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Siekiama, taikant pasirinktas verslo analitikos sistemas, sukurti ir pritaikyti interaktyvias vizualizacijas bei atlikti draudimo sumų pokyčio ir dominuojančių sveikatos klausimų analizę. Duomenų analizė papildoma mašininio mokymosi metodais, o rezultatai apibendrinami, pateikiant sistemingą požiūrį į rizikos vertinimo sprendimų pagrindimą.",{"@graph":69,"@context":114},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/insurance-underwriting-risk-assessment-using-business-analytics-systems-and-machine-learning-bachelors-thesis/290604/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/insurance-underwriting-risk-assessment-using-business-analytics-systems-and-machine-learning-bachelors-thesis/290604.png","ImageObject",300,407,{"name":92,"@type":93},"Ezra","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-25","2026-09-17",true,{"@type":102,"interactionType":103,"userInteractionCount":39},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108],{"name":109,"@type":110,"acceptedAnswer":111},"Kokie pagrindiniai įgyvendinimo etapai aprašomi?","Question",{"text":112,"@type":113},"Numatyti duomenų paruošimo, interaktyvių diagramų kūrimo ir duomenų analizės naudojant mašininį mokymąsi etapai, po jų pateikiami rezultatai ir apibendrinimas.","Answer","https://schema.org",{"og:url":83,"og:type":116,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":118,"canonical":83},"index,follow",{"doc_id":120,"site_id":62},290604,1790442653,{"code":4,"msg":5,"data":123},{"doc_id":120,"user_id":124,"nickname":92,"user_avatar":125,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":126,"file_id":127,"file_url":128,"file_type":129,"file_size":130,"view_count":39,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":131,"language":132,"language_code":63,"site_id":62,"html_lang":133,"table_of_contents":134,"faqs":135,"seo_title":136,"seo_description":67,"update_tm":137,"read_time":138,"preview_page_count":4},1099514068035,"https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c","VILNIAUS UNIVERSITETAS  \nMATEMATIKOS IR INFORMATIKOS FAKULTETAS  \nINFORMACINIŲ SISTEMŲ INŽINERIJOS STUDIJŲ PROGRAMA  \nDraudimo rizikos vertinimo analizė naudojant verslo analitikos sistemas bei mašininį mokymąsi  \nInsurance Underwriting Analysis Using Business Analytics Systems and Machine Learning  \nBaigiamasis bakalauro darbas  \nAtliko: Gabija Balionytė  \nVU el. p.: [gabija.balionyte@mif.stud.vu.lt](gabija.balionyte@mif.stud.vu.lt)  \nVadovas: J. Asist. Marius Liutvinavičius  \nVilnius  \nTURINYS  \nSANTRAUKA..................................................................................................................................................5  \nSUMMARY ....................................................................................................................................................6  \n1. ĮVADAS..................................................................................................................................................7  \n1.1. Temos aktualumas .......................................................................................................................7  \n1.2. Problema ......................................................................................................................................7  \n1.3. Konfidencialumo sutartis .............................................................................................................7  \n1.4. Tikslas ...........................................................................................................................................7  \n1.5. Uždaviniai .....................................................................................................................................7  \n1.6. Naudojamos sąvokos....................................................................................................................8  \n1.7. Darbo struktūra ............................................................................................................................8  \n2. ANALITINĖ DALIS ..................................................................................................................................9  \n2.1. Procesų tyryba ..............................................................................................................................9  \n Įvadas į procesų tyrybą .........................................................................................................9  \n Procesų tyrybos naudojimas ..............................................................................................10  \n2.2. Duomenų tyryba.........................................................................................................................12  \n Įvadas į duomenų tyrybą ....................................................................................................12  \n Duomenų tyrybos technikos ..............................................................................................13  \n2.3. Verslo analitikos sistemų palyginimas........................................................................................15  \n Microsoft Power BI .............................................................................................................15  \n Qlik Sense ...........................................................................................................................16  \n Tableau ...............................................................................................................................18  \n Mašininio mokymo galimybės ............................................................................................18  \n Sistemos pasirinkimas ........................................................................................................19  \n3. METODINĖ DALIS................................................................................................................................22  \n3.1. Įmonės procesų modeliavimas .......................","cbCaivmNkUFs2As7","https://ap.wps.com/l/cbCaivmNkUFs2As7","pdf",1284838,39,"Lithuanian","en","# ĮVADAS\n## Temos aktualumas\n## Problema\n## Konfidencialumo sutartis\n## Tikslas\n## Uždaviniai\n## Naudojamos sąvokos\n## Darbo struktūra\n# ANALITINĖ DALIS\n## Procesų tyryba\n## Duomenų tyryba\n## Verslo analitikos sistemų palyginimas\n# METODINĖ DALIS\n## Įmonės procesų modeliavimas\n## Duomenų modeliavimas\n## Duomenų importavimas\n## Funkciniai reikalavimai diagramoms\n# ĮGYVENDINIMO DALIS\n## Duomenų paruošimas\n## Interaktyvių diagramų kūrimas\n## Duomenų analizė naudojant mašininį mokymąsi\n# REZULTATAI IR APIBENDRINIMAS\n# LITERATŪRA\n# 1 PRIEDAS","[{\"question\":\"Kokie pagrindiniai įgyvendinimo etapai aprašomi?\",\"answer\":\"Numatyti duomenų paruošimo, interaktyvių diagramų kūrimo ir duomenų analizės naudojant mašininį mokymąsi etapai, po jų pateikiami rezultatai ir apibendrinimas.\"}]","Draudimo rizikos vertinimo analizė naudojant verslo analitikos sistemas bei mašininį mokymąsi - Baigiamasis bakalauro darbas | PDF",1789642181,98]