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[{"key": "dc.contributor.advisor", "value": "Halttunen, Veikko", "language": "", "element": "contributor", "qualifier": "advisor", "schema": "dc"}, {"key": "dc.contributor.author", "value": "Orola, Jaakko", "language": "", "element": "contributor", "qualifier": "author", "schema": "dc"}, {"key": "dc.date.accessioned", "value": "2020-12-28T07:31:14Z", "language": null, "element": "date", "qualifier": "accessioned", "schema": "dc"}, {"key": "dc.date.available", "value": "2020-12-28T07:31:14Z", "language": null, "element": "date", "qualifier": "available", "schema": "dc"}, {"key": "dc.date.issued", "value": "2020", "language": "", "element": "date", "qualifier": "issued", "schema": "dc"}, {"key": "dc.identifier.uri", "value": "https://jyx.jyu.fi/handle/123456789/73428", "language": null, "element": "identifier", "qualifier": "uri", "schema": "dc"}, {"key": "dc.description.abstract", "value": "Informaatioyhteiskunta tuottaa itsest\u00e4\u00e4n jatkuvasti kasvavalla nopeudella tietoa, jota on mahdollista hy\u00f6dynt\u00e4\u00e4 uusien menetelmien, kuten koneoppimisen avulla. Taloustieteilij\u00e4t ovat viimeisten vuosikymmenten aikana kehitt\u00e4neet tapoja tehd\u00e4 talouden ennusteita k\u00e4ytt\u00e4en useita erilaisia tiedonl\u00e4hteit\u00e4 samanaikaisesti. T\u00e4m\u00e4 kirjallisuuskatsauksena toteutettu tutkielma vastaa kysymykseen, kuinka suuria datamassoja voidaan hy\u00f6dynt\u00e4\u00e4 makrotaloustieteess\u00e4, ja kuinka koneoppimisen menetelm\u00e4t soveltuvat korvaamaan ja t\u00e4ydent\u00e4m\u00e4\u00e4n makrotaloustieteen perinteisesti k\u00e4ytt\u00e4mi\u00e4 ekonometrian menetelmi\u00e4 ennustamisessa. Tutkimuksessa havaittiin, ett\u00e4 prosessi hy\u00f6dynt\u00e4\u00e4 koneoppimisen menetelmi\u00e4 t\u00e4ysin on makrotaloustieteess\u00e4 edelleen vaiheessa. Tutkimustulokset osoittavat, ett\u00e4 esimerkiksi verkkoharavoinnilla hankittu data ja hakukonedata sis\u00e4lt\u00e4v\u00e4t informaatiota, jota perinteisist\u00e4 tietol\u00e4hteist\u00e4 ei l\u00f6ydy. Hadoop ja NoSQL-tietokannat osoittautuvat t\u00e4rkeiksi datanhallinnan ty\u00f6kaluiksi. Monet uudet tiedonl\u00e4hteet sopivat reaaliaikaiseen ennustamiseen, sill\u00e4 dataa on julkisesti tarjolla p\u00e4ivitt\u00e4istasolla.", "language": "fi", "element": "description", "qualifier": "abstract", "schema": "dc"}, {"key": "dc.description.abstract", "value": "The modern information society creates data about itself at an ever-increasing pace. With emerging technologies like machine learning, it is possible to make use of this data. For the last three decades, economists have developed models that predict using a multiple data source approach. This literature review answers the question how Big Data can be utilized in macroeconomics and how machine learning technologies can complement or replace econometrical methods in prediction. The process of utilizing machine learning in macroeconomics was found to be incomplete at the time of this review. The results show that data gathered with web scraping and search engine statistics contain information that is not present in contemporary datasets. Apache Hadoop and NoSQL databases prove to be important tools in managing Big Data. Many new data sources that can be collected at a high frequency are useful in macroeconomic nowcasting.", "language": "en", "element": "description", "qualifier": "abstract", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Submitted by Paivi Vuorio (paelvuor@jyu.fi) on 2020-12-28T07:31:14Z\nNo. of bitstreams: 0", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Made available in DSpace on 2020-12-28T07:31:14Z (GMT). No. of bitstreams: 0\n Previous issue date: 2020", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.format.extent", "value": "27", "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": "nowcasting", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.title", "value": "Massadata ja koneoppiminen makrotaloustieteess\u00e4", "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-202012287360", "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": "koneoppiminen", "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": "makrotaloustiede", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "ennusteet", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "data", "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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