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[{"key": "dc.contributor.advisor", "value": "Makkonen, Pekka", "language": "", "element": "contributor", "qualifier": "advisor", "schema": "dc"}, {"key": "dc.contributor.author", "value": "K\u00e4\u00e4ri\u00e4inen, Jenni", "language": "", "element": "contributor", "qualifier": "author", "schema": "dc"}, {"key": "dc.date.accessioned", "value": "2019-03-05T07:00:33Z", "language": null, "element": "date", "qualifier": "accessioned", "schema": "dc"}, {"key": "dc.date.available", "value": "2019-03-05T07:00:33Z", "language": null, "element": "date", "qualifier": "available", "schema": "dc"}, {"key": "dc.date.issued", "value": "2019", "language": "", "element": "date", "qualifier": "issued", "schema": "dc"}, {"key": "dc.identifier.uri", "value": "https://jyx.jyu.fi/handle/123456789/63021", "language": null, "element": "identifier", "qualifier": "uri", "schema": "dc"}, {"key": "dc.description.abstract", "value": "Big data on yksi IT-alan suosituimpia termej\u00e4 t\u00e4ll\u00e4 hetkell\u00e4 ja monet yritykset haluavat l\u00f6yt\u00e4\u00e4 big datassa piilev\u00e4n hy\u00f6dyn. Tavalliseen data-analyysiin verrattuna big dataa ker\u00e4t\u00e4\u00e4n ja analysoidaan suurempia datam\u00e4\u00e4ri\u00e4 sek\u00e4 rakenteetontakin dataa. T\u00e4m\u00e4n tutkielman tarkoituksena on tutkia big datan k\u00e4ytt\u00f6\u00e4 ty\u00f6ntekij\u00f6iden seurannassa ja rekrytoinnissa, erityisesti hy\u00f6tyj\u00e4 joita big datan k\u00e4ytt\u00f6 voi tuoda henkil\u00f6st\u00f6nhallinnalle. Ty\u00f6ntekij\u00f6iden seurantaa on yrityksiss\u00e4 tehty vuosikausia ja monet nykyaikaiset muutokset ty\u00f6nteossa kuten et\u00e4ty\u00f6t sek\u00e4 teknologian kehittymisen tuomat uudet haasteet ty\u00f6ss\u00e4 vaativat seurannallekin uusia askeleita. Rekrytointi on aina ollut yritykseen suuresti vaikuttava ja haastava teht\u00e4v\u00e4, johon yritykset mielell\u00e4\u00e4n ottavat k\u00e4ytt\u00f6\u00f6n tehokkaampia keinoja. \nBig datan k\u00e4sittelemiseen liittyy sek\u00e4 sen hallinta ett\u00e4 analysointi ja ty\u00f6kaluja n\u00e4ihin molempiin l\u00f6ytyy useita. Kirjallisuutta l\u00f6ytyy paljon sek\u00e4 big datasta ett\u00e4 henkil\u00f6st\u00f6nhallinnasta, mutta kirjallisuutta big datan hy\u00f6dynt\u00e4misest\u00e4 seurannassa ja rekrytoinnissa l\u00f6ytyy viel\u00e4 suhteellisen v\u00e4h\u00e4n. \n Tutkimuksessa huomattiin, ett\u00e4 big data hy\u00f6dytt\u00e4\u00e4 yrityksien henkil\u00f6st\u00f6nhallintaa eniten p\u00e4\u00e4t\u00f6ksenteossa, kustannusten v\u00e4hent\u00e4misess\u00e4, tyytyv\u00e4isyyden parantamisessa sek\u00e4 sopivien ty\u00f6ntekij\u00f6iden valinnassa. Erityisesti seurannassa big datan avulla voidaan suorittaa tarkempaa analyysia suurilla datam\u00e4\u00e4rill\u00e4, seurata ty\u00f6ntekij\u00f6iden terveytt\u00e4, suoriutumista sek\u00e4 tyytyv\u00e4isyytt\u00e4. Rekrytoinnissa big datan k\u00e4ytt\u00f6 voi helpottaa sopivien ty\u00f6ntekij\u00f6iden l\u00f6yt\u00e4mist\u00e4 ja valitsemista, parantaa yrityksen br\u00e4ndi\u00e4, tehostamalla hakemusten l\u00e4pik\u00e4ynti\u00e4 sek\u00e4 parantaa rekrytointiprosessia. \nYrityksille voi siis olla runsaasti hy\u00f6tyj\u00e4 big datan k\u00e4yt\u00f6st\u00e4. Kun otetaan huomioon datan tietoturva, ty\u00f6ntekij\u00f6iden oikeudet sek\u00e4 yrityst\u00e4 velvoittavat lait sek\u00e4 big dataa k\u00e4sittelev\u00e4n henkil\u00f6kunnan ammattimaisuus, on mahdollisuus parantaa sek\u00e4 ty\u00f6ntekij\u00f6iden seurantaa ett\u00e4 rekrytointia big datan avulla.", "language": "fi", "element": "description", "qualifier": "abstract", "schema": "dc"}, {"key": "dc.description.abstract", "value": "Big data is one of the most popular terms in IT right now and multiple companies are wanting to find the benefits hidden in big data. Compared to usual data-analysis big data is about collecting big amounts of data, storing and analyzing it and even collecting unstructured data. The purpose of this study is to examine the use of big data in monitoring and recruiting employees, especially the benefits that the use of big data can bring to the context of Human resources. Companies have monitored employees for decades and many recent changes in the way we work such as remote working and the progress of technologies have brought new requirements at work that require new steps to be taken in monitoring. Recruitment has always been one of the most influential and challenging missions of a company. That is why many companies would like to find more efficient ways to recruit. \nData management and data analysis relate to the use of big data and tools to these are plenty. There is a lot of literature relating to both big data and HR but there are still relatively few studies to the use of big data in employee monitoring and recruitment. \nIn this study it was discovered that big data can benefit HR in decision making, lowering costs, improving employee satisfaction and choosing the best applicants. Especially in monitoring big data can help with getting more precise analysis with big volumes, monitoring employee health, performance and satisfaction. In recruiting use of big data can help in finding and choosing more suitable employees, improving company brand, making going through applications more efficient and improving recruitment process. \nCompanies can benefit a lot from the use of big data and when we factor in information security, employee rights and laws that bind the company and the professionalism of the big data employees, there is a chance to improve employee monitoring and recruitment with big data.", "language": "en", "element": "description", "qualifier": "abstract", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Submitted by Paivi Vuorio (paelvuor@jyu.fi) on 2019-03-05T07:00:33Z\nNo. of bitstreams: 0", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Made available in DSpace on 2019-03-05T07:00:33Z (GMT). No. of bitstreams: 0\n Previous issue date: 2019", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.format.extent", "value": "36", "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": "henkil\u00f6st\u00f6nhallinta", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "seuranta", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.title", "value": "Big datan k\u00e4ytt\u00f6 ty\u00f6ntekij\u00f6iden seurannassa ja rekrytoinnissa", "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-201903051733", "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": "valvonta", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "henkil\u00f6st\u00f6", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "big data", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "ty\u00f6ntekij\u00e4t", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "rekrytointi", "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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