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[{"key": "dc.contributor.advisor", "value": "Grahn, Hilkka", "language": null, "element": "contributor", "qualifier": "advisor", "schema": "dc"}, {"key": "dc.contributor.author", "value": "Ky\u00f6stil\u00e4, Lauri", "language": null, "element": "contributor", "qualifier": "author", "schema": "dc"}, {"key": "dc.date.accessioned", "value": "2025-05-19T09:26:56Z", "language": null, "element": "date", "qualifier": "accessioned", "schema": "dc"}, {"key": "dc.date.available", "value": "2025-05-19T09:26:56Z", "language": null, "element": "date", "qualifier": "available", "schema": "dc"}, {"key": "dc.date.issued", "value": "2025", "language": null, "element": "date", "qualifier": "issued", "schema": "dc"}, {"key": "dc.identifier.uri", "value": "https://jyx.jyu.fi/handle/123456789/102433", "language": null, "element": "identifier", "qualifier": "uri", "schema": "dc"}, {"key": "dc.description.abstract", "value": "The amount of data in companies has grown tremendously, to the extent that \nmany businesses have more data than they can effectively manage. However, \ndue to its sheer volume, fully leveraging this data for business development re\nmains challenging. For this reason, business intelligence (BI) systems have been \nimplemented to process large amounts of data and extract the most critical infor\nmation to support decision-making. In BI systems, information for decision-mak\ning is presented to users as data visualizations, allowing them to search for and \nfilter the information they need and process it into actionable knowledge. Based \non this relevant and actionable knowledge, users can make data-driven decisions, \na process known as data-driven decision-making. The challenge, however, lies in \nensuring the accuracy and relevance of the data representation, verifying \nwhether users understand the information presentation, and determining \nwhether they can process it into meaningful insights and make rational, data\ndriven decisions. This research aims to address this issue by investigating how \nteam managers experience two different data visualization during operational \ndata-driven decision-making situation. This phenomenon was researched by \nconducting eight individual during task performance, where each team manager \nwas asked to share their answers to business related questions using two differ\nently visualized Power BI reports, old and new. The new dashboard visualization \nwas designed based on the research theoretical framework, using the exact same \ndata as in the old dashboard. The research data was collected from during task \nperformance using thinking aloud method. The data was analysed using the\nmatic analysis. The research results provide understanding of different experi\nences that stem from different data visualization during operational data-driven \ndecision-making and highlight the importance of combining data visualization \nand decision-making theories and practises into a precise and well-structured \ndata visualization design process. Additionally, the research result was a new \ndesign of old dashboard with theories and findings that can be utilized as design \nguidelines to creating more predictable data visualization experience during op\nerational decision-making. However, the research does not offer single explana\ntion or theory on how participants experience data visualization during opera\ntional data-driven decision-making due to the complexity of the research area.", "language": "en", "element": "description", "qualifier": "abstract", "schema": "dc"}, {"key": "dc.description.abstract", "value": "Datan m\u00e4\u00e4r\u00e4 yrityksiss\u00e4 on kasvanut valtavasti mutta sen m\u00e4\u00e4r\u00e4st\u00e4 johtuen \nt\u00e4ysimittainen hy\u00f6dynt\u00e4minen liiketoiminnan kehitt\u00e4misess\u00e4 on haastavaa. \nT\u00e4st\u00e4 syyst\u00e4 liiketoimintatiedon hallinnanj\u00e4rjestelmi\u00e4 (BI) on otettu k\u00e4ytt\u00f6\u00f6n, \njotta valtavasta m\u00e4\u00e4r\u00e4st\u00e4 dataa voidaan prosessoida t\u00e4rkein informaatio \nk\u00e4ytt\u00e4j\u00e4n p\u00e4\u00e4t\u00f6ksenteon tueksi. BI-j\u00e4rjestelmiss\u00e4 informaatio p\u00e4\u00e4t\u00f6ksenteon \ntueksi esitet\u00e4\u00e4n k\u00e4ytt\u00e4j\u00e4lle datan visualisointina, josta k\u00e4ytt\u00e4j\u00e4n on mahdollista \netsi\u00e4 tarvitsemansa informaatio ja muuttaa se tiedoksi. T\u00e4m\u00e4n relevantin tiedon \npohjalta k\u00e4ytt\u00e4j\u00e4n on mahdollista tehd\u00e4 dataan perustuvia p\u00e4\u00e4t\u00f6ksi\u00e4, jota \nkutsutaan dataohjautuvaksi p\u00e4\u00e4t\u00f6ksenteoksi. Ongelma kuitenkin on, miten \nvarmistetaan esitett\u00e4v\u00e4n informaation relevantti esitystapa eli ymm\u00e4rt\u00e4\u00e4k\u00f6 \nk\u00e4ytt\u00e4j\u00e4 esitetyn informaation ja pystyyk\u00f6 h\u00e4n prosessoimaan sen relevantiksi \ntiedoksi sek\u00e4 tekem\u00e4\u00e4n dataan perustuvia p\u00e4\u00e4t\u00f6ksi\u00e4. T\u00e4m\u00e4 tutkimus pyrkii \nvastaamaan t\u00e4h\u00e4n ongelmaan selvitt\u00e4m\u00e4ll\u00e4, kuinka tiiminvet\u00e4j\u00e4 kokee kahden \neri tavalla visualisoidun datan operationaalisessa dataohjautuvassa \np\u00e4\u00e4t\u00f6ksenteon tilanteessa. Datan visualisoinnin kokemusta p\u00e4\u00e4t\u00f6ksenteon \ntilanteessa arvioitiin j\u00e4rjest\u00e4m\u00e4ll\u00e4 kahdeksan erillist\u00e4 suoritustilannetta, joissa \nyksi tiiminvet\u00e4j\u00e4 kerrallaan jakoi vastauksia liiketoiminnan kysymyksiin \nk\u00e4ytt\u00e4en kahta eri tavalla visualisoitua Power BI raporttia, vanhaa ja uutta. \nUuden raportin visualisointi luotiin tutkimuksen teorioiden pohjalta \nk\u00e4ytt\u00e4m\u00e4ll\u00e4 t\u00e4ysin samaa dataa kuin vanhassa raportissa. Tutkimuksen data \nker\u00e4ttiin suoritustilanteista k\u00e4ytt\u00e4en \u00e4\u00e4neen ajattelun metodia. Tutkimuksen \ndata analysoitiin temaattisella analyysill\u00e4. Tutkimustulokset antavat \nymm\u00e4rryksen erilaisista kokemuksista, jotka johtuvat datan visualisoinnin \neroavaisuudesta dataohjautuvan p\u00e4\u00e4t\u00f6ksenteon tilanteessa ja korostavat datan \nvisualisoinnin ja p\u00e4\u00e4t\u00f6ksenteon teorioiden ja k\u00e4yt\u00e4nt\u00f6jen yhdist\u00e4mist\u00e4 osaksi \ndatan visualisoinnin suunnitteluprosessia. Tutkimustuloksena on uudelleen \nvisualisoitu raportti, jonka suunnittelussa k\u00e4ytettyj\u00e4 teorioita ja k\u00e4yt\u00e4nt\u00f6j\u00e4 \nvoidaan k\u00e4ytt\u00e4\u00e4 ohjeistuksena datan visualisoinnin kokemuksen \nsuunnittelussa. Tutkimus ei kuitenkaan tarjoa yht\u00e4 selke\u00e4\u00e4 selityst\u00e4 tai teoriaa \nsiit\u00e4, miten tiiminvet\u00e4j\u00e4t kokevat datavisualisoinnin operatiivisen dataohjatun \np\u00e4\u00e4t\u00f6ksenteon aikana, johtuen tutkimusalueen monimutkaisuudesta.", "language": "fi", "element": "description", "qualifier": "abstract", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Submitted by jyx lomake-julkaisija (jyx-julkaisija.group@korppi.jyu.fi) on 2025-05-19T09:26:56Z\nNo. of bitstreams: 0", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Made available in DSpace on 2025-05-19T09:26:56Z (GMT). No. of bitstreams: 0", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.format.extent", "value": "90", "language": null, "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": "eng", "language": null, "element": "language", "qualifier": "iso", "schema": "dc"}, {"key": "dc.rights", "value": "CC BY 4.0", "language": null, "element": "rights", "qualifier": null, "schema": "dc"}, {"key": "dc.title", "value": "How team managers experience data visualization during operational data-driven decision-making", "language": null, "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-202505194366", "language": null, "element": "identifier", "qualifier": "urn", "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.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": "Kognitiotieteen maisteriohjelma", "language": "fi", "element": "subject", "qualifier": "discipline", "schema": "dc"}, {"key": "dc.subject.discipline", "value": "Master\u2019s Degree Programme in Cognitive Science", "language": "en", "element": "subject", "qualifier": "discipline", "schema": "dc"}, {"key": "dc.type.coar", "value": "http://purl.org/coar/resource_type/c_bdcc", "language": null, "element": "type", "qualifier": "coar", "schema": "dc"}, {"key": "dc.rights.copyright", "value": "\u00a9 The Author(s)", "language": null, "element": "rights", "qualifier": "copyright", "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.format.content", "value": "fulltext", "language": null, "element": "format", "qualifier": "content", "schema": "dc"}, {"key": "dc.rights.url", "value": "https://creativecommons.org/licenses/by/4.0/", "language": null, "element": "rights", "qualifier": "url", "schema": "dc"}, {"key": "dc.description.accessibilityfeature", "value": "unknown accessibility", "language": "en", "element": "description", "qualifier": "accessibilityfeature", "schema": "dc"}, {"key": "dc.description.accessibilityfeature", "value": "ei tietoa saavutettavuudesta", "language": "fi", "element": "description", "qualifier": "accessibilityfeature", "schema": "dc"}]
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