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[{"key": "dc.contributor.advisor", "value": "Luoma, Eetu", "language": "", "element": "contributor", "qualifier": "advisor", "schema": "dc"}, {"key": "dc.contributor.author", "value": "Ojansuu, Ilari", "language": "", "element": "contributor", "qualifier": "author", "schema": "dc"}, {"key": "dc.date.accessioned", "value": "2018-06-07T07:45:27Z", "language": null, "element": "date", "qualifier": "accessioned", "schema": "dc"}, {"key": "dc.date.available", "value": "2018-06-07T07:45:27Z", "language": null, "element": "date", "qualifier": "available", "schema": "dc"}, {"key": "dc.date.issued", "value": "2018", "language": "", "element": "date", "qualifier": "issued", "schema": "dc"}, {"key": "dc.identifier.uri", "value": "https://jyx.jyu.fi/handle/123456789/58423", "language": null, "element": "identifier", "qualifier": "uri", "schema": "dc"}, {"key": "dc.description.abstract", "value": "Erilaiset liiketoiminnan dataa jalostavat j\u00e4rjestelm\u00e4t ovat her\u00e4tt\u00e4neet mielenkiintoa organisaatioissa. Laaja datan keruu ja mallintaminen mahdollistavat organisaatioiden p\u00e4\u00e4t\u00f6ksenteon siirtymisen entist\u00e4 enemm\u00e4n intuitiivisesta p\u00e4\u00e4t\u00f6ksenteosta datapohjaiseen p\u00e4\u00e4t\u00f6ksentekoon. Tarkoituksenmukaiset ennusteet tarjoavat organisaatioille pohjaa niin strategiselle, kuin my\u00f6s operatiiviselle p\u00e4\u00e4t\u00f6ksenteolle. Ennusteet tarjoavat siis mahdollisesti merkitt\u00e4v\u00e4\u00e4 hy\u00f6ty\u00e4 organisaation toiminnalle ja kilpailukyvylle. Tutkielma tehtiin kirjallisuuskatsauksena ja tutkielman tarkoituksena oli tarkastella teko\u00e4lyn hy\u00f6dynt\u00e4mist\u00e4 liiketoiminnan ennakoinnin n\u00e4k\u00f6kulmasta. Tutkielmassa tarkasteltiin teko\u00e4lyn sovelluksien ominaisuuksia ja verrattiin n\u00e4it\u00e4 ennakoivan analytiikan vaatimiin ominaisuuksiin. Teko\u00e4ly ja erityisesti neuroverkot tarjoavat potentiaalisen ratkaisun perinteisen ennakoivan analytiikan kohtaamiin ongelmiin, ja koneellinen tietojenk\u00e4sittely soveltuu hyvin massiivisten datam\u00e4\u00e4rien k\u00e4sittelyyn. Liiketoiminnasta ker\u00e4ttyyn dataan sis\u00e4ltyy usein paljon ep\u00e4lineaarisia asiayhteyksi\u00e4. Neuroverkoilla pystyt\u00e4\u00e4n tehokkaasti tunnistamaan t\u00e4llaiset suhteet datan pohjalta, ja usein teko\u00e4lyll\u00e4 toimiva j\u00e4rjestelm\u00e4 kykenee osoittamaan asiayhteyksi\u00e4, joita ei perinteisill\u00e4 menetelmill\u00e4 ole tunnistettu. Aihealueen tutkimukset osoittavat, ett\u00e4 teko\u00e4ly soveltuu monipuolisesti liiketoiminnan erilaisiin ennakoinnin teht\u00e4viin. Ihmisen ja koneen p\u00e4\u00e4t\u00f6ksenteon vahvuudet t\u00e4ydent\u00e4v\u00e4t toistensa heikkouksia ja teko\u00e4ly\u00e4 voidaankin hy\u00f6dynt\u00e4\u00e4 my\u00f6s k\u00e4ytt\u00e4j\u00e4\u00e4 tukevana ty\u00f6kaluna. Laajempi teko\u00e4lyn k\u00e4ytt\u00f6\u00f6notto liiketoiminnan ennakoinnin teht\u00e4viin vaatii lis\u00e4tutkimusta aiheesta, jotta voidaan muodostaa kattavat ohjeistukset oikeaoppisten j\u00e4rjestelmien kehitt\u00e4miselle.", "language": "fi", "element": "description", "qualifier": "abstract", "schema": "dc"}, {"key": "dc.description.abstract", "value": "Applications that focus on refining collected data are becoming more popular amongst organizations. The information gained from processing and modeling of business data is moving organizations from intuitive decision-making into more data-based decision-making. Appropriate forecasting offers a basis for strategic and operative decision-making in organizations. Forecasting is potentially able to provide significant benefits for the organizations competitivity. This bachelors\u2019 thesis is a literature review and the purpose of this thesis was to find out how artificial intelligence could be used in business forecasting. The thesis compares artificial intelligence applications and the demands of predictive analytics. Artificial intelligence and especially artificial neural networks provide a potential solution to the restrictions of traditional predictive analysis. The mechanical processing of computers is also appropriate for the needs of massive data analysis. The data collected from business activities often contains significant amounts of nonlinear relationships. Artificial neural networks are capable of identifying such relationships and neural networks can often showcase relationships in the data that have not been recognized in the past using traditional methods. The research on the field indicates that artificial intelligence fits well for business forecasting. The strengths of human brain and artificial intelligence reinforce the weaknesses of one another, and therefore one approach is to use artificial intelligence to create a supporting system for a human user. Broader implementation of artificial intelligence in business forecasting requires more thorough research on the field, so guidelines for the development of such forecasting systems can be created.", "language": "en", "element": "description", "qualifier": "abstract", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Submitted by Paivi Vuorio (paelvuor@jyu.fi) on 2018-06-07T07:45:27Z\nNo. of bitstreams: 0", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Made available in DSpace on 2018-06-07T07:45:27Z (GMT). No. of bitstreams: 0\n Previous issue date: 2018", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.format.extent", "value": "25", "language": "", "element": "format", "qualifier": "extent", "schema": "dc"}, {"key": "dc.language.iso", "value": "fin", "language": null, "element": "language", "qualifier": "iso", "schema": "dc"}, {"key": "dc.rights", "value": "In Copyright", "language": "en", "element": "rights", "qualifier": null, "schema": "dc"}, {"key": "dc.subject.other", "value": "data-analytiikka", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.title", "value": "Teko\u00e4ly liiketoiminnan ennakoinnissa", "language": "", "element": "title", "qualifier": null, "schema": "dc"}, {"key": "dc.type", "value": "bachelor thesis", "language": null, "element": "type", "qualifier": null, "schema": "dc"}, {"key": "dc.identifier.urn", "value": "URN:NBN:fi:jyu-201806073085", "language": "", "element": "identifier", "qualifier": "urn", "schema": "dc"}, {"key": "dc.type.ontasot", "value": "Bachelor's thesis", "language": "en", "element": "type", "qualifier": "ontasot", "schema": "dc"}, {"key": "dc.type.ontasot", "value": "Kandidaatinty\u00f6", "language": "fi", "element": "type", "qualifier": "ontasot", "schema": "dc"}, {"key": "dc.contributor.faculty", "value": "Informaatioteknologian tiedekunta", "language": "fi", "element": "contributor", "qualifier": "faculty", "schema": "dc"}, {"key": "dc.contributor.faculty", "value": "Faculty of Information Technology", "language": "en", "element": "contributor", "qualifier": "faculty", "schema": "dc"}, {"key": "dc.contributor.department", "value": "Informaatioteknologia", "language": "fi", "element": "contributor", "qualifier": "department", "schema": "dc"}, {"key": "dc.contributor.department", "value": "Information Technology", "language": "en", "element": "contributor", "qualifier": "department", "schema": "dc"}, {"key": "dc.contributor.organization", "value": "Jyv\u00e4skyl\u00e4n yliopisto", "language": "fi", "element": "contributor", "qualifier": "organization", "schema": "dc"}, {"key": "dc.contributor.organization", "value": "University of Jyv\u00e4skyl\u00e4", "language": "en", "element": "contributor", "qualifier": "organization", "schema": "dc"}, {"key": "dc.subject.discipline", "value": "Tietoj\u00e4rjestelm\u00e4tiede", "language": "fi", "element": "subject", "qualifier": "discipline", "schema": "dc"}, {"key": "dc.subject.discipline", "value": "Information Systems Science", "language": "en", "element": "subject", "qualifier": "discipline", "schema": "dc"}, {"key": "yvv.contractresearch.funding", "value": "0", "language": "", "element": "contractresearch", "qualifier": "funding", "schema": "yvv"}, {"key": "dc.type.coar", "value": "http://purl.org/coar/resource_type/c_7a1f", "language": null, "element": "type", "qualifier": "coar", "schema": "dc"}, {"key": "dc.rights.accesslevel", "value": "openAccess", "language": null, "element": "rights", "qualifier": "accesslevel", "schema": "dc"}, {"key": "dc.type.publication", "value": "bachelorThesis", "language": null, "element": "type", "qualifier": "publication", "schema": "dc"}, {"key": "dc.subject.oppiainekoodi", "value": "601", "language": "", "element": "subject", "qualifier": "oppiainekoodi", "schema": "dc"}, {"key": "dc.subject.yso", "value": "ennakointi", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "liiketoiminta", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "koneoppiminen", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "teko\u00e4ly", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "neuroverkot", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.rights.url", "value": "https://rightsstatements.org/page/InC/1.0/", "language": null, "element": "rights", "qualifier": "url", "schema": "dc"}]
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