{"id":55144,"date":"2020-01-13T00:00:00","date_gmt":"2020-01-12T21:00:00","guid":{"rendered":"https:\/\/prohoster.info\/blog\/blog_prohoster\/tableau-v-roznitse-realno"},"modified":"2020-02-18T14:03:13","modified_gmt":"2020-02-18T11:03:13","slug":"tableau-v-roznitse-realno","status":"publish","type":"post","link":"https:\/\/prohoster.info\/lv\/blog\/news\/tableau-v-roznitse-realno","title":{"rendered":"Tableau mazumtirdzniec\u012bb\u0101, vai tas ir iesp\u0113jams?","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"<p><b>Laiks zi\u0146ojumu sagatavo\u0161anai Excel strauji beidzas \u2014 tendence uz \u0113rt\u0101m inform\u0101cijas prezent\u0101cijas un anal\u012bzes r\u012bku izmanto\u0161anu ir redzama vis\u0101s jom\u0101s. M\u0113s jau sen esam apspriedu\u0161i digit\u0101lo p\u0101reju zi\u0146ojumu sagatavo\u0161an\u0101 un izv\u0113l\u0113j\u0101mies vizualiz\u0101cijas un self-service anal\u012btikas sist\u0113mu Tableau. Aleksandrs Bezug\u013cijs, anal\u012btisko risin\u0101jumu un zi\u0146ojumu noda\u013cas vad\u012bt\u0101js Grup\u0101 \"M.Viedo-Eldorado\", past\u0101st\u012bja par pieredzi un rezult\u0101tiem c\u012b\u0146as pane\u013ca izstr\u0101d\u0113.<\/b><\/p>\n<p>Saku uzreiz, ka ne viss, kas tika iepl\u0101nots, izdev\u0101s \u012bstenot, bet pieredze bija interesanta, ceru, ka t\u0101 b\u016bs noder\u012bga ar\u012b jums. Un, ja k\u0101dam ir idejas, k\u0101 to var\u0113ja izdar\u012bt lab\u0101k \u2013 b\u016b\u0161u \u013coti pateic\u012bgs par ieteikumiem un idej\u0101m.<\/p>\n<p><img decoding=\"async\" alt=\"Tableau mazumtirdzniec\u012bb\u0101, vai tas ir iesp\u0113jams?\" src=\"\/wp-content\/uploads\/2020\/01\/81c41899e9b3acf1858a4faa627c121b.png\" style=\"display:block;margin: 0 auto;\" \/><br \/>\n<br \/>\nZem\u0101k ir par to, ar ko m\u0113s sask\u0101r\u0101mies un ko uzzin\u0101j\u0101m.<br \/>\n<noindex><a rel=\"nofollow\" name=\"habracut\"><\/a><\/noindex><\/p>\n<h4>Ar ko m\u0113s s\u0101k\u0101m<\/h4>\n<p>\nGrup\u0101 \"M.Viedo-Eldorado\" ir labi izstr\u0101d\u0101ta datu modelis: struktur\u0113ta inform\u0101cija ar nepiecie\u0161amo uzglab\u0101\u0161anas dzi\u013cumu un milz\u012bgs skaits fiks\u0113t\u0101s formas zi\u0146ojumu (skat. s\u012bk\u0101k <noindex><a rel=\"nofollow\" href=\"https:\/\/habr.com\/ru\/company\/mvideo\/blog\/462015\/\">\u0161aj\u0101 rakst\u0101<\/a><\/noindex>). No tiem anal\u012bti\u0137i veido vai nu kopsavilkuma tabulas vai format\u0113tas izs\u016bt\u012b\u0161anas Excel, vai skaistas prezent\u0101cijas PowerPoint galalietot\u0101jiem.<\/p>\n<p>Aptuveni pirms diviem gadiem, viet\u0101 fiks\u0113t\u0101s formas zi\u0146ojumu, m\u0113s s\u0101k\u0101m izveidot anal\u012btiskos zi\u0146ojumus SAP Analysis (p\u0101rsl\u0113gums uz Excel, b\u016bt\u012bb\u0101 \u2014 kopsavilkuma tabula p\u0101r OLAP dzin\u0113ju). Bet \u0161is r\u012bks nevar\u0113ja nodro\u0161in\u0101t visu lietot\u0101ju vajadz\u012bbas, liel\u0101k\u0101 da\u013ca turpin\u0101ja izmantot inform\u0101ciju, papildus apstr\u0101d\u0101tu anal\u012bti\u0137u.<\/p>\n<p>M\u016bsu galalietot\u0101ji tiek iedal\u012bti tr\u012bs kategorij\u0101s:<\/p>\n<p><b>Augst\u0101k\u0101 vad\u012bba<\/b>. Pieprasa inform\u0101ciju labi noform\u0113t\u0101 un vizu\u0101li saprotam\u0101 veid\u0101.<\/p>\n<p><b>Vid\u0113j\u0101 vad\u012bba<\/b>, progres\u012bvi lietot\u0101ji. Interes\u0113 dati un sp\u0113j patst\u0101v\u012bgi veidot zi\u0146ojumus, ja r\u012bki ir pieejami. Tie\u0161i vi\u0146i k\u013cuva par galvenajiem anal\u012btisko zi\u0146ojumu lietot\u0101jiem SAP Analysis.<\/p>\n<p><b>Masas lietot\u0101ji<\/b>. Neinteres\u0113 pa\u0161p\u0101rvalde datu anal\u012bz\u0113, izmanto zi\u0146ojumus ar ierobe\u017eotu br\u012bv\u012bbas pak\u0101pi, izs\u016bt\u012b\u0161anas un kopsavilkuma tabulu form\u0101t\u0101 Excel.<\/p>\n<p>M\u016bsu ideja bija apmierin\u0101t visu lietot\u0101ju vajadz\u012bbas un sniegt vi\u0146iem vienotu \u0113rtu r\u012bku. S\u0101k\u0101m ar augst\u0101k\u0101 l\u012bme\u0146a vad\u012bbu. Vi\u0146iem bija nepiecie\u0161amas \u0113rtas sada\u013cas, lai analiz\u0113tu galvenos biznesa rezult\u0101tus. T\u0101d\u0113j\u0101di m\u0113s s\u0101k\u0101m ar Tableau un s\u0101kum\u0101 izv\u0113l\u0113j\u0101mies divus virzienus: p\u0101rdo\u0161anas r\u0101d\u012bt\u0101jus mazumtirdzniec\u012bb\u0101 un tie\u0161saist\u0113 ar ierobe\u017eotu anal\u012bzes dzi\u013cumu un platumu, kas aptvertu aptuveni 80% datu, ko piepras\u012bja augst\u0101k\u0101 vad\u012bba.<\/p>\n<p>T\u0101 k\u0101 pane\u013cu lietot\u0101ji bija augst\u0101k\u0101 l\u012bme\u0146a vad\u012bba, rad\u0101s v\u0113l viens papildu produkta KPI \u2013 atbildes \u0101trums. Neviens negaid\u012bs 20\u201330 sekundes, kam\u0113r dati tiek atjaunin\u0101ti. Navig\u0101cijai bija j\u0101b\u016bt 4\u20135 sekun\u017eu ietvaros, v\u0113lams visp\u0101r uzreiz. Un to mums, diem\u017e\u0113l, neizdev\u0101s pan\u0101kt.<\/p>\n<p>T\u0101 izskat\u012bj\u0101s m\u016bsu galven\u0101 pane\u013ca makets:<\/p>\n<p><img decoding=\"async\" alt=\"Tableau mazumtirdzniec\u012bb\u0101, vai tas ir iesp\u0113jams?\" src=\"\/wp-content\/uploads\/2020\/01\/a7a028feee6542dfbc1fd3c2feeaa3de.png\" style=\"display:block;margin: 0 auto;\" \/><br \/>\n<br \/>\nGalven\u0101 ideja ir apvienot galvenos KPI dzin\u0113jus, kuru beig\u0101s uzkr\u0101j\u0101s 19, kreisaj\u0101 pus\u0113 un att\u0113lot to dinamiku un sadal\u012bjumu pa galvenajiem atrib\u016btam labaj\u0101 pus\u0113. Uzdevums \u0161\u0137iet vienk\u0101r\u0161s, vizualiz\u0101cija ir lo\u0123iska un saprotama, l\u012bdz non\u0101c pie deta\u013c\u0101m.<\/p>\n<h2>Deta\u013ca 1. Datu apjoms<\/h2>\n<p>\nGalven\u0101 p\u0101rdo\u0161anas tabula par gadu ir apm\u0113ram 300 miljoni rindu. T\u0101 k\u0101 ir nepiecie\u0161ams atspogu\u013cot dinamiku sal\u012bdzin\u0101jum\u0101 ar iepriek\u0161\u0113jiem gadiem, faktisko p\u0101rdo\u0161anas datu apjoms ir apm\u0113ram 1 miljards rindu. Turkl\u0101t atsevi\u0161\u0137i tiek glab\u0101ta inform\u0101cija par pl\u0101nu datiem un interneta p\u0101rdo\u0161anas bloks. T\u0101d\u0113\u013c, pat neskatoties uz to, ka m\u0113s izmantoj\u0101m kolonnveida in-memory DB SAP HANA, piepras\u012bjuma \u0101trums ar visiem r\u0101d\u012bt\u0101jiem par vienu ned\u0113\u013cu no eso\u0161ajiem kr\u0101jumiem uz lido jau bija ap 15-20 sekund\u0113m. \u0160\u012bs probl\u0113mas risin\u0101jums ir ac\u012bmredzams \u2013 papildu datu materializ\u0101cija. Bet taj\u0101 ar\u012b ir sl\u0113ptie riski, par kuriem run\u0101\u0161u zem\u0101k.<\/p>\n<h2>Deta\u013ca 2. Neadit\u012bvie r\u0101d\u012bt\u0101ji<\/h2>\n<p>\nMums daudzi KPI ir saist\u012bti ar \u010dekiem. Un \u0161is r\u0101d\u012bt\u0101js atspogu\u013co COUNT DISTINCT rindu (\u010deku virsrakstu) skaitu un r\u0101da at\u0161\u0137ir\u012bgas summas atkar\u012bb\u0101 no izv\u0113l\u0113tajiem atrib\u016btiem. Piem\u0113ram, k\u0101 \u0161im r\u0101d\u012bt\u0101jam un t\u0101 atvasin\u0101jumam b\u016btu j\u0101tiek apr\u0113\u0137in\u0101ti:<\/p>\n<p><img decoding=\"async\" alt=\"Tableau mazumtirdzniec\u012bb\u0101, vai tas ir iesp\u0113jams?\" src=\"\/wp-content\/uploads\/2020\/01\/0a6d676f0a5c2b779a5e7892b1f54929.png\" style=\"display:block;margin: 0 auto;\" \/><br \/>\n<br \/>\nLai nodro\u0161in\u0101tu apr\u0113\u0137inu precizit\u0101ti, var:<\/p>\n<ul>\n<li>Veikt \u0161\u0101du r\u0101d\u012bt\u0101ju apr\u0113\u0137in\u0101\u0161anu uz vietas datu kr\u0101tuv\u0113;\n<\/li>\n<li>Veikt apr\u0113\u0137inu uz visa datu apjoma Tableau, t.i., p\u0113c piepras\u012bjuma Tableau atdot visus datus, \u0146emot v\u0113r\u0101 izv\u0113l\u0113tos filtrus \u010dek\u0101\u0146u poz\u012bciju granularit\u0101t\u0113;\n<\/li>\n<li>Izveidot materializ\u0113tu vitr\u012bnu, kur\u0101 tiks apr\u0113\u0137in\u0101ti visi r\u0101d\u012bt\u0101ji visos izv\u0113les variantos, kas sniedz at\u0161\u0137ir\u012bgus neadit\u012bvus rezult\u0101tus.\n<\/li>\n<\/ul>\n<p>\nIr skaidrs, ka piem\u0113r\u0101 UTE1 un UTE2 ir materi\u0101la atrib\u016bti, kas att\u0113lo pre\u010du hierarhiju. Tas nav statisks j\u0113dziens, caur to notiek vad\u012bba iek\u0161\u0113j\u0101 uz\u0146\u0113mum\u0101, jo par da\u017e\u0101d\u0101m pre\u010du grup\u0101m atbild da\u017e\u0101di mened\u017eeri. Mums ir bijusi liela glob\u0101la \u0161\u012bs hierarhijas p\u0101rskat\u012b\u0161ana, kad main\u012bj\u0101s visi l\u012bme\u0146i, kad tika p\u0101rskat\u012btas savstarp\u0113j\u0101s attiec\u012bbas, k\u0101 ar\u012b regul\u0101ras punktveida izmai\u0146as, kad viena grupa p\u0101riet no viena mezgla uz citu. Parastaj\u0101 p\u0101rskat\u0101 tas viss tiek apr\u0113\u0137in\u0101ts uz vietas no materi\u0101la atrib\u016btiem, bet, ja \u0161os datus materializ\u0113, ir nepiecie\u0161ams izstr\u0101d\u0101t meh\u0101nismu, lai izsekotu \u0161\u0101das izmai\u0146as un autom\u0101tiski atjaunotu v\u0113sturiskos datus. Tas ir \u013coti sare\u017e\u0123\u012bts uzdevums.<\/p>\n<h2>Deta\u013cas 3. Datu sal\u012bdzin\u0101\u0161ana <\/h2>\n<p>\n\u0160is punkts ir l\u012bdz\u012bgs iepriek\u0161\u0113jam. J\u0113ga ir t\u0101da, ka uz\u0146\u0113mum\u0101, analiz\u0113jot, ir pie\u0146emts izveidot vair\u0101kus sal\u012bdzin\u0101\u0161anas l\u012bme\u0146us ar iepriek\u0161\u0113jo periodu:<\/p>\n<p><i>Sal\u012bdzin\u0101\u0161ana ar iepriek\u0161\u0113jo periodu (diena pret dienu, ned\u0113\u013ca pret ned\u0113\u013cu, m\u0113nesis pret m\u0113nesi)<\/i><\/p>\n<p>\u0160aj\u0101 sal\u012bdzin\u0101jum\u0101 tiks pie\u0146emts, ka, atkar\u012bb\u0101 no lietot\u0101ja izv\u0113l\u0113t\u0101 perioda (piem\u0113ram, 33. gada ned\u0113\u013ca), mums j\u0101par\u0101da dinamika pret 32. ned\u0113\u013cu. Ja m\u0113s izv\u0113l\u0113tos datus par m\u0113nesi, piem\u0113ram, maiju, tad \u0161is sal\u012bdzin\u0101jums par\u0101d\u012btu dinamiku pret apr\u012bli.<\/p>\n<p><i>Sal\u012bdzin\u0101\u0161ana ar iepriek\u0161\u0113jo gadu<\/i><\/p>\n<p>\u0160eit galvenais nianses ir taj\u0101, ka, sal\u012bdzinot pa dien\u0101m un ned\u0113\u013c\u0101m, j\u016bs ne\u0146emiet to pa\u0161u dienu iepriek\u0161\u0113j\u0101 gad\u0101, t.i., j\u016bs nevarat vienk\u0101r\u0161i \u0146emt pa\u0161reiz\u0113jo gadu m\u012bnus viens. Jums ir j\u0101piev\u0113r\u0161as sal\u012bdzin\u0101tajai ned\u0113\u013cas dienai. Bet, sal\u012bdzinot m\u0113ne\u0161us, pret\u0113ji, ir j\u0101\u0146em tie\u0161i t\u0101ds pats kalend\u0101ra dienas iepriek\u0161\u0113j\u0101 gad\u0101. Ir ar\u012b nianses ar izsl\u0113gtu gadiem. Avota kr\u0101tuv\u0113s visa inform\u0101cija ir sadal\u012bta pa dien\u0101m, tur nav atsevi\u0161\u0137u lauku ned\u0113\u013c\u0101m, m\u0113ne\u0161iem, gadiem. T\u0101p\u0113c, lai ieg\u016btu piln\u012bgu anal\u012btisko p\u0101rskatu panel\u012b, nav j\u0101r\u0113\u0137ina viens periods, piem\u0113ram, ned\u0113\u013ca, bet 4 ned\u0113\u013cas, un p\u0113c tam \u0161os datus v\u0113l ir j\u0101sal\u012bdzina, atspogu\u013cojot dinamiku, novirzes. Attiec\u012bgi \u0161o dinamisk\u0101s sal\u012bdzin\u0101\u0161anas lo\u0123iku var realiz\u0113t vai nu Tableau, vai uz vitr\u012bnas puses. J\u0101, un par \u0161\u012bm deta\u013c\u0101m m\u0113s, protams, zin\u0101j\u0101m un dom\u0101j\u0101m v\u0113l projekt\u0113\u0161anas posm\u0101, bet to ietekmi uz gala pane\u013ca veiktsp\u0113ju prognoz\u0113t bija gr\u016bti.<\/p>\n<p>Datu pane\u013ca ievie\u0161an\u0101 m\u0113s g\u0101j\u0101m pa garu Agile ce\u013cu. M\u016bsu uzdevums bija p\u0113c iesp\u0113jas \u0101tr\u0101k nodro\u0161in\u0101t test\u0113\u0161anai str\u0101d\u0101jo\u0161u r\u012bku ar nepiecie\u0161amajiem datiem. T\u0101p\u0113c m\u0113s dev\u0101mies sprintos un balst\u012bj\u0101mies uz pa\u0161reiz\u0113j\u0101 kr\u0101tuves darba minimiz\u0101ciju.<\/p>\n<h2>1. da\u013ca. Tic\u012bba Tableau<\/h2>\n<p>\nLai vienk\u0101r\u0161otu IT atbalstu un \u0101tri ieviestu izmai\u0146as, m\u0113s pie\u0146\u0113m\u0101m l\u0113mumu izstr\u0101d\u0101t neaddit\u012bvo r\u0101d\u012bt\u0101ju apr\u0113\u0137ina un iepriek\u0161\u0113jo periodu sal\u012bdzin\u0101\u0161anas lo\u0123iku Tableau.<\/p>\n<h3>1. posms. Viss ir Live, nek\u0101das papildin\u0101\u0161anas vitr\u012bn\u0101m.<\/h3>\n<p>\n\u0160aj\u0101 posm\u0101 m\u0113s pievienoj\u0101m Tableau eso\u0161ajiem vitr\u012bn\u0101m un nol\u0113m\u0101m apskat\u012bt, k\u0101 tiks apr\u0113\u0137in\u0101ts \u010deku skaits gada laik\u0101.<\/p>\n<p><b>Rezult\u0101ts:<\/b><\/p>\n<p>Atbilde bija nom\u0101co\u0161a \u2013 20 min\u016btes. Datu p\u0101rs\u016bt\u012b\u0161ana pa t\u012bklu, augsta slodze uz Tableau. M\u0113s saprat\u0101m, ka lo\u0123iku ar neaddit\u012bvajiem r\u0101d\u012bt\u0101jiem ir j\u0101realiz\u0113 uz HANA. M\u016bs tas nebaid\u012bja, mums jau bija l\u012bdz\u012bga pieredze ar BO un Analysis un b\u016bv\u0113t \u0101tras vitr\u012bnas HANA, kas sniedz pareizi apr\u0113\u0137in\u0101tus neaddit\u012bvos r\u0101d\u012bt\u0101jus, m\u0113s prat\u0101m. Tagad bija j\u0101saska\u0146o t\u0101s ar Tableau.<\/p>\n<h3>2. posms. Piel\u0101gojam vitr\u012bnas, nek\u0101das materializ\u0101cijas, viss uz vietas.<\/h3>\n<p>\nM\u0113s izveidoj\u0101m atsevi\u0161\u0137u jaunu vitr\u012bnu, kas uzreiz sniedza nepiecie\u0161amos datus TABLEAU. Kopum\u0101 m\u0113s ieguv\u0101m labu rezult\u0101tu, samazinot visu r\u0101d\u012bt\u0101ju \u0123ener\u0113\u0161anas laiku no ned\u0113\u013cas l\u012bdz 9-10 sekund\u0113m. God\u012bgi skatoties, gaid\u012bj\u0101m, ka Tableau atbildes laiks vis\u0101 d\u0113l\u012b b\u016bs 20-30 sekundes pirmaj\u0101 atv\u0113r\u0161an\u0101 un p\u0113c tam, pateicoties ke\u0161atmi\u0146ai, no 10 l\u012bdz 12 sekund\u0113m, kas m\u016bs kopum\u0101 apmierin\u0101tu.<\/p>\n<p><b>Rezult\u0101ts:<\/b><\/p>\n<p>Pirmaj\u0101s atv\u0113rtaj\u0101s d\u0113l\u012b: 4-5 min\u016btes<br \/>\nIkviens klik\u0161\u0137is: 3-4 min\u016btes<br \/>\nNeviens negaid\u012bja \u0161\u0101du papildu uzlabojumu vitr\u012bnas darb\u0101.<\/p>\n<h2>2. da\u013ca. Iedzi\u013cin\u0101\u0161an\u0101s Tableau<\/h2>\n<p><\/p>\n<h3>1. posms. Tableau veiktsp\u0113jas anal\u012bze un \u0101tra tuning<\/h3>\n<p>\nM\u0113s s\u0101k\u0101m analiz\u0113t, uz ko Tableau t\u0113r\u0113 galveno laiku. Un tam ir patie\u0161\u0101m labi r\u012bki, kas, protams, ir plus Tableau. Galven\u0101 probl\u0113ma, ko m\u0113s identific\u0113j\u0101m, bija \u013coti sare\u017e\u0123\u012bti SQL vaic\u0101jumi, kurus b\u016bv\u0113ja Tableau. Tie bija saist\u012bti galvenok\u0101rt ar:<\/p>\n<p> \u2014 datu transpon\u0113\u0161anu. T\u0101 k\u0101 Tableau nav r\u012bku datasetu transpon\u0113\u0161anai, tad, lai izveidotu kreiso d\u0113\u013ca da\u013cu ar detaliz\u0113tu visu KPI att\u0113lo\u0161anu, mums bija j\u0101veido tabula, izmantojot case. SQL vaic\u0101jumu izm\u0113rs DB sasniedza 120 000 rakstz\u012bmes.<\/p>\n<p><img decoding=\"async\" alt=\"Tableau mazumtirdzniec\u012bb\u0101, vai tas ir iesp\u0113jams?\" src=\"\/wp-content\/uploads\/2020\/01\/8fc4d99017ddd604bbabb5ea0a19b38d.png\" style=\"display:block;margin: 0 auto;\" \/><br \/>\n<br \/>\n \u2014 laika perioda izv\u0113li. \u0160\u0101ds vaic\u0101jums DB l\u012bmen\u012b pras\u012bja vair\u0101k laika kompil\u0101cijai nek\u0101 izpildei:<\/p>\n<p><img decoding=\"async\" alt=\"Tableau mazumtirdzniec\u012bb\u0101, vai tas ir iesp\u0113jams?\" src=\"\/wp-content\/uploads\/2020\/01\/a9b9cc6ddd6b03c643935d070532728e.png\" style=\"display:block;margin: 0 auto;\" \/><br \/>\n<br \/>\nT.i., vaic\u0101juma apstr\u0101de 12 sekundes + 5 sekundes izpilde.<\/p>\n<p>M\u0113s nol\u0113m\u0101m vienk\u0101r\u0161ot apr\u0113\u0137inu lo\u0123iku Tableau pus\u0113 un p\u0101rcelt v\u0113l vienu da\u013cu apr\u0113\u0137inu uz vitr\u012bnu un DB l\u012bmeni. Tas deva labus rezult\u0101tus.<\/p>\n<p>Vispirms m\u0113s veic\u0101m transpon\u0113\u0161anu uz vietas, izmantojot pilnu \u0101r\u0113jo saiti gala VIEW apr\u0113\u0137ina posm\u0101, saska\u0146\u0101 ar \u0161\u0101du pieeju, kas aprakst\u012bta wiki <noindex><a rel=\"nofollow\" href=\"http:\/\/en.wikipedia.org\/wiki\/Transpose\">Transpose \u2014 Vikip\u0113dija, br\u012bv\u0101 enciklop\u0113dija<\/a><\/noindex> un <noindex><a rel=\"nofollow\" href=\"http:\/\/en.wikipedia.org\/wiki\/Elementary_matrix#Row-addition_transformations\">Elementary matrix \u2014 Vikip\u0113dija, br\u012bv\u0101 enciklop\u0113dija<\/a><\/noindex>.<\/p>\n<p><img decoding=\"async\" alt=\"Tableau mazumtirdzniec\u012bb\u0101, vai tas ir iesp\u0113jams?\" src=\"\/wp-content\/uploads\/2020\/01\/5259995831dc8ae379a34bfe84e52daa.png\" style=\"display:block;margin: 0 auto;\" \/><br \/>\n<br \/>\nT\u0101tad m\u0113s izveidoj\u0101m konfigur\u0101cijas tabulu \u2013 transpon\u0113\u0161anas matricu (21x21) un sa\u0146\u0113m\u0101m visus r\u0101d\u012bt\u0101jus rindu sadal\u012bjum\u0101.<\/p>\n<p>Bija:<br \/>\n<img decoding=\"async\" alt=\"Tableau mazumtirdzniec\u012bb\u0101, vai tas ir iesp\u0113jams?\" src=\"\/wp-content\/uploads\/2020\/01\/9382ee65a1482cc137a52b5f80c39eeb.png\" style=\"display:block;margin: 0 auto;\" \/><br \/>\n<br \/>\nK\u013cuva par:<br \/>\n<img decoding=\"async\" alt=\"Tableau mazumtirdzniec\u012bb\u0101, vai tas ir iesp\u0113jams?\" src=\"\/wp-content\/uploads\/2020\/01\/1d6653ec427ce0621b441943f589d860.png\" style=\"display:block;margin: 0 auto;\" \/><br \/>\n<br \/>\nDatu transpon\u0113\u0161ana gandr\u012bz neprasa laiku. Piepras\u012bjums p\u0113c visiem r\u0101d\u012bt\u0101jiem ned\u0113\u013cas laik\u0101 joproj\u0101m tika izpild\u012bts aptuveni 10 sekun\u017eu laik\u0101. Ta\u010du tagad ir zaud\u0113ta elast\u012bba attiec\u012bb\u0101 uz konkr\u0113to r\u0101d\u012bt\u0101ju pane\u013ca izveidi, t.i., pane\u013ca labaj\u0101 pus\u0113, kur att\u0113lota dinamika un detaliz\u0113ta konkr\u0113ta r\u0101d\u012bt\u0101ja sadal\u012bjums, iepriek\u0161 skat\u012bjums str\u0101d\u0101ja 1-3 sekundes, jo piepras\u012bjums tika veikts p\u0113c viena r\u0101d\u012bt\u0101ja, bet tagad datub\u0101ze vienm\u0113r atlas\u012bja visus r\u0101d\u012bt\u0101jus un filtr\u0113ja rezult\u0101tu tikai pirms to atgrie\u0161anas Tableau.<\/p>\n<p>Kopum\u0101 pane\u013ca darb\u012bbas \u0101trums samazin\u0101j\u0101s gandr\u012bz tr\u012bs reizes.<\/p>\n<p><b>Rezult\u0101ts:<\/b><\/p>\n<ol>\n<li>5 sek \u2014 pane\u013ca un vizualiz\u0101ciju pars\u0113\u0161ana<\/li>\n<li> 15-20 sek \u2014 sagatavo\u0161ana piepras\u012bjumu kompil\u0101cijai ar iepriek\u0161\u0113jo apr\u0113\u0137inu veik\u0161anu Tableau<\/li>\n<li> 35-45 sek \u2014 SQL piepras\u012bjumu kompil\u0101cija un taj\u0101 pa\u0161\u0101 laik\u0101 to sec\u012bga izpilde Hana<\/li>\n<li> 5 sek \u2014 rezult\u0101tu apstr\u0101de, \u0161\u0137iro\u0161ana, vizualiz\u0101ciju p\u0101rskait\u012b\u0161ana Tableau<\/li>\n<li>Protams, \u0161\u0101di rezult\u0101ti neg\u0101ja pie sirds biznesam, t\u0101p\u0113c turpin\u0101j\u0101m optimiz\u0101ciju.<\/li>\n<\/ol>\n<p><\/p>\n<h3>Posms 2. Minim\u0101la lo\u0123ika Tableau, piln\u012bga materializ\u0101cija<\/h3>\n<p>\nM\u0113s saprat\u0101m, ka nav iesp\u0113jams izveidot pane\u013ca atbildes laiku da\u017eu sekun\u017eu laik\u0101, ja skat\u012bjums darbojas 10 sekundes, un apsv\u0113r\u0101m datu materializ\u0101cijas iesp\u0113jas datub\u0101zes pus\u0113 tie\u0161i pras\u012btajam panelim. Bet mums bija j\u0101risina glob\u0101la probl\u0113ma, k\u0101 min\u0113ts iepriek\u0161 \u2013 neadit\u012bvi r\u0101d\u012bt\u0101ji. M\u0113s nevar\u0113j\u0101m izveidot t\u0101, lai mainot filtrus vai izkliedes Tableau elast\u012bgi p\u0101rsl\u0113gtos starp da\u017e\u0101diem skat\u012bjumiem un l\u012bme\u0146iem, kas iepriek\u0161 apr\u0113\u0137in\u0101ti da\u017e\u0101d\u0101m produktu hierarhij\u0101m (piem\u0113r\u0101 tr\u012bs piepras\u012bjumi bez UTE, ar UTE1 un UTE2 veido at\u0161\u0137ir\u012bgus rezult\u0101tus). T\u0101p\u0113c m\u0113s pie\u0146\u0113m\u0101m l\u0113mumu vienk\u0101r\u0161ot paneli, atteikties no produktu hierarhijas panel\u012b un noskaidrot, cik \u0101trs tas var b\u016bt vienk\u0101r\u0161ot\u0101 versij\u0101.<\/p>\n<p>T\u0101tad, \u0161aj\u0101 p\u0113d\u0113j\u0101 posm\u0101 m\u0113s izveidoj\u0101m atsevi\u0161\u0137u kr\u0101tuvi, kur\u0101 transpon\u0113t\u0101 veid\u0101 saglab\u0101j\u0101m visus KPI. Datub\u0101zes pus\u0113 jebkuram piepras\u012bjumam uz \u0161\u0101du kr\u0101tuvi tiek izpild\u012bts 0,1 \u2013 0,3 sekun\u017eu laik\u0101. Panel\u012b m\u0113s sa\u0146\u0113m\u0101m \u0161\u0101dus rezult\u0101tus:<\/p>\n<p>Pirmais atkl\u0101jums: 8-10 sekundes<br \/>\nJebkura klik\u0161\u0137is: 6-7 sekundes<\/p>\n<p>Laiks, ko t\u0113r\u0113 Tableau, sast\u0101v no:<\/p>\n<ol>\n<li>0,3 sek. \u2014 pane\u013ca pars\u0113\u0161ana un SQL piepras\u012bjumu kompil\u0101cija\n<\/li>\n<li>1,5-3 sek. \u2014 SQL piepras\u012bjumu izpilde Hana galvenaj\u0101m vizualiz\u0101cij\u0101m (s\u0101kas paral\u0113li ar 1. punktu)\n<\/li>\n<li>1,5-2 sek. \u2014 render\u0113\u0161ana, vizualiz\u0101ciju p\u0101rr\u0113\u0137in\u0101\u0161ana\n<\/li>\n<li>1,3 sek. \u2014 papildus SQL vaic\u0101jumu izpilde, lai ieg\u016btu atbilsto\u0161\u0101s filtru v\u0113rt\u012bbas (Z\u012bmols, D\u012bvizions, Pils\u0113ta, Veikals), rezult\u0101tu pars\u0113\u0161ana\n<\/li>\n<\/ol>\n<p><\/p>\n<h3>Ja j\u0101izdara \u012bss kopsavilkums<\/h3>\n<p>\nMums patika instrumenta Tableau vizualiz\u0101cijas aspekt\u0101. Projekt\u0113\u0161anas posm\u0101 m\u0113s apl\u016bkoj\u0101m da\u017e\u0101dus vizualiz\u0101cijas elementus un visus tos atrad\u0101m bibliot\u0113k\u0101s, tostarp sare\u017e\u0123\u012btas daudzsl\u0101\u0146u segment\u0101cijas un daudzp\u0101rraides waterfall.<\/p>\n<p>Ievie\u0161ot p\u0101rdo\u0161anas galvenos r\u0101d\u012bt\u0101jus, m\u0113s sask\u0101r\u0101mies ar veiktsp\u0113jas probl\u0113m\u0101m, kuras pagaid\u0101m neesam sp\u0113ju\u0161i nov\u0113rst. M\u0113s pavad\u012bj\u0101m vair\u0101k nek\u0101 divus m\u0113ne\u0161us un sa\u0146\u0113m\u0101m funkcion\u0101li nepiln\u012bgu pane\u013cu, kuru reakcijas \u0101trums bija uz pie\u013caujam\u0101 robe\u017eas. Un m\u0113s izdar\u012bj\u0101m secin\u0101jumus:<\/p>\n<ol>\n<li>Tableau nesp\u0113j str\u0101d\u0101t ar lieliem datu apjomiem. Ja j\u016bsu s\u0101kotn\u0113j\u0101 datu model\u012b ir vair\u0101k nek\u0101 10 GB datu (aptuveni 200 miljoni x 50 rindu), tad inform\u0101cijas panelis nopietni pal\u0113nin\u0101s \u2013 no 10 sekund\u0113m l\u012bdz da\u017e\u0101m min\u016bt\u0113m katram klik\u0161\u0137im. M\u0113s eksperiment\u0113j\u0101m gan ar live-connect, gan ar ekstraktu. Darb\u012bbas \u0101trums ir sal\u012bdzino\u0161i l\u012bdz\u012bgs.\n<\/li>\n<li>Ierobe\u017eojumi, izmantojot vair\u0101kas datu kr\u0101tuves (datakomplekti). Nav iesp\u0113jas standarta veid\u0101 nor\u0101d\u012bt datu komplektu savstarp\u0113j\u0101s attiec\u012bbas. Ja izmantojat apvedce\u013cu risin\u0101jumus datu komplektu savienojumam, tas b\u016btiski atspogu\u013cos veiktsp\u0113ju. M\u016bsu gad\u012bjum\u0101 m\u0113s apsv\u0113ra variantu datu materializ\u0113\u0161anai katr\u0101 nepiecie\u0161amaj\u0101 griezum\u0101, un uz \u0161iem materializ\u0113tajiem datu komplektiem veikt p\u0101rl\u0113kumus ar iepriek\u0161 izv\u0113l\u0113tiem filtriem \u2013 tas izr\u0101d\u012bj\u0101s neiesp\u0113jami izdar\u012bt Tableau.\n<\/li>\n<li>Tableau nav iesp\u0113jams izveidot dinamiskos parametrus. J\u016bs nevarat parametru, kas tiek izmantots datu komplekta filtr\u0113\u0161anai ekstrakt\u0101 vai tie\u0161aj\u0101 savienojum\u0101, aizpild\u012bt ar citas izv\u0113les rezult\u0101tu no datu komplekta vai cita SQL vaic\u0101juma rezult\u0101ta, tikai nat\u012bvo lietot\u0101ja ievadi vai konstantu.\n<\/li>\n<li>Ierobe\u017eojumi, kas saist\u012bti ar pane\u013ca izveido\u0161anu ar OLAP|Kopsavilkuma tabulas elementiem. <br \/>\nMSTR, SAP SAC, SAP Analysis, ja pievienojat datu kopu zi\u0146ojumam, visi objekti uz t\u0101 ir savstarp\u0113ji saist\u012bti p\u0113c noklus\u0113juma. Tableau tam nav, saist\u012bbu j\u0101iestata manu\u0101li. Tas, iesp\u0113jams, ir elast\u012bg\u0101k, ta\u010du visiem m\u016bsu vad\u012bbas pane\u013ciem tas ir oblig\u0101ts pras\u012bbas elements \u2013 t\u0101p\u0113c tas papildus palielina darba slodzi. Turkl\u0101t, ja veidojat saist\u012btus filtrus, lai, piem\u0113ram, filtr\u0113jot re\u0123ionu, pils\u0113tu saraksts tiktu ierobe\u017eots tikai uz \u0161\u012b re\u0123iona pils\u0113t\u0101m, j\u016bs uzreiz saskarsities ar sec\u012bgiem piepras\u012bjumiem uz DB vai Ekstrahu, kas iev\u0113rojami pal\u0113nina vad\u012bbas paneli.<\/li>\n<li>R\u016bp\u012bbu ierobe\u017eojumi funkcij\u0101s. Ne par ekstraktu, ne par datu kopu no Live-connecta nevar veikt masveida p\u0101rveidojumus. To var izdar\u012bt caur Tableau Prep, bet tas ir papildu darba slogs un v\u0113l viens instruments, kuru j\u0101apg\u016bst un j\u0101tur. J\u016bs, piem\u0113ram, nevarat transpon\u0113t datus, izveidot savienojumu ar pa\u0161iem sevi. Tas aizveras caur kolonn\u0101m vai lauka atsevi\u0161\u0137\u0101m p\u0101rveido\u0161an\u0101m, kas j\u0101izv\u0113las caur case vai if, un tas rada \u013coti sare\u017e\u0123\u012btus SQL piepras\u012bjumus, kuros datub\u0101ze pavad\u012bs liel\u0101ko da\u013cu laika, kompil\u0113jot piepras\u012bjuma tekstu. \u0160\u012bs instrumenta neelast\u012bbas bija j\u0101saraksta l\u012bme\u0146a vitr\u012bn\u0101, kas noved pie datu glab\u0101\u0161anas sare\u017e\u0123\u012bjuma, papildu slodz\u0113m un p\u0101rveido\u0161an\u0101m.\n<\/li>\n<\/ol>\n<p>\nM\u0113s neesam noliku\u0161i krustu uz Tableau. Bet k\u0101 instrumentu, kas sp\u0113j veidot r\u016bpnieciskus vad\u012bbas pane\u013cus un l\u012bdzekli, ar kura pal\u012bdz\u012bbu var aizst\u0101t un digitaliz\u0113t visu uz\u0146\u0113muma korporat\u012bv\u0101s p\u0101rskatu sist\u0113mas, Tableau netiek apsv\u0113rts.<\/p>\n<p>\u0160obr\u012bd akt\u012bvi izstr\u0101d\u0101jam l\u012bdz\u012bgu vad\u012bbas paneli cit\u0101 instrument\u0101 un paral\u0113li m\u0113\u0123in\u0101m p\u0101rskat\u012bt vad\u012bbas pane\u013ca arhitekt\u016bru Tableau, lai to v\u0113l vair\u0101k atvieglotu. Ja kopiena b\u016bs ieinteres\u0113ta \u2013 past\u0101st\u012bsim par rezult\u0101tiem.<\/p>\n<p>T\u0101pat gaid\u0101m j\u016bsu idejas vai padomus par to, k\u0101 Tableau var b\u016bv\u0113t \u0101trus vad\u012bbas pane\u013cus uz tik lieliem datu apjomiem, jo mums ir ar\u012b vietne, kur datu ir daudz vair\u0101k nek\u0101 mazumtirdzniec\u012bb\u0101.<br \/>\n<br \/>Avots: <a content=\"nofollow\" rel=\"nofollow\" href=\"https:\/\/habr.com\/ru\/company\/mvideo\/blog\/483656\/\">habr.com<\/a><\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"<p>\u0412\u0440\u0435\u043c\u044f \u043e\u0442\u0447\u0451\u0442\u043d\u043e\u0441\u0442\u0438 \u0432 Excel \u0441\u0442\u0440\u0435\u043c\u0438\u0442\u0435\u043b\u044c\u043d\u043e \u0443\u0445\u043e\u0434\u0438\u0442 \u2014 \u0442\u0440\u0435\u043d\u0434 \u043d\u0430 \u0443\u0434\u043e\u0431\u043d\u044b\u0435 \u0438\u043d\u0441\u0442\u0440\u0443\u043c\u0435\u043d\u0442\u044b \u043f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u043b\u0435\u043d\u0438\u044f \u0438 \u0430\u043d\u0430\u043b\u0438\u0437\u0430 \u0438\u043d\u0444\u043e\u0440\u043c\u0430\u0446\u0438\u0438 \u0432\u0438\u0434\u0435\u043d \u0432\u043e \u0432\u0441\u0435\u0445 \u0441\u0444\u0435\u0440\u0430\u0445. \u041c\u044b \u0434\u0430\u0432\u043d\u043e \u043e\u0431\u0441\u0443\u0436\u0434\u0430\u043b\u0438 \u0432\u043d\u0443\u0442\u0440\u0438 \u0446\u0438\u0444\u0440\u043e\u0432\u0438\u0437\u0430\u0446\u0438\u044e \u043f\u043e\u0441\u0442\u0440\u043e\u0435\u043d\u0438\u044f \u043e\u0442\u0447\u0451\u0442\u043d\u043e\u0441\u0442\u0438 \u0438 \u0432\u044b\u0431\u0440\u0430\u043b\u0438 \u0441\u0438\u0441\u0442\u0435\u043c\u0443 \u0432\u0438\u0437\u0443\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u0438 \u0438 self-service \u0430\u043d\u0430\u043b\u0438\u0442\u0438\u043a\u0438 Tableau. \u0410\u043b\u0435\u043a\u0441\u0430\u043d\u0434\u0440 \u0411\u0435\u0437\u0443\u0433\u043b\u044b\u0439, \u0440\u0443\u043a\u043e\u0432\u043e\u0434\u0438\u0442\u0435\u043b\u044c \u043e\u0442\u0434\u0435\u043b\u0430 \u0430\u043d\u0430\u043b\u0438\u0442\u0438\u0447\u0435\u0441\u043a\u0438\u0445 \u0440\u0435\u0448\u0435\u043d\u0438\u0439 \u0438 \u043e\u0442\u0447\u0451\u0442\u043d\u043e\u0441\u0442\u0438 \u0413\u0440\u0443\u043f\u043f\u044b \u00ab\u041c.\u0412\u0438\u0434\u0435\u043e-\u042d\u043b\u044c\u0434\u043e\u0440\u0430\u0434\u043e\u00bb, \u0440\u0430\u0441\u0441\u043a\u0430\u0437\u0430\u043b \u043e\u0431 \u043e\u043f\u044b\u0442\u0435 \u0438 \u0438\u0442\u043e\u0433\u0430\u0445 \u043f\u043e\u0441\u0442\u0440\u043e\u0435\u043d\u0438\u044f \u0431\u043e\u0435\u0432\u043e\u0433\u043e \u0434\u0430\u0448\u0431\u043e\u0440\u0434\u0430. \u0421\u043a\u0430\u0436\u0443 \u0441\u0440\u0430\u0437\u0443, \u043d\u0435 [&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":[702],"tags":[],"class_list":["post-55144","post","type-post","status-publish","format-standard","hentry","category-news"],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 5.0.4 - aioseo.com -->\n\t<meta name=\"description\" content=\"\u0412\u0440\u0435\u043c\u044f \u043e\u0442\u0447\u0451\u0442\u043d\u043e\u0441\u0442\u0438 \u0432 Excel \u0441\u0442\u0440\u0435\u043c\u0438\u0442\u0435\u043b\u044c\u043d\u043e \u0443\u0445\u043e\u0434\u0438\u0442 \u2014 \u0442\u0440\u0435\u043d\u0434 \u043d\u0430 \u0443\u0434\u043e\u0431\u043d\u044b\u0435 \u0438\u043d\u0441\u0442\u0440\u0443\u043c\u0435\u043d\u0442\u044b \u043f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u043b\u0435\u043d\u0438\u044f \u0438 \u0430\u043d\u0430\u043b\u0438\u0437\u0430 \u0438\u043d\u0444\u043e\u0440\u043c\u0430\u0446\u0438\u0438 \u0432\u0438\u0434\u0435\u043d \u0432\u043e \u0432\u0441\u0435\u0445 \u0441\u0444\u0435\u0440\u0430\u0445.\" \/>\n\t<meta name=\"robots\" content=\"max-image-preview:large\" \/>\n\t<meta name=\"author\" content=\"Yuri Gagarin\"\/>\n\t<link rel=\"canonical\" href=\"https:\/\/prohoster.info\/lv\/blog\/news\/tableau-v-roznitse-realno\" \/>\n\t\t<meta name=\"generator\" content=\"All in One SEO (AIOSEO) 5.0.4\" \/>\n\t\t<meta property=\"og:locale\" content=\"lv_LV\" \/>\n\t\t<meta property=\"og:site_name\" content=\"ProHoster | \u041a\u0443\u043f\u0438\u0442\u044c \u043d\u0430\u0434\u0435\u0436\u043d\u044b\u0439 \u0445\u043e\u0441\u0442\u0438\u043d\u0433 \u0434\u043b\u044f \u0441\u0430\u0439\u0442\u043e\u0432 \u0441 \u0437\u0430\u0449\u0438\u0442\u043e\u0439 \u043e\u0442 DDoS, VPS VDS \u0441\u0435\u0440\u0432\u0435\u0440\u044b\" \/>\n\t\t<meta property=\"og:type\" content=\"article\" \/>\n\t\t<meta property=\"og:title\" content=\"\ud83e\udd47Tableau \u0432 \u0440\u043e\u0437\u043d\u0438\u0446\u0435, \u0440\u0435\u0430\u043b\u044c\u043d\u043e? 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