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[{"key": "dc.contributor.advisor", "value": "Makkonen, Pekka", "language": "", "element": "contributor", "qualifier": "advisor", "schema": "dc"}, {"key": "dc.contributor.author", "value": "Paloniemi, Juuso", "language": "", "element": "contributor", "qualifier": "author", "schema": "dc"}, {"key": "dc.date.accessioned", "value": "2018-05-21T05:46:08Z", "language": null, "element": "date", "qualifier": "accessioned", "schema": "dc"}, {"key": "dc.date.available", "value": "2018-05-21T05:46:08Z", "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/123456789/58025", "language": null, "element": "identifier", "qualifier": "uri", "schema": "dc"}, {"key": "dc.description.abstract", "value": "ABSTRACT\nPaloniemi, Juuso\nThe benefits of ICT and Big Data-analytics in forest based industries business management\nJyv\u00e4skyl\u00e4: University of Jyv\u00e4skyl\u00e4, 2018, 86 p.\nInformation Systems, Master\u2019s Thesis\nSupervisor: Pekka Makkonen\n\nBig Data and analysing it as part of business intelligence (BI) systems is at this very moment one of the most popular research topics in the field of Information Systems Science. It offers unprecedented opportunities to store, handle, store and analyse information for both private individuals as for organizations. Big Data \u2013systems that are implemented to business intelligence systems are considered to be one of the cornerstones in the next digital revolution. In the forest based industry Enterprise Resource Planning systems have been revised mainly with larger investments in machinery and equipment, but it is now possible to integrate the ERP system and Big Data analytics to build new kind of business as well as improve efficiency and bring cots to a lower level. However the problem is what information should be used and how the process of extracting the information generated by individual processes can be processed so it can be analysed as a whole. Also an important part of the process is to research if the users are collecting usable information and whether or not they know what they are supposed to do whit that information.\nThis study examines how Big Data - analytics could best be utilized in business intelligence \u2013 systems to obtain the forest based industries operational sites to bring the best possible added value. The study focused find and locate the opportunities that engineers and managers found possible and worth pursuing. The research also studied the potential benefits of investments for customers as well as suppliers of raw materials in the form of a purely economic added value, but also in the form of increased knowledge and harmonization of operating cultures. These issues formed the Big Data analytics package, which creates a new understanding of how the data explosion can be used for the benefit of new business development as well as making current operations more efficient.\n\tThe study explored not only the Big Data systems theoretical and technological background (e.g. Hadoop, HDFS & MapReduce) by means of a literature review, but also the challenges in implementing and gathering usable information from forest based industries BI-systems. That gave more understanding to the research problem. This was followed by a qualitative case study relevant group of experts in which the answers were sought based on the interviews of those experts and professionals. After this the empirical research was discussed and compared to the literature findings. With that method it was possible to build more understanding to the research problem.\n\nKeywords: Big Data, Big Data Analytics, ERP, Enterprise Resource Planning System, Forest Based Industry, Paper Machine, Board Machine, Pulp Mill, Maintenance", "language": "en", "element": "description", "qualifier": "abstract", "schema": "dc"}, {"key": "dc.description.abstract", "value": "TIIVISTELM\u00c4\nPaloniemi, Juuso\nTietoj\u00e4rjestelmien ja Big Data-analytiikan hy\u00f6dyt mets\u00e4teollisuuden liiketoi-minnan hallinnassa\nJyv\u00e4skyl\u00e4: Jyv\u00e4skyl\u00e4n yliopisto, 2018, 86 s.\nTietoj\u00e4rjestelm\u00e4tiede, Pro Gradu - tutkielma\nOhjaaja: Pekka Makkonen\n\nBig Data ja sen analysointi on t\u00e4ll\u00e4kin hetkell\u00e4 yksi tietoj\u00e4rjestelm\u00e4tieteen ajankohtaisimpia tutkimusaiheita. Se tarjoaa ennenn\u00e4kem\u00e4tt\u00f6mi\u00e4 mahdollisuuksia tallentaa, k\u00e4sitell\u00e4, varastoida ja analysoida tietoa niin yksityishenkil\u00f6ille, kuin organisaatioille. Moderneista tietoj\u00e4rjestelmist\u00e4 juuri Big Data-sovelluksia pidet\u00e4\u00e4nkin yhten\u00e4 kulmakiven\u00e4 seuraavassa digitaalisessa vallankumouksessa. Mets\u00e4teollisuudessa tieto- ja toiminnanohjausj\u00e4rjestelmi\u00e4 on uudistettu l\u00e4hinn\u00e4 suurempien kone- ja laitteistoinvestointien yhteydess\u00e4, mutta nyt on mahdollista integroida tietoj\u00e4rjestelmiin ja Big Data-analytiikkaa uusien liiketoimintamuotojen, tehokkuuden ja kustannuss\u00e4\u00e4st\u00f6jen mahdollistamiseksi. Ongelmana on kuitenkin se, mit\u00e4 tietoa kannattaa ottaa prosessista talteen ja kuka m\u00e4\u00e4ritte-lee mit\u00e4 tietoa yksitt\u00e4isest\u00e4 prosessista tarvitaan, jotta liiketoimintaa voidaan hallita ja kehitt\u00e4\u00e4 mahdollisimman tehokkaasti.\nT\u00e4ss\u00e4 ty\u00f6ss\u00e4 tutkitaan, kuinka nykyaikaisia tietoj\u00e4rjestelmi\u00e4 ja Big Data - analytiikkaa voisi parhaiten k\u00e4ytt\u00e4\u00e4 hyv\u00e4ksi mets\u00e4teollisuuden konelin-jastoilla parhaan mahdollisen arvonlis\u00e4n saamiseksi. Ty\u00f6ss\u00e4 keskityttiin havaitsemaan tutkimuksen keinoin niit\u00e4 mahdollisuuksia, jotka tuotannon asiantuntijat ja p\u00e4\u00e4llik\u00f6t kokevat mahdollisiksi ja tavoittelemisen arvoisiksi. Lis\u00e4ksi selvitettiin tietoj\u00e4rjestelmien ja liiketoiminnan hallinnan yhteenlinjauksen haasteita asiantuntija- ja esimiesorganisaatioissa. N\u00e4ist\u00e4 teemoista muodostui liiketoiminnan hallinnan ja Big Data-tietoj\u00e4rjestelm\u00e4analytiikan kokonaisuus, joka luo uutta ymm\u00e4rryst\u00e4 siit\u00e4, kuinka valtavasti lis\u00e4\u00e4ntynytt\u00e4 tietom\u00e4\u00e4r\u00e4\u00e4 voidaan k\u00e4ytt\u00e4\u00e4 hyv\u00e4ksi uutta liiketoimintaa kehitett\u00e4ess\u00e4 sek\u00e4 nykyist\u00e4 toimintaa tehostettaessa. T\u00e4t\u00e4 ymm\u00e4rryst\u00e4 johdettiin my\u00f6s tutustumalla niihin teknologioihin (mm. Hadoop, HDFS, MapReduce) jotka mahdollistavat t\u00e4m\u00e4n uuden, entist\u00e4 kattavamman ja tarkemman tavan ker\u00e4t\u00e4, tallentaa ja analysoida prosessista saatavaa tietoa. T\u00e4m\u00e4 oli eritt\u00e4in t\u00e4rke\u00e4\u00e4, jotta tulosten pohjalta pystyt\u00e4\u00e4n analysoimaan niit\u00e4 teknologioita, joiden jatkokehitys on organisaation kehityksen kannalta kriittisint\u00e4.\nTy\u00f6ss\u00e4 k\u00e4siteltiin ensin erilaisten massadataan perustuvien tietoj\u00e4rjestelm\u00e4teknologioiden k\u00e4sitteist\u00f6\u00e4 ja toiminnallisuuksia, jonka j\u00e4lkeen siirryttiin liiketoiminnan hallintaan ja n\u00e4iden kahden yhteenlinjauksen aiheuttamiin haasteisiin. Kyseist\u00e4 aiheista rakennetun kirjallisuuskatsauksen avulla haettiin ymm\u00e4rryst\u00e4 tutkimusongelmaan. T\u00e4m\u00e4n j\u00e4lkeen suoritettiin laadullinen tapaustutkimus valikoidulle asiantuntijajoukolle, jossa vastauksia haettiin pohjautuen asiantuntijoiden haastatteluihin. T\u00e4m\u00e4n j\u00e4lkeen pohdittiin empiirisen tutkimuksen havaintoja ja vertailtiin niit\u00e4 kirjallisuuden havaintoihin, jonka avulla tutkimusongelmaan pystyttiin rakentamaan lis\u00e4\u00e4 ymm\u00e4rryst\u00e4.\n\nAsiasanat: Tietoj\u00e4rjestelm\u00e4, Big Data, Big Data-analytiikka, Toiminnanohjaus, Toiminnanohjausj\u00e4rjestelm\u00e4, Mets\u00e4teollisuus, Kunnossapito, ERP-j\u00e4rjestelm\u00e4, Liiketoiminannan hallinta, Liiketoiminnan ja IT:n yhteenlinjaus", "language": "fi", "element": "description", "qualifier": "abstract", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Submitted by Miia Hakanen (mihakane@jyu.fi) on 2018-05-21T05:46:07Z\nNo. of bitstreams: 0", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Made available in DSpace on 2018-05-21T05:46:08Z (GMT). No. of bitstreams: 0\n Previous issue date: 2018", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.format.extent", "value": "86", "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": "Tietoj\u00e4rjestelm\u00e4", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "Data-analytiikka", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "Toiminnanohjausj\u00e4rjestelm\u00e4", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "Mets\u00e4teollisuus", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "Kunnossapito", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "ERP-j\u00e4rjestelm\u00e4", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "Liiketoiminnan hallinta", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "Liiketoiminnan ja IT:n yhteenlinjaus", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.title", "value": "Tietoj\u00e4rjestelmien ja Big Data-analytiikan hy\u00f6dyt mets\u00e4teollisuuden liiketoiminnan hallinnassa", "language": "", "element": "title", "qualifier": null, "schema": "dc"}, 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