{"id":39275,"date":"2019-10-31T22:29:10","date_gmt":"2019-10-31T19:29:10","guid":{"rendered":"https:\/\/prohoster.info\/blog\/plan-prokachki-dlya-polucheniya-professii-data-engineer\/"},"modified":"2019-10-31T22:29:10","modified_gmt":"2019-10-31T19:29:10","slug":"plan-prokachki-dlya-polucheniya-professii-data-engineer","status":"publish","type":"post","link":"https:\/\/prohoster.info\/da\/blog\/administrirovanie\/plan-prokachki-dlya-polucheniya-professii-data-engineer","title":{"rendered":"Uddannelsesplan for at blive Data engineer","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"<p>De sidste otte \u00e5r har jeg arbejdet som projektleder (jeg skriver ikke kode p\u00e5 jobbet), hvilket naturligvis har en negativ indvirkning p\u00e5 min teknologiske baggrund. Jeg har besluttet at reducere mit teknologiske eftersl\u00e6b og f\u00e5 en profession som Data engineer. Den prim\u00e6re f\u00e6rdighed som Data engineer er evnen til at udvikle, bygge og vedligeholde datalagre.<\/p>\n<p>Jeg har lavet en l\u00e6ringsplan, som jeg tror vil v\u00e6re nyttig ikke kun for mig. Planen er rettet mod selvstudium af kurser. Der gives prioritet til gratis kurser p\u00e5 russisk.<\/p>\n<p>Sektioner: <\/p>\n<ul>\n<li><b>Algoritmer og datastrukturer. <\/b>N\u00f8glesektion. Hvis du l\u00e6rer det, vil alt det andet ogs\u00e5 lykkes. Det er vigtigt at f\u00e5 erfaring med at skrive kode og bruge de grundl\u00e6ggende strukturer og algoritmer.<\/li>\n<li><b>Databaser og datalagre, Business Intelligence.<\/b> Fra algoritmer g\u00e5r vi over til opbevaring og behandling af data.<\/li>\n<li><b>Hadoop og Big Data. <\/b>N\u00e5r databasen ikke passer p\u00e5 harddisken, eller n\u00e5r data skal analyseres, men Excel allerede ikke kan indl\u00e6se dem, begynder Big Data. Efter min mening b\u00f8r man kun g\u00e5 til denne sektion efter en grundig studie af de to foreg\u00e5ende.<\/li>\n<\/ul>\n<p><noindex><a rel=\"nofollow\" name=\"habracut\"><\/a><\/noindex><\/p>\n<h2>Algoritmer og datastrukturer<\/h2>\n<p>\nJeg har inkluderet studiet af Python, repetition af matematikens grundl\u00e6ggende principper og algoritmer.<\/p>\n<ul>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/stepik.org\/course\/67\">Programmering i Python<\/a><\/noindex> <\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/stepik.org\/course\/512\">Python: grundl\u00e6ggende og anvendelse<\/a><\/noindex><\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/stepik.org\/course\/2461\">Line\u00e6r algebra<\/a><\/noindex><\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/stepik.org\/course\/91\/\">Indf\u00f8ring i diskret matematik <\/a><\/noindex><\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/stepik.org\/course\/217\/\">Algoritmer: teori og praksis. Metoder<\/a><\/noindex><\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/stepik.org\/course\/1547\">Algoritmer: teori og praksis. Datastrukturer<\/a><\/noindex><\/li>\n<\/ul>\n<p><\/p>\n<h2>Databaser og datalagre, Business Intelligence<\/h2>\n<p><\/p>\n<ul>\n<li>Bogen: Martin Kleppmann \u2014 H\u00f8jtydende applikationer. Programmering, skalering, support. Bogen beskriver, hvordan forskellige datamodeller fungerer, deres interne implementering, begr\u00e6nsninger og valg afh\u00e6ngigt af opgaven. <\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/stepik.org\/course\/551\">Introduktion til databaser <\/a><\/noindex><\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/stepik.org\/course\/3203\">Dykning i databasesystemer<\/a><\/noindex><\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/stepik.org\/course\/2586\">Introduktion til ikke-relationelle databaser <\/a><\/noindex><\/li>\n<\/ul>\n<p>\nEmner relateret til opbygning af datalagre, ETL, OLAP-kuber afh\u00e6nger st\u00e6rkt af v\u00e6rkt\u00f8jerne, s\u00e5 i dette dokument giver jeg ikke links til kurser. Det er hensigtsm\u00e6ssigt at studere s\u00e5danne systemer, mens man arbejder p\u00e5 et specifikt projekt i en konkret virksomhed. For at blive bekendt med ETL kan man pr\u00f8ve <noindex><a rel=\"nofollow\" href=\"https:\/\/www.talend.com\/\">Talend<\/a><\/noindex> eller <noindex><a rel=\"nofollow\" href=\"https:\/\/airflow.apache.org\/\">Airflow<\/a><\/noindex>.<\/p>\n<p>Efter min mening er det vigtigt at studere den moderne metodologi til design af datalagre Data Vault <noindex><a rel=\"nofollow\" href=\"https:\/\/habr.com\/ru\/post\/348188\/\">link 1<\/a><\/noindex>, <noindex><a rel=\"nofollow\" href=\"http:\/\/www.dwh-club.com\/ru\/dwh-bi-articles\/vse-o-data-vault.html\">link 2<\/a><\/noindex>. Og den bedste m\u00e5de at l\u00e6re det p\u00e5 er at tage det og implementere det i et simpelt eksempel. P\u00e5 GitHub er der flere eksempler p\u00e5 implementering af Data Vault. <noindex><a rel=\"nofollow\" href=\"https:\/\/github.com\/semashkinvg\/DataVault\">link<\/a><\/noindex>. Moderne bog om datalagre: Modeling the Agile Data Warehouse with Data Vault af Hans Hultgren.<\/p>\n<p>For at l\u00e6re om Business Intelligence-v\u00e6rkt\u00f8jer til slutbrugere kan man bruge den gratis rapport-, dashboard- og mini-datalagerbygger Power BI Desktop. L\u00e6ringsmaterialer: <noindex><a rel=\"nofollow\" href=\"https:\/\/docs.microsoft.com\/ru-ru\/learn\/paths\/create-use-analytics-reports-power-bi\/\">link 1<\/a><\/noindex>, <noindex><a rel=\"nofollow\" href=\"https:\/\/docs.microsoft.com\/ru-ru\/learn\/paths\/consume-data-with-power-bi\/\">link 2<\/a><\/noindex>.<\/p>\n<h2>Hadoop og Big Data<\/h2>\n<p><\/p>\n<ul>\n<li>Begynd med at implementere MapReduce selv uden tredjepartsbiblioteker. Det vil i fremtiden give en bedre forst\u00e5else for multitr\u00e5dede implementeringer. Et fremragende eksempel p\u00e5 Python er beskrevet <noindex><a rel=\"nofollow\" href=\"http:\/\/michaelnielsen.org\/blog\/write-your-first-mapreduce-program-in-20-minutes\/\">her<\/a><\/noindex>.<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/stepik.org\/course\/150\">Hadoop. Et system til behandling af store datam\u00e6ngder.<\/a><\/noindex> <\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/openedu.ru\/course\/misis\/ABD\/\">Introduktion til stor data engineering <\/a><\/noindex><\/li>\n<\/ul>\n<p><\/p>\n<h2>Konklusion<\/h2>\n<p>\nIkke alt, hvad man l\u00e6rer, kan anvendes i arbejdet. Derfor er et diplomprojekt n\u00f8dvendigt, hvor man kan pr\u00f8ve at anvende de nye f\u00e6rdigheder. <\/p>\n<p>Planen indeholder ikke emner relateret til dataanalyse og Machine Learning, da dette mere h\u00f8rer til professionen Data Scientist. Der er heller ikke emner relateret til cloud-l\u00f8sninger s\u00e5som AWS eller Azure, da disse emner i h\u00f8j grad afh\u00e6nger af valget af platform.<\/p>\n<p>Sp\u00f8rgsm\u00e5l til samfundet:<br \/>\nHvor rimelig er min plan for udvikling? Hvad skal jeg fjerne eller tilf\u00f8je?<br \/>\nHvilket projekt vil I anbefale som diplomarbejde?<br \/>\n<br \/>Kilde: <a content=\"nofollow\" rel=\"nofollow\" href=\"https:\/\/habr.com\/ru\/post\/472622\/\">habr.com<\/a><\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"<p>\u041f\u043e\u0441\u043b\u0435\u0434\u043d\u0438\u0435 \u0432\u043e\u0441\u0435\u043c\u044c \u043b\u0435\u0442 \u044f \u0440\u0430\u0431\u043e\u0442\u0430\u044e \u0440\u0443\u043a\u043e\u0432\u043e\u0434\u0438\u0442\u0435\u043b\u0435\u043c \u043f\u0440\u043e\u0435\u043a\u0442\u043e\u0432 (\u043d\u0435 \u043f\u0438\u0448\u0443 \u043a\u043e\u0434 \u043d\u0430 \u0440\u0430\u0431\u043e\u0442\u0435), \u0447\u0442\u043e \u0435\u0441\u0442\u0435\u0441\u0442\u0432\u0435\u043d\u043d\u043e \u043d\u0435\u0433\u0430\u0442\u0438\u0432\u043d\u043e \u0432\u043b\u0438\u044f\u0435\u0442 \u043d\u0430 \u043c\u043e\u0439 \u0442\u0435\u0445\u043d\u043e\u043b\u043e\u0433\u0438\u0447\u0435\u0441\u043a\u0438\u0439 \u0431\u0435\u043a\u044d\u043d\u0434. \u042f \u0440\u0435\u0448\u0438\u043b \u0441\u043e\u043a\u0440\u0430\u0442\u0438\u0442\u044c \u0441\u0432\u043e\u0451 \u0442\u0435\u0445\u043d\u043e\u043b\u043e\u0433\u0438\u0447\u0435\u0441\u043a\u043e\u0435 \u043e\u0442\u0441\u0442\u0430\u0432\u0430\u043d\u0438\u0435 \u0438 \u043f\u043e\u043b\u0443\u0447\u0438\u0442\u044c \u043f\u0440\u043e\u0444\u0435\u0441\u0441\u0438\u044e Data engineer. \u041e\u0441\u043d\u043e\u0432\u043d\u043e\u0439 \u043d\u0430\u0432\u044b\u043a Data engineer \u2014 \u0441\u043f\u043e\u0441\u043e\u0431\u043d\u043e\u0441\u0442\u044c \u0440\u0430\u0437\u0440\u0430\u0431\u0430\u0442\u044b\u0432\u0430\u0442\u044c, \u0441\u0442\u0440\u043e\u0438\u0442\u044c \u0438 \u043f\u043e\u0434\u0434\u0435\u0440\u0436\u0438\u0432\u0430\u0442\u044c \u0445\u0440\u0430\u043d\u0438\u043b\u0438\u0449\u0430 \u0434\u0430\u043d\u043d\u044b\u0445. \u0421\u043e\u0441\u0442\u0430\u0432\u0438\u043b \u043f\u043b\u0430\u043d \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f, \u0434\u0443\u043c\u0430\u044e \u043e\u043d \u0431\u0443\u0434\u0435\u0442 \u043f\u043e\u043b\u0435\u0437\u0435\u043d \u043d\u0435 \u0442\u043e\u043b\u044c\u043a\u043e \u0434\u043b\u044f \u043c\u0435\u043d\u044f. \u041f\u043b\u0430\u043d [&hellip;]<\/p>\n","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[688],"tags":[],"class_list":["post-39275","post","type-post","status-publish","format-standard","hentry","category-administrirovanie"],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 5.0.3 - aioseo.com -->\n\t<meta name=\"description\" content=\"\u041f\u043e\u0441\u043b\u0435\u0434\u043d\u0438\u0435 \u0432\u043e\u0441\u0435\u043c\u044c \u043b\u0435\u0442 \u044f 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