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[{"key": "dc.contributor.advisor", "value": "Taipalus, Toni", "language": "", "element": "contributor", "qualifier": "advisor", "schema": "dc"}, {"key": "dc.contributor.author", "value": "Talviaho, Henri", "language": "", "element": "contributor", "qualifier": "author", "schema": "dc"}, {"key": "dc.date.accessioned", "value": "2021-05-26T12:53:19Z", "language": null, "element": "date", "qualifier": "accessioned", "schema": "dc"}, {"key": "dc.date.available", "value": "2021-05-26T12:53:19Z", "language": null, "element": "date", "qualifier": "available", "schema": "dc"}, {"key": "dc.date.issued", "value": "2021", "language": "", "element": "date", "qualifier": "issued", "schema": "dc"}, {"key": "dc.identifier.uri", "value": "https://jyx.jyu.fi/handle/123456789/75976", "language": null, "element": "identifier", "qualifier": "uri", "schema": "dc"}, {"key": "dc.description.abstract", "value": "Datan m\u00e4\u00e4r\u00e4 on kasvanut r\u00e4j\u00e4hdysm\u00e4isesti. Datan rooli yhteiskunnassa on muuttunut 2000-luvulla merkitt\u00e4v\u00e4sti. Dataa hy\u00f6dynnet\u00e4\u00e4n monilla eri tavoilla, esimerkiksi markkinoinnissa. Big Datalla tarkoitetaan dataa, joka on m\u00e4\u00e4r\u00e4lt\u00e4\u00e4n suurta ja olemukseltaan moninaista. Big Datalle ei kuitenkaan ole olemassa yksitt\u00e4ist\u00e4 k\u00e4sitett\u00e4, vaan niin yritysmaailma, kuin my\u00f6s akateeminen maailma ovat pullollaan useita toisistaan poikkeavia k\u00e4sitteit\u00e4. T\u00e4ss\u00e4 tutkielmassa tavoitteena on kartoittaa niin kirjallisuuskatsauksen kuin my\u00f6s empiirisen tutkimuksen avulla sit\u00e4, mit\u00e4 Big Datalla tarkoitetaan ja sit\u00e4, mink\u00e4laisia v\u00e4\u00e4rink\u00e4sityksi\u00e4 Big Dataan liittyy. Tutkielmassa tutustutaan aluksi kuvailemaan sit\u00e4, miten akateemikot n\u00e4kev\u00e4t Big Datan k\u00e4sitteen tasolla. Lis\u00e4ksi tutustutaan Big Datan yleisimpiin ominaisuuksiin. Empiirisen tutkimuksen avulla tutustutaan siihen, miten asiantuntijoiden ja opiskelijoiden piiriss\u00e4 Big Data miellet\u00e4\u00e4n. Tutkimuksessa havaittiin, ett\u00e4 Big Dataan liittyvi\u00e4 v\u00e4\u00e4rink\u00e4sityksi\u00e4 ovat yleisimmin se, ett\u00e4 Big Datan koetaan olevan vain m\u00e4\u00e4r\u00e4llisesti suurta dataa ja t\u00e4ten eroavan vain m\u00e4\u00e4r\u00e4n perusteella tavallisesti datasta. Lis\u00e4ksi toisena yleisimp\u00e4n\u00e4 v\u00e4\u00e4rink\u00e4sityksen muotona tutkimuksessa ilmeni se, ett\u00e4 Big Data sekoitetaan analytiikan kanssa, toisin sanoen vastaajat olettavat, ett\u00e4 Big Data itsess\u00e4\u00e4n on prosessi, joka kattaa kaiken tiedon ker\u00e4\u00e4misest\u00e4 analysointiin saakka. Tutkimuksen lopussa pohditaan Big Datan t\u00e4rkeytt\u00e4 ja tarpeellisuutta. Kyseenalaistetaan termin Big Data tarpeellisuus ja ehdotetaan, ett\u00e4 Big Data olisi vain osa data-analytiikkaa.", "language": "fi", "element": "description", "qualifier": "abstract", "schema": "dc"}, {"key": "dc.description.abstract", "value": "The amount of data has grown significantly. Nowadays data is collected in many different ways and with different means. Data is, for example, used to profile us and in marketing. Big Data has multiple different definitions. Usually Big Data is seen as data that is huge in volume and rich in form. Most of academics explain the Big Data with three feature, volume, velocity and variety. Because of the lack of accepted definition, defining Big Data is challenging. The aim of this Master\u2019s thesis is to investigate how Big Data is defined in academia and in practice, and what misunderstanding and misconceptions of Big Data excist. The study found that the most common misconceptions about Big Data are that Big Data is perceived to be only quantitatively large data and thus differs only with volume when compared to basic data. the second most common form of misunderstanding in the study was that Big Data is confused with analytics, i.e., respondents assume that Big Data itself is a process that covers everything from data collection to analysis. At the end of the study, the importance and necessity of Big Data is considered. The necessity of the term Big Data is questioned and it is suggested that Big Data should only be part of data analytics.", "language": "en", "element": "description", "qualifier": "abstract", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Submitted by Paivi Vuorio (paelvuor@jyu.fi) on 2021-05-26T12:53:19Z\nNo. of bitstreams: 0", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Made available in DSpace on 2021-05-26T12:53:19Z (GMT). No. of bitstreams: 0\n Previous issue date: 2021", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.format.extent", "value": "61", "language": "", "element": "format", "qualifier": "extent", "schema": "dc"}, {"key": "dc.format.mimetype", "value": "application/pdf", "language": null, "element": "format", "qualifier": "mimetype", "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": "analytiikka", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "data-analytiikka", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.title", "value": "N\u00e4kemyksi\u00e4 Big Datasta : paljon dataa, vai jotain enemm\u00e4n?", "language": "", "element": "title", "qualifier": null, "schema": "dc"}, {"key": "dc.type", "value": "master thesis", "language": null, "element": "type", "qualifier": null, "schema": "dc"}, {"key": "dc.identifier.urn", "value": "URN:NBN:fi:jyu-202105263233", "language": "", "element": "identifier", "qualifier": "urn", "schema": "dc"}, {"key": "dc.type.ontasot", "value": "Pro gradu -tutkielma", "language": "fi", "element": "type", "qualifier": "ontasot", "schema": "dc"}, {"key": "dc.type.ontasot", "value": "Master\u2019s thesis", "language": "en", "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_bdcc", "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": "masterThesis", "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": "big data", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "data", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.format.content", "value": "fulltext", "language": null, "element": "format", "qualifier": "content", "schema": "dc"}, {"key": "dc.rights.url", "value": "https://rightsstatements.org/page/InC/1.0/", "language": null, "element": "rights", "qualifier": "url", "schema": "dc"}, {"key": "dc.type.okm", "value": "G2", "language": null, "element": "type", "qualifier": "okm", "schema": "dc"}]
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