksiebedryf in Suid-Afrika ly aan soortgelyke koste- en tydoorskrydings, maar data-ontginning in die konstruksiesektor is beperk. Min toepassings van data-ontginning om die bestuur van konstruksieprojekte te verbeter, bestaan. Die proses wat gevolg is om 'n data-ontginnings aansoek te implementeer, het hoofsaaklik gefokus op die spesifieke statistiese en tegniese besonderhede van die data-voorbereiding en die data-ontginningsmodel. Hierdie inligting is inherent toepassingspesifiek en is geneig om af te sien daarvan om algemene advies te gee. Gidse wat die algemene dataontginningsproses definieer en demonstreer is beperk of verouderd en geen sodanige gids vir data-ontginning in die konstruksiesektor bestaan nie. Die navorsing ondersoek die toepassing van data-ontginning aan die konstruksiesektor en die verbetering van projekbestuur in die sagteware-ontwikkelingsektor. Uit hierdie bronne en 'n bespreking van konstruksieprojekte in Suid-Afrika is 'n omvattende data-ontginningsproses gesintetiseer. Die data-ontginningsproses is bespreek in die konteks van die konstruksiesektor in Suid-Afrika en konstruksiesektorpersoneel met beperkte ervaring van data-ontginning. 'n Aantal gebruikersvriendelike dog streng data-ontginningsbronne is aangebied. 'n Seleksie van hierdie hulpbronne is toegepas op 'n werklike projekdatastel wat verkry is van die Wes- Kaapse regering se Departement van Openbare Werke se interne projekdatabasis. 'n Dataontginningstoepassing is ontwikkel deur te voldoen aan die data-ontginningsproses wat binne die navorsing gedefinieer is. Die uitslae is bespreek met verskeie belangrike lesse wat geleer is. 2018-11-27T19:17:49Z 2018-12-07T06:58:56Z 2018-11-27T19:17:49Z 2018-12-07T06:58:56Z 2018-12 Thesis http://hdl.handle.net/10019.1/105088 en_ZA Stellenbosch University 153 pages : illustrations application/pdf Stellenbosch : Stellenbosch University |
| spellingShingle | Data Mining Construction -- Management Project management Construction Industry UCTD Botha, Louis Johan Data mining construction project information to aid project management |
| title | Data mining construction project information to aid project management |
| title_full | Data mining construction project information to aid project management |
| title_fullStr | Data mining construction project information to aid project management |
| title_full_unstemmed | Data mining construction project information to aid project management |
| title_short | Data mining construction project information to aid project management |
| title_sort | data mining construction project information to aid project management |
| topic | Data Mining Construction -- Management Project management Construction Industry UCTD |
| url | http://hdl.handle.net/10019.1/105088 |
| work_keys_str_mv | AT bothalouisjohan dataminingconstructionprojectinformationtoaidprojectmanagement |