{"id":31936,"date":"2022-06-24T09:24:00","date_gmt":"2022-06-24T07:24:00","guid":{"rendered":"https:\/\/fotc.com\/bigquery-ce-este-tutorial\/"},"modified":"2026-07-02T11:31:03","modified_gmt":"2026-07-02T09:31:03","slug":"bigquery-ce-este-tutorial","status":"publish","type":"post","link":"https:\/\/fotc.com\/ro\/blog\/bigquery-ce-este-tutorial\/","title":{"rendered":"BigQuery \u2013 ce este \u0219i cum s\u0103 \u00eencepe\u021bi? [Tutorial]"},"content":{"rendered":"\n<p>Datele sunt noul aur \u2013 companiile \u0219i organiza\u021biile orientate spre cre\u0219tere \u00ee\u0219i dau seama de acest lucru. Afacerile con\u0219tiente analizeaz\u0103 procesele existente, implement\u00e2nd modific\u0103ri \u0219i \u00eembun\u0103t\u0103\u021biri pe baza cifrelor. Unele merg mai departe \u2013 utiliz\u00e2nd posibilit\u0103\u021bile oferite de tehnologie, anticip\u00e2nd tendin\u021be, posibilele schimb\u0103ri ale pie\u021bei \u0219i consecin\u021bele deciziilor de afaceri care urmeaz\u0103 s\u0103 fie luate.<\/p>\n\n\n\n<p>Pe m\u0103sur\u0103 ce afacerile cresc, volumele de date cresc &#8211; gigaocte\u021bii se transform\u0103 \u00een teraocte\u021bi sau chiar petaocte\u021bi. Pentru a men\u021bine un nivel adecvat al costurilor de \u00eentre\u021binere a instrumentelor analitice \u0219i timpi scur\u021bi de generare a rapoartelor, este esen\u021bial s\u0103 alege\u021bi tehnologia potrivit\u0103.\u00a0<br><strong>BigQuery<\/strong>\u00a0&#8211; un serviciu dedicat analizei Big Data, care alimenteaz\u0103 numeroase instrumente analitice &#8211; ofer\u0103 asisten\u021b\u0103 nepre\u021buit\u0103. Ast\u0103zi, BigQuery este mai mult dec\u00e2t un simplu depozit de date &#8211; Google \u00eel descrie ca o platform\u0103 de date integrat\u0103 cu inteligen\u021ba artificial\u0103, deschiz\u00e2nd posibilit\u0103\u021bi de analiz\u0103 complet noi, pe care le vom discuta mai jos.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-ce-este-bigquery-depozitul-de-date-de-la-google\">Ce este BigQuery, depozitul de date de la Google?<\/h2>\n\n\n\n<p><strong>BigQuery este un serviciu de depozitare a datelor \u00een cloud, scalabil \u0219i f\u0103r\u0103 server.\u00a0\u00a0Acesta<\/strong>\u00a0v\u0103 permite s\u0103 gestiona\u021bi milioane de interog\u0103ri\u00a0<br><em>\u0219i<\/em>\u00a0s\u0103 efectua\u021bi analize avansate ale unor cantit\u0103\u021bi masive de date &#8211; petabytes &#8211; \u00een SQL, f\u0103r\u0103 a fi nevoie s\u0103 v\u0103 face\u021bi griji cu privire la \u00eentre\u021binerea, scalarea sau echilibrarea \u00eenc\u0103rc\u0103rii costisitoare a infrastructurii.<\/p>\n\n\n\n<p>BigQuery este unul dintre serviciile disponibile pe\u00a0<a href=\"https:\/\/fotc.com\/ro\/blog\/google-cloud-platform-ce-este\/\" target=\"_blank\" rel=\"noreferrer noopener\">Google Cloud Platform (GCP)<\/a>\u00a0. Seturile de date sunt stocate \u0219i procesate \u00een cloud, utiliz\u00e2nd infrastructura stabil\u0103, sigur\u0103 \u0219i scalabil\u0103 Google Cloud. Folosind acest serviciu, v\u0103 pute\u021bi crea propriul instrument analitic &#8211; de exemplu,\u00a0<a href=\"https:\/\/fotc.com\/ro\/blog\/depozit-de-date-definitie-concepte-cheie\/\" target=\"_blank\" rel=\"noreferrer noopener\">un depozit de date &#8211; pentru a urm\u0103ri dezvoltarea, procesele \u0219i schimb\u0103rile din cadrul sau din jurul companiei dvs. Google BigQuery are \u00eenv\u0103\u021bare automat\u0103 (\u00a0<\/a><br><em>ML<\/em>\u00a0) \u00eencorporat\u0103\u00a0\u0219i, a\u0219a cum este descris \u00een sec\u021biunea urm\u0103toare, inteligen\u021b\u0103 artificial\u0103 generativ\u0103, permi\u021b\u00e2ndu-v\u0103 s\u0103 extinde\u021bi sistemul cu capacit\u0103\u021bi predictive sau s\u0103 simula\u021bi diverse scenarii de afaceri.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-tehnologie-fara-server\">Tehnologie f\u0103r\u0103 server<\/h3>\n\n\n\n<p>Google BigQuery este un serviciu f\u0103r\u0103 server, ceea ce \u00eenseamn\u0103 c\u0103 procesele de mentenan\u021b\u0103 sunt automatizate. Ca utilizator, nu trebuie s\u0103 \u00eentre\u021bine\u021bi ma\u0219ini fizice, s\u0103 actualiza\u021bi software, s\u0103 seta\u021bi reguli de scalare, s\u0103 echilibra\u021bi sarcina sau s\u0103 implementa\u021bi politici de securitate complexe. Furnizorul de servicii, Google Cloud, se ocup\u0103 de aceste elemente, permi\u021b\u00e2ndu-v\u0103 s\u0103 v\u0103 concentra\u021bi asupra analizelor f\u0103r\u0103 distrageri suplimentare.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-analiza-rapida-a-straturilor-de-date\">Analiza rapid\u0103 a straturilor de date<\/h3>\n\n\n\n<p>Depozitele de date,\u00a0spre deosebire de bazele de date,\u00a0sunt capabile s\u0103 analizeze cantit\u0103\u021bi vaste de informa\u021bii \u0219i s\u0103 efectueze analize complexe, \u00een timp ce bazele de date func\u021bioneaz\u0103 mai eficient \u00eentr-un model de interogare mic\u0103\/r\u0103spuns rapid. Aceast\u0103 performan\u021b\u0103 ridicat\u0103 provine din stocarea pe coloane\u00a0<em>&#8211;<\/em>\u00a0BigQuery cite\u0219te doar coloanele necesare pentru executarea interog\u0103rii, \u00een loc s\u0103 scaneze r\u00e2nduri \u00eentregi, acceler\u00e2nd semnificativ analiza. Procesarea unui terabyte de date dureaz\u0103 c\u00e2teva secunde \u00een BigQuery, iar procesarea unui petabyte dureaz\u0103 aproximativ 3 minute (timpul real depinde de complexitatea interog\u0103rii, de resursele alocate \u0219i de optimizarea tabelului). Aceasta \u00eenseamn\u0103 c\u0103, av\u00e2nd o multitudine de date actuale \u0219i istorice, efectuarea analizei \u00een BigQuery poate dura\u00a0<strong>p\u00e2n\u0103 la c\u00e2teva minute<\/strong>\u00a0, \u00een timp ce alte sisteme de depozitare ar putea dura c\u00e2teva ore. Scalabilitatea \u00eenseamn\u0103 c\u0103 cantit\u0103\u021bile mari de date nu au un impact semnificativ asupra timpului de a\u0219teptare pentru rezultate &#8211; resursele sunt alocate automat, \u00een func\u021bie de \u00eenc\u0103rcare.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-fara-interferen\u021be-cu-codul-sursa\">F\u0103r\u0103 interferen\u021be cu codul surs\u0103<\/h3>\n\n\n\n<p>Utilizarea BigQuery\u00a0<strong>nu necesit\u0103 modific\u0103ri majore<\/strong>\u00a0sau rescrierea codului surs\u0103. Acest lucru se datoreaz\u0103 faptului c\u0103 BigQuery este compatibil cu standardul ANSI SQL:2011 \u0219i ofer\u0103 interfe\u021be de programare ODBC \u0219i JDBC gratuite.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-securitatea-datelor-in-google-bigquery\">Securitatea datelor \u00een Google BigQuery<\/h3>\n\n\n\n<p>Datele sunt criptate \u00een repaus (\u00a0<em>criptare \u00een repaus<\/em>\u00a0) \u0219i \u00een tranzit (\u00a0<em>criptare \u00een tranzit<\/em>\u00a0), iar accesul poate fi controlat cu precizie la nivel de proiect \u0219i set de date &#8211; de exemplu, prin roluri IAM. \u00cen plus, datele sunt stocate redundant pe discuri replicate (\u00een oglind\u0103), protej\u00e2nd \u00eempotriva pierderii de date \u00een cazul unei defec\u021biuni hardware. Acest model asigur\u0103 un nivel ridicat de securitate a datelor, \u00een concordan\u021b\u0103 cu cerin\u021bele pentru solu\u021biile de clas\u0103 enterprise.<br><\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-copiere-de-rezerva-automata\">Copiere de rezerv\u0103 automat\u0103<\/h3>\n\n\n\n<p>Instrumentul efectueaz\u0103 copii de rezerv\u0103 automate \u0219i stocheaz\u0103\u00a0<strong>implicit un istoric al modific\u0103rilor timp de 7 zile<\/strong>\u00a0( func\u021bie\u00a0<em>de c\u0103l\u0103torie \u00een timp<\/em>\u00a0, configurabil\u0103 de la 2 la 7 zile). Acest lucru v\u0103 permite s\u0103 compara\u021bi cu u\u0219urin\u021b\u0103 rezultatele cu o perioad\u0103 anterioar\u0103 sau s\u0103 restaura\u021bi datele.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-analiza-datelor-din-diverse-surse\">Analiza datelor din diverse surse<\/h3>\n\n\n\n<p>BigQuery poate fi utilizat pentru a analiza date din diverse surse &#8211; Google Marketing Platform, Google Analytics, YouTube, platforme de publicitate \u0219i media (de exemplu, Facebook Ads) \u0219i sute de aplica\u021bii SaaS externe. Datele pot fi importate manual sau se poate construi o re\u021bea de procesare care preia, unific\u0103 \u0219i trimite automat date c\u0103tre serviciu. Integrarea cu fluxul de date \u00een timp real face ca noile \u00eenregistr\u0103ri &#8211; de exemplu, de la senzori \u0219i dispozitive IoT &#8211; s\u0103 fie disponibile pentru analiz\u0103 \u00een timp real.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-analiza-multi-cloud-cu-bigquery-omni\">Analiz\u0103 multi-cloud cu BigQuery Omni<\/h3>\n\n\n\n<p>BigQuery Omni v\u0103 permite s\u0103 analiza\u021bi date din alte cloud-uri publice (AWS, Azure) f\u0103r\u0103 a p\u0103r\u0103si interfa\u021ba serviciului, inclusiv interog\u0103ri \u0219i\u00a0<em>jonc\u021biuni cross-cloud<\/em>\u00a0\u00eentre date stocate \u00een cloud-uri diferite. Pute\u021bi citi mai multe despre acest serviciu \u00een articolul:\u00a0<a href=\"https:\/\/fotc.com\/pl\/blog\/bigquery-omni-hurtownia-danych-multi-cloud\/\" target=\"_blank\" rel=\"noreferrer noopener\">BigQuery Omni \u2013 un depozit de date multi-cloud<\/a>.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-bigquery-ml-modele-de-inva\u021bare-automata-incorporate\">BigQuery ML \u2013 modele de \u00eenv\u0103\u021bare automat\u0103 \u00eencorporate<\/h3>\n\n\n\n<p>Una dintre func\u021biile disponibile este\u00a0<strong>BigQuery ML<\/strong>\u00a0, dedicat construirii \u0219i dezvolt\u0103rii capabilit\u0103\u021bilor de \u00eenv\u0103\u021bare automat\u0103 folosind interog\u0103ri SQL standard. BigQuery ML accelereaz\u0103 dezvoltarea produselor de \u00eenv\u0103\u021bare automat\u0103, reduc\u00e2nd \u00een acela\u0219i timp cerin\u021bele pentru scrierea codului surs\u0103 \u0219i mutarea datelor. Serviciul poate fi, de asemenea, integrat cu platforma Vertex AI, modele generative (inclusiv Gemini) \u0219i TensorFlow pentru a construi \u0219i antrena propriile modele de \u00eenv\u0103\u021bare automat\u0103 &#8211; mai multe despre acest subiect \u00een sec\u021biunea despre BigQuery Studio \u0219i Gemini.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-suport-pentru-business-intelligence-bi-in-timp-real\">Suport pentru Business Intelligence (BI) \u00een timp real<\/h3>\n\n\n\n<p><strong>BigQuery BI Engine<\/strong>\u00a0este o func\u021bie \u00eencorporat\u0103 de analiz\u0103 \u00een memorie care permite analiza \u00een timp aproape real a seturilor sau segmentelor mari de date. BI Engine este integrat cu instrumentul de vizualizare a datelor Looker Studio (fostul Google Data Studio), ceea ce face din BigQuery un instrument excelent de business intelligence care sprijin\u0103 luarea deciziilor de afaceri. Serviciul accept\u0103, de asemenea, raportarea\u00a0<em>ad-hoc<\/em>\u00a0, adic\u0103 rapoarte care acoper\u0103 un segment de date specific \u0219i nu necesit\u0103 implicarea departamentului de analiz\u0103 sau IT pentru preg\u0103tirea rezumatului. Dac\u0103 lucra\u021bi cu rapoarte \u00een Looker Studio (fostul Google Data Studio), acest depozit de date este una dintre sursele de date native ale instrumentului. BigQuery se integreaz\u0103, de asemenea, cu alte instrumente BI populare, cum ar fi Tableau \u0219i Power BI, prin conectori dedica\u021bi \u0219i drivere ODBC\/JDBC.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-bigquery-studio-\u0219i-gemini-bigquery-ca-platforma-de-date-bazata-pe-inteligen\u021ba-artificiala\">BigQuery Studio \u0219i Gemini \u2013 BigQuery ca platform\u0103 de date bazat\u0103 pe inteligen\u021b\u0103 artificial\u0103<\/h2>\n\n\n\n<p>Google BigQuery este acum mai mult dec\u00e2t un simplu depozit de date clasic \u2013 Google \u00eel descrie ca\u00a0<em>o platform\u0103 de date bazat\u0103 pe inteligen\u021b\u0103 artificial\u0103<\/em>\u00a0, adic\u0103 o platform\u0103 de date integrat\u0103 cu modele de inteligen\u021b\u0103 artificial\u0103 \u00een fiecare etap\u0103 de lucru: de la explorarea datelor, prin scrierea interog\u0103rilor, p\u00e2n\u0103 la analiz\u0103 \u0219i predic\u021bie.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-bigquery-studio-un-singur-loc-pentru-a-lucra-cu-datele-tale\">BigQuery Studio \u2013 un singur loc pentru a lucra cu datele tale<\/h3>\n\n\n\n<p><strong>BigQuery Studio<\/strong>\u00a0este un spa\u021biu de lucru unificat care combin\u0103 editorul SQL, blocnotesurile (powered by Colab Enterprise), asistentul Gemini \u0219i instrumentele de explorare \u0219i preg\u0103tire a datelor \u00eentr-o singur\u0103 interfa\u021b\u0103. \u00cen loc s\u0103 comute \u00eentre mai multe servicii, anali\u0219tii pot scrie interog\u0103ri SQL, cod Python \u0219i pot utiliza asistentul AI \u00eentr-o singur\u0103 fereastr\u0103 a consolei Google Cloud.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-gemini-pe-bigquery-sql-in-limbaj-natural-\u0219i-informa\u021bii-automate\">Gemini pe BigQuery \u2013 SQL \u00een limbaj natural \u0219i informa\u021bii automate<\/h3>\n\n\n\n<p><strong>Gemini \u00een BigQuery<\/strong>&nbsp;este un asistent de inteligen\u021b\u0103 artificial\u0103 \u00eencorporat care ofer\u0103 asisten\u021b\u0103 utilizatorilor pe mai multe niveluri:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>generarea de interog\u0103ri SQL dintr-o descriere \u00een limbaj natural<\/strong>\u00a0\u2013 descrie\u021bi pur \u0219i simplu datele de care ave\u021bi nevoie, iar Gemini v\u0103 va propune o interogare gata f\u0103cut\u0103;<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>clarificarea \u0219i optimizarea interog\u0103rilor<\/strong>\u00a0\u2013 asistentul \u00een\u021belege contextul filei deschise cu interogarea \u0219i poate sugera simplificarea sau optimizarea acesteia f\u0103r\u0103 a copia codul \u00een chat;<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>informa\u021bii automate (informa\u021bii despre date)<\/strong>\u00a0\u2013 Gemini analizeaz\u0103 metadatele tabelului \u00een timp real \u0219i sugereaz\u0103 independent \u00eentreb\u0103ri \u0219i modele care merit\u0103 verificate, ceea ce faciliteaz\u0103 primii pa\u0219i cu un nou set de date;<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>data canvas<\/strong>\u00a0\u2013 explorare vizual\u0103 a datelor folosind comenzi \u00een limbaj natural, f\u0103r\u0103 a scrie cod;<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>C\u0103utare resurse<\/strong>\u00a0\u2013 asistentul caut\u0103 seturi de date, tabele, modele \u0219i interog\u0103ri salvate \u00een mai multe proiecte simultan.<\/li>\n<\/ul>\n\n\n\n<p>Pentru echipele care abia \u00eencep s\u0103 utilizeze BigQuery, Gemini scurteaz\u0103 cu adev\u0103rat curba de \u00eenv\u0103\u021bare: nu este nevoie s\u0103 cunoa\u0219te\u021bi sintaxa SQL din prima zi pentru a \u00eencepe s\u0103 extrage\u021bi informa\u021bii din datele dvs.<\/p>\n\n\n\n<figure class=\"wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio\"><div class=\"wp-block-embed__wrapper\">\n<iframe title=\"Intro to Google Gemini AI and Data Analytics In BigQuery\" width=\"500\" height=\"281\" src=\"https:\/\/www.youtube.com\/embed\/-MWIHAH4cbA?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen><\/iframe>\n<\/div><\/figure>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-ia-func\u021bioneaza-direct-in-interogarile-sql\">IA func\u021bioneaz\u0103 direct \u00een interog\u0103rile SQL<\/h3>\n\n\n\n<p>BigQuery v\u0103 permite, de asemenea, s\u0103 invoca\u021bi modele generative (inclusiv Gemini \u0219i alte modele disponibile prin Vertex AI) direct din interog\u0103ri SQL, f\u0103r\u0103 a p\u0103r\u0103si mediul BigQuery. Caracteristici cheie:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>AI.GENERATE<\/strong>\u00a0\u2013 generare de text pe baza datelor din tabel (de exemplu, rezumate automate, clasificare, descrieri);<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>AI.EMBED \/ AI.GENERATE_EMBEDDING<\/strong>\u00a0\u2013 crearea de embedding-uri (reprezent\u0103ri vectoriale) din date text, dar \u0219i imagini, fi\u0219iere audio, video \u0219i PDF, ceea ce permite c\u0103utarea semantic\u0103 \u0219i compararea similarit\u0103\u021bii con\u021binutului;<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>AI.SIMILARITY<\/strong>\u00a0\u2013 compararea similarit\u0103\u021bii datelor pe baza \u00eencorpor\u0103rilor generate.<\/li>\n<\/ul>\n\n\n\n<p>Aceasta extinde capacit\u0103\u021bile\u00a0<strong>BigQuery ML<\/strong>\u00a0descrise anterior \u2013 pe l\u00e2ng\u0103 modelele clasice (regresie, clustering, serii temporale), BigQuery ML v\u0103 permite \u0219i s\u0103 crea\u021bi modele la distan\u021b\u0103\u00a0<br><em>care<\/em>\u00a0utilizeaz\u0103 modelele generative disponibile \u00een Vertex AI.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-agen\u021bi-ai-agent-de-analiza-conversa\u021bionala-\u0219i-inginerie-de-date\">Agen\u021bi AI: Agent de analiz\u0103 conversa\u021bional\u0103 \u0219i inginerie de date<\/h3>\n\n\n\n<p>BigQuery dezvolt\u0103, de asemenea, un strat de agent, accesibil prin BigQuery Studio.\u00a0<strong>Analiza conversa\u021bional\u0103<\/strong>\u00a0permite o \u201econversa\u021bie\u201d cu datele \u00een mai multe etape \u2013 agentul genereaz\u0103, execut\u0103 \u0219i vizualizeaz\u0103 interog\u0103ri SQL pe baza \u00eentreb\u0103rilor \u00een limbaj natural \u00een timp real, \u00een contextul de afaceri al companiei. Rezultatele (tabele, diagrame \u0219i explica\u021bii) sunt complet verificabile, deoarece codul SQL utilizat este vizibil. Agentul de\u00a0<strong>inginerie a datelor,<\/strong>\u00a0la r\u00e2ndul s\u0103u , sus\u021bine construirea \u0219i \u00eentre\u021binerea conductelor de date \u2013 pe baza descrierilor \u00een limbaj natural, genereaz\u0103 cod \u00een concordan\u021b\u0103 cu cele mai bune practici de inginerie a datelor \u0219i ajut\u0103 la modificarea conductelor existente. Disponibilitatea func\u021biilor individuale variaz\u0103 \u00een func\u021bie de regiune \u0219i de etapa de implementare \u2013 merit\u0103 s\u0103 verifica\u021bi documenta\u021bia BigQuery pentru starea actual\u0103.<\/p>\n\n\n\n<p>Pentru companii, acesta este un alt pas c\u0103tre analiza \u00een regim self-service \u2013 persoanele f\u0103r\u0103 cuno\u0219tin\u021be tehnice pot pune \u00eentreb\u0103ri despre date, iar echipele de date c\u00e2\u0219tig\u0103 timp pentru sarcini care necesit\u0103 mai mult control \u0219i supraveghere.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-costul-bigquery-cat-costa-un-serviciu-de-analiza-a-datelor-in-cloud\">Costul BigQuery \u2013 C\u00e2t cost\u0103 un serviciu de analiz\u0103 a datelor \u00een cloud?<\/h2>\n\n\n\n<p>Modelul standard de plat\u0103 pentru serviciile cloud este\u00a0<em>plata pe m\u0103sur\u0103 ce utilizezi<\/em>\u00a0(pay-as-you-go) &#8211; pl\u0103te\u0219ti doar pentru ceea ce utilizezi efectiv, f\u0103r\u0103 taxe \u00een avans. Pre\u021burile Google BigQuery constau din dou\u0103 componente principale:\u00a0<strong>costul interog\u0103rilor (calcul)<\/strong>\u00a0\u0219i\u00a0<strong>costul stoc\u0103rii datelor<\/strong>\u00a0.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-costul-interogarii-edi\u021biile-la-cerere-vs-bigquery\">Costul interog\u0103rii \u2013 Edi\u021biile la cerere vs. BigQuery<\/h3>\n\n\n\n<p>Pentru costurile interog\u0103rilor, ave\u021bi de ales \u00eentre dou\u0103 modele de facturare:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>La cerere (per TB)<\/strong>\u00a0\u2013 pl\u0103ti\u021bi pentru cantitatea de date procesate, adic\u0103 num\u0103rul de octe\u021bi, la un tarif de aproximativ 5 USD per TB de date procesate (ca ghid \u2013 tariful exact, actual, \u00een TB poate fi g\u0103sit \u00een lista de pre\u021buri Google Cloud). Primii TB de date pe lun\u0103 sunt gratuit, iar TB-urile ulterioare sunt facturate la tariful actual pentru TB. Aceast\u0103 solu\u021bie este destinat\u0103 companiilor care efectueaz\u0103 analize \u00een mod neregulat sau au sarcini de lucru imprevizibile.<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Edi\u021biile BigQuery (pre\u021buri bazate pe capacitate)<\/strong>\u00a0\u2013 achizi\u021biona\u021bi putere de calcul \u00een sloturi (procesoare virtuale) \u00eentr-una dintre cele trei edi\u021bii:\u00a0<strong>Standard<\/strong>\u00a0(sarcini de lucru mai mici, intermitente),\u00a0<strong>Enterprise<\/strong>\u00a0(performan\u021b\u0103 previzibil\u0103 \u0219i gestionarea sarcinii de lucru) \u0219i\u00a0<strong>Enterprise Plus<\/strong>\u00a0(cele mai \u00eenalte cerin\u021be de securitate a datelor \u0219i conformitate). Sloturile pot fi scalate automat sau rezervate pentru unul sau trei ani cu un angajament, asigur\u00e2nd scalabilitate complet\u0103 indiferent de sarcina de lucru \u0219i oferind un pre\u021b mai mic.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-stocarea-datelor\">Stocarea datelor<\/h3>\n\n\n\n<p>Stocarea datelor \u00een BigQuery este facturat\u0103 \u00een dou\u0103 moduri, iar taxa depinde de cantitatea de date stocate \u0219i de timpul scurs de la ultima modificare:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>stocare activ\u0103<\/strong>\u00a0\u2013 pentru tabele \u0219i parti\u021bii modificate \u00een ultimele 90 de zile;<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>stocare pe termen lung<\/strong>\u00a0\u2013 pentru tabele \u0219i parti\u021bii care r\u0103m\u00e2n neschimbate timp de 90 de zile; pre\u021bul scade automat cu aproximativ 50%, f\u0103r\u0103 a afecta performan\u021ba sau disponibilitatea datelor.<\/li>\n<\/ul>\n\n\n\n<p>\u00cen plus, BigQuery v\u0103 permite s\u0103 alege\u021bi \u00eentre facturarea\u00a0<strong>logic\u0103<\/strong>\u00a0(bazat\u0103 pe dimensiunea datelor necomprimate) \u0219i\u00a0<strong>facturarea fizic\u0103<\/strong>\u00a0(bazat\u0103 pe spa\u021biul real, comprimat, pe disc). Ultimul model este adesea mai avantajos pentru seturile de date bine comprimate. Ca ghid, stocarea pe termen lung cost\u0103 \u00een jur de 1 cent pe GB pe lun\u0103 (tarifele variaz\u0103 \u00een func\u021bie de regiune \u0219i de modelul de facturare ales &#8211; consulta\u021bi documenta\u021bia Google Cloud pentru pre\u021burile actuale). Primii 10 GB pe lun\u0103 sunt gratuit cu oricare dintre modele.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-costuri-suplimentare-\u0219i-estimare\">Costuri suplimentare \u0219i estimare<\/h3>\n\n\n\n<p>Costurile suplimentare pot include BI Engine, antrenarea modelelor BigQuery ML, exportarea datelor \u00een afara serviciului sau transferul de date \u00eentre loca\u021bii. Utilizarea parti\u021bion\u0103rii \u00een tabele \u0219i a grup\u0103rii \u00een clustere este o practic\u0103 recomandat\u0103 pentru reducerea costurilor interog\u0103rilor. Deoarece tarifele Google Cloud se modific\u0103 \u00een timp, pute\u021bi ob\u021bine cea mai precis\u0103 \u0219i actualizat\u0103 estimare utiliz\u00e2nd\u00a0<a href=\"https:\/\/cloud.google.com\/products\/calculator\" target=\"_blank\" rel=\"noreferrer noopener\">calculatorul de costuri Google Cloud<\/a>\u00a0sau\u00a0<a href=\"https:\/\/cloud.google.com\/bigquery\/pricing\" target=\"_blank\" rel=\"noreferrer noopener\">documenta\u021bia de pre\u021buri BigQuery<\/a>\u00a0.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-incearca-bigquery-gratuit-bigquery-sandbox\">\u00cencearc\u0103 BigQuery gratuit \u2013 BigQuery sandbox<\/h2>\n\n\n\n<p>Cea mai bun\u0103 modalitate de a experimenta cu adev\u0103rat poten\u021bialul Google BigQuery este prin practic\u0103. Cel mai bun punct de plecare este\u00a0<strong>BigQuery sandbox<\/strong>\u00a0\u2013 un mod gratuit care nu necesit\u0103 furnizarea detaliilor cardului de credit sau configurarea unui cont de facturare Google Cloud.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-ce-este-sandbox-ul-bigquery\">Ce este sandbox-ul BigQuery?<\/h3>\n\n\n\n<p>Sandbox-ul BigQuery este un mod special de acces la serviciu, disponibil oric\u0103rui utilizator cu un cont Google. Acesta func\u021bioneaz\u0103 \u00een cadrul nivelului gratuit Google Cloud \u0219i v\u0103 permite s\u0103 explora\u021bi interfa\u021ba, s\u0103 rula\u021bi interog\u0103ri SQL pe seturi de date publice \u0219i s\u0103 \u00eenc\u0103rca\u021bi \u0219i s\u0103 analiza\u021bi propriile date &#8211; gratuit \u0219i f\u0103r\u0103 riscul unor facturi nea\u0219teptate. Noii utilizatori Google Cloud pot beneficia, de asemenea, de un credit promo\u021bional suplimentar de 300 USD pe parcursul unei perioade de prob\u0103 limitate &#8211; merit\u0103 s\u0103 verifica\u021bi termenii actuali \u00eenainte de a v\u0103 \u00eenscrie.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" width=\"1024\" height=\"854\" src=\"https:\/\/fotc.com\/app\/uploads\/2023\/03\/bigquery-sandbox-1024x854.png\" alt=\"\" class=\"wp-image-172603\" srcset=\"https:\/\/fotc.com\/app\/uploads\/2023\/03\/bigquery-sandbox-1024x854.png 1024w, https:\/\/fotc.com\/app\/uploads\/2023\/03\/bigquery-sandbox-300x250.png 300w, https:\/\/fotc.com\/app\/uploads\/2023\/03\/bigquery-sandbox-768x641.png 768w, https:\/\/fotc.com\/app\/uploads\/2023\/03\/bigquery-sandbox-123x103.png 123w, https:\/\/fotc.com\/app\/uploads\/2023\/03\/bigquery-sandbox-142x118.png 142w, https:\/\/fotc.com\/app\/uploads\/2023\/03\/bigquery-sandbox-210x175.png 210w, https:\/\/fotc.com\/app\/uploads\/2023\/03\/bigquery-sandbox-338x282.png 338w, https:\/\/fotc.com\/app\/uploads\/2023\/03\/bigquery-sandbox-219x183.png 219w, https:\/\/fotc.com\/app\/uploads\/2023\/03\/bigquery-sandbox-26x22.png 26w, https:\/\/fotc.com\/app\/uploads\/2023\/03\/bigquery-sandbox.png 1392w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-limitele-bigquery-sandbox\">Limitele BigQuery sandbox<\/h3>\n\n\n\n<p>Sandbox func\u021bioneaz\u0103 \u00een urm\u0103toarele limite:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>1 TB de interog\u0103ri pe lun\u0103<\/strong>\u00a0\u2013 suficient pentru \u00eenv\u0103\u021bare \u0219i testare;<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>10 GB de stocare a datelor<\/strong>\u00a0\u2013 pentru propriile tabele \u0219i colec\u021bii;<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>f\u0103r\u0103 streaming de date<\/strong>\u00a0\u2013 datele pot fi importate doar \u00een lot, nu \u00een timp real;<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>f\u0103r\u0103 opera\u021biuni DML<\/strong>\u00a0(INSERT, UPDATE, DELETE) \u2013 tabelele pot fi create \u0219i interogate, dar nu modificate r\u00e2nd cu r\u00e2nd;<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>expirarea tabelului<\/strong>\u00a0\u2013 tabelele neutilizate timp de 60 de zile sunt \u0219terse automat.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-cum-se-ruleaza-bigquery-sandbox\">Cum se ruleaz\u0103 BigQuery sandbox?<\/h3>\n\n\n\n<ol class=\"wp-block-list\">\n<li>Accesa\u021bi console.cloud.google.com \u0219i conecta\u021bi-v\u0103 cu contul dvs. Google.<\/li>\n\n\n\n<li>Crea\u021bi un proiect nou \u2013 f\u0103r\u0103 a introduce detaliile cardului de plat\u0103 sau a configura un cont de facturare.<\/li>\n\n\n\n<li><strong>Selecta\u021bi BigQuery<\/strong>\u00a0din meniul din st\u00e2nga\u00a0\u2013 sandbox-ul se va activa automat.<\/li>\n\n\n\n<li>\u00cen BigQuery Studio, pute\u021bi interoga imediat seturi de date publice sau pute\u021bi \u00eenc\u0103rca propriile date \u0219i \u00eencepe analiza.<\/li>\n\n\n\n<li>Dac\u0103 nu ave\u021bi \u00eenc\u0103 propriile date, conecta\u021bi unul dintre seturile de date publice BigQuery: \u00een panoul din st\u00e2nga, face\u021bi clic pe\u00a0<strong>+ Ad\u0103uga\u021bi date<\/strong>\u00a0\u2192\u00a0<strong>Seturi de date publice<\/strong>\u00a0\u0219i selecta\u021bi setul de date care v\u0103 intereseaz\u0103 (de exemplu, date demografice, financiare sau de transport). Acesta va fi disponibil pentru interogare imediat, f\u0103r\u0103 nicio configurare.<\/li>\n<\/ol>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-cand-nu-mai-este-suficient-sandboxing-ul\">C\u00e2nd nu mai este suficient sandboxing-ul?<\/h3>\n\n\n\n<p>Sandboxing-ul este un \u00eenceput excelent, dar are limitele sale. Atunci c\u00e2nd compania ta are nevoie de streaming de date din sistemele de produc\u021bie, opera\u021biuni DML, volume de stocare mai mari sau integrare cu alte servicii Google Cloud Platform, este timpul s\u0103 faci upgrade la un cont complet \u0219i s\u0103 planifici implementarea. Aici este locul \u00een care asisten\u021ba din partea unui partener certificat Google Cloud accelereaz\u0103 cu adev\u0103rat \u0219i reduce costurile \u00eentregului proces.<\/p>\n\n\n\n<p>Dac\u0103 vrei s\u0103 afli ce poate face BigQuery pentru afacerea ta \u0219i cum s\u0103 \u00eel implementezi f\u0103r\u0103 \u00eencerc\u0103ri \u0219i erori inutile,\u00a0<a href=\"https:\/\/fotc.com\/ro\/contact\/\" target=\"_blank\" rel=\"noreferrer noopener\">contacteaz\u0103 FOTC<\/a>\u00a0\u2013 un partener certificat Google Cloud Premier.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-tutoriale-bigquery-cum-sa-incepi-in-practica\">Tutoriale BigQuery \u2013 Cum s\u0103 \u00eencepi \u00een practic\u0103?<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-no\u021biuni-introductive-despre-bigquery-studio-cu-gemini-pentru-incepatori\">No\u021biuni introductive despre BigQuery Studio cu Gemini \u2013 pentru \u00eencep\u0103tori<\/h3>\n\n\n\n<p>Pentru a \u00eencepe s\u0103 utiliza\u021bi BigQuery, ve\u021bi avea nevoie\u00a0<strong>de un cont Google Cloud<\/strong>\u00a0(iat\u0103 un ghid despre\u00a0<a href=\"https:\/\/fotc.com\/ro\/blog\/configurarea-google-cloud-platform\/\">cum s\u0103 crea\u021bi \u0219i s\u0103 configura\u021bi un cont Google Cloud<\/a>\u00a0). Apoi, accesa\u021bi consola Google Cloud Platform (BigQuery Console) \u0219i selecta\u021bi proiectul la care ve\u021bi lucra.<\/p>\n\n\n\n<p>Dac\u0103 nu te sim\u021bi \u00eenc\u0103 familiarizat cu SQL, cel mai bun punct de plecare este\u00a0<strong>BigQuery Studio,<\/strong>\u00a0cu asistentul s\u0103u Gemini \u00eencorporat. \u00cen loc s\u0103 scrii cod manual, po\u021bi descrie interogarea \u00een limbaj natural &#8211; Gemini va genera cod SQL pentru tine, pe care \u00eel po\u021bi verifica, edita \u0219i rula. Acesta este un bun punct de plecare pentru cei care doresc mai \u00eent\u00e2i s\u0103 \u00een\u021beleag\u0103 \u00eentreb\u0103rile pe care le pot adresa datelor lor \u0219i s\u0103-\u0219i perfec\u021bioneze sintaxa SQL prin practic\u0103.<\/p>\n\n\n\n<p>De exemplu, \u00een caseta de chat BigQuery Studio, pute\u021bi tasta\u00a0<em>\u201eArat\u0103-mi veniturile pe canal pentru ultimul trimestru<\/em>\u00a0\u201d. Gemini va preg\u0103ti interogarea SQL corespunz\u0103toare pe baza structurii tabelelor dvs., va returna rezultatul &#8211; de exemplu, sub form\u0103 de tabel sau diagram\u0103 &#8211; \u0219i va afi\u0219a codul SQL utilizat, pe care \u00eel pute\u021bi revizui, salva sau modifica ulterior.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-seturi-de-date-publice-bigquery\">Seturi de date publice BigQuery<\/h3>\n\n\n\n<p>\u00cenainte de a \u00eencepe s\u0103 lucra\u021bi cu propriile date, merit\u0103 s\u0103 exersa\u021bi interog\u0103rile SQL pe\u00a0<strong>seturi de date publice BigQuery<\/strong>\u00a0\u2014 baze de date gratuite, preg\u0103tite pentru interog\u0103ri, furnizate de Google \u0219i partenerii s\u0103i. Acestea includ date demografice, geografice, financiare \u0219i despre transportul public, printre altele. Pur \u0219i simplu deschide\u021bi BigQuery Studio, c\u0103uta\u021bi setul de date care v\u0103 intereseaz\u0103 \u0219i \u00eencepe\u021bi interogarea \u2014 fie cu propriul cod SQL, fie cu Gemini.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-pentru-utilizatori-avansa\u021bi-lucrul-cu-bq-in-cloud-shell\">Pentru utilizatori avansa\u021bi \u2013 lucrul cu bq \u00een Cloud Shell<\/h3>\n\n\n\n<p>Dac\u0103 prefera\u021bi s\u0103 lucra\u021bi cu linia de comand\u0103 sau dori\u021bi s\u0103 automatiza\u021bi interog\u0103rile \u00een scripturi, pute\u021bi utiliza instrumentul bq din\u00a0<strong>Cloud Shell<\/strong>\u00a0, terminalul \u00eencorporat \u00een Google Cloud Console. Mai jos sunt exemple care utilizeaz\u0103 setul de date public Shakespeare.<\/p>\n\n\n\n<p>Dup\u0103 ce selecta\u021bi proiectul, lansa\u021bi\u00a0<strong>Cloud Shell<\/strong>\u00a0\u00een col\u021bul din dreapta sus al consolei. Pentru a verifica schema tabelului, num\u0103rul de r\u00e2nduri \u0219i ponderea \u00een octe\u021bi, utiliza\u021bi comanda:<\/p>\n\n\n\n<p>Pentru a valida interogarea \u00eenainte de execu\u021bie, ad\u0103uga\u021bi indicatorul\u00a0<strong>\u2013dry_run<\/strong>\u00a0:<\/p>\n\n\n\n<p>bq query &#8211;use_legacy_sql=false &#8211;dry_run \\<br>&#8216;SELECT<br>word<br>FROM<br><code>bigquery-public-data<\/code>.samples.shakespeare<br>LIMIT 5&#8242;<\/p>\n\n\n\n<p>Dac\u0103 interogarea este valid\u0103, elimina\u021bi indicatorul\u00a0<strong>\u2013dry_run<\/strong>\u00a0pentru a vedea rezultatul:<\/p>\n\n\n\n<p>bq query &#8211;use_legacy_sql=false \\<br>&#8216;SELECT<br>word<br>FROM<br><code>bigquery-public-data<\/code>.samples.shakespeare<br>LIMIT 5&#8242;<\/p>\n\n\n\n<p>Clauza&nbsp;<strong>WHERE<\/strong>&nbsp;v\u0103 permite s\u0103 filtra\u021bi rezultatele dup\u0103 o anumit\u0103 valoare. Urm\u0103toarea interogare returneaz\u0103 r\u00e2nduri \u00een care coloana&nbsp;<strong>\u201ecuv\u00e2nt\u201d<\/strong>&nbsp;con\u021bine cuv\u00e2ntul \u201e&nbsp;<em>raising\u201d<\/em>&nbsp;:<\/p>\n\n\n\n<p>bq query &#8211;use_legacy_sql=false \\<br>&#8216;SELECT<br>word<br>FROM<br><code>bigquery-public-data<\/code>.samples.shakespeare<br>WHERE<br>word = &#8220;raising&#8221;<br>LIMIT 5&#8242;<\/p>\n\n\n\n<p>Semnul&nbsp;<strong>%<\/strong>&nbsp;din fa\u021ba sintagmei de c\u0103utare include prefixul (de exemplu,&nbsp;<strong>disp<\/strong>&nbsp;raisin), iar pe ambele p\u0103r\u021bi \u2013 prefixul \u0219i sufixul (de exemplu,&nbsp;<strong>disp<\/strong>&nbsp;raisin&nbsp;<strong>gly<\/strong>&nbsp;). C\u00e2nd trebuie s\u0103 grupa\u021bi rezultatele, utiliza\u021bi&nbsp;<strong>GROUP BY<\/strong>&nbsp;:<\/p>\n\n\n\n<p>bq query &#8211;use_legacy_sql=false \\<br>&#8216;SELECT<br>word,<br>COUNT(word_count) AS count<br>FROM<br><code>bigquery-public-data<\/code>.samples.shakespeare<br>WHERE<br>word LIKE &#8220;%raising%&#8221;<br>GROUP BY<br>word&#8217;<\/p>\n\n\n\n<figure class=\"wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio\"><div class=\"wp-block-embed__wrapper\">\n<iframe title=\"Visualize BigQuery data with Looker\" width=\"500\" height=\"281\" src=\"https:\/\/www.youtube.com\/embed\/Q2JD3_YBaRc?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen><\/iframe>\n<\/div><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-intrebari-frecvente-despre-bigquery\">\u00centreb\u0103ri frecvente despre BigQuery<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-ce-este-google-bigquery\">Ce este Google BigQuery?<\/h3>\n\n\n\n<p>Google BigQuery este un depozit de date \u00een cloud scalabil \u0219i f\u0103r\u0103 server de la Google Cloud, care permite analiza seturilor mari de date folosind SQL \u0219i \u2013 datorit\u0103 Gemini \u2013 limbaj natural.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-prin-ce-se-diferen\u021biaza-bigquery-de-o-baza-de-date-tradi\u021bionala\">Prin ce se diferen\u021biaz\u0103 BigQuery de o baz\u0103 de date tradi\u021bional\u0103?<\/h3>\n\n\n\n<p>Bazele de date sunt optimizate pentru interog\u0103ri scurte \u0219i r\u0103spunsuri rapide la \u00eenregistr\u0103ri individuale. Google BigQuery, ca depozit de date, este conceput pentru analizarea unor cantit\u0103\u021bi foarte mari de date &#8211; poate scana terabytes de date \u00een c\u00e2teva secunde \u0219i un petabyte \u00een aproximativ c\u00e2teva minute.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-cat-costa-google-bigquery\">C\u00e2t cost\u0103 Google BigQuery?<\/h3>\n\n\n\n<p>Deci, c\u00e2t cost\u0103 de fapt Google BigQuery? Depinde de cantitatea de date procesate \u0219i stocate \u0219i de modelul de facturare ales. Costul const\u0103 \u00een taxe de interogare (la cerere per TiB sau edi\u021bii BigQuery cu sloturi) \u0219i taxe de stocare a datelor (stocare activ\u0103 \u0219i pe termen lung). Primii TiB de interog\u0103ri \u0219i 10 GiB de stocare pe lun\u0103 sunt gratuite. Pentru o estimare exact\u0103 pentru cazul dvs. specific, cel mai bine este s\u0103 consulta\u021bi calculatorul de costuri Google Cloud.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-are-bigquery-o-versiune-gratuita\">Are BigQuery o versiune gratuit\u0103?<\/h3>\n\n\n\n<p>Da \u2013&nbsp;<strong>BigQuery sandbox<\/strong>&nbsp;v\u0103 permite s\u0103 \u00eencerca\u021bi serviciul f\u0103r\u0103 a furniza detaliile cardului de plat\u0103, \u00een limitele nivelului gratuit Google Cloud (inclusiv 1 TiB de interog\u0103ri \u0219i 10 GiB de stocare pe lun\u0103).<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-trebuie-sa-\u0219tii-sql-pentru-a-lucra-cu-bigquery\">Trebuie s\u0103 \u0219tii SQL pentru a lucra cu BigQuery?<\/h3>\n\n\n\n<p>De\u0219i cuno\u0219tin\u021bele de SQL sunt foarte utile, acestea nu mai sunt o condi\u021bie prealabil\u0103 \u2013 Gemini \u00een BigQuery Studio v\u0103 permite s\u0103 genera\u021bi, s\u0103 explica\u021bi \u0219i s\u0103 optimiza\u021bi interog\u0103ri pe baza descrierilor \u00een limbaj natural.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-bigquery-folose\u0219te-inteligen\u021ba-artificiala-\u0219i-gemini\">BigQuery folose\u0219te inteligen\u021ba artificial\u0103 \u0219i Gemini?<\/h3>\n\n\n\n<p>Da. BigQuery Studio integreaz\u0103 asistentul Gemini (generare SQL, informa\u021bii despre date, data canvas, agen\u021bi pentru comunicarea cu datele \u0219i construirea de conducte), iar \u00een cadrul interog\u0103rilor SQL, pute\u021bi apela func\u021bii AI precum AI.GENERATE sau AI.EMBED, care utilizeaz\u0103 modele Gemini \u0219i alte modele disponibile prin Vertex AI.<\/p>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Datele sunt noul aur \u2013 companiile \u0219i organiza\u021biile orientate spre cre\u0219tere \u00ee\u0219i dau seama de acest lucru. Afacerile con\u0219tiente analizeaz\u0103 procesele existente, implement\u00e2nd modific\u0103ri \u0219i \u00eembun\u0103t\u0103\u021biri pe baza cifrelor. Unele merg mai departe \u2013 utiliz\u00e2nd posibilit\u0103\u021bile oferite de tehnologie, anticip\u00e2nd tendin\u021be, posibilele schimb\u0103ri ale pie\u021bei \u0219i consecin\u021bele deciziilor de afaceri care urmeaz\u0103 s\u0103 fie luate&#8230;.<\/p>\n","protected":false},"author":43,"featured_media":75163,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_editorskit_title_hidden":false,"_editorskit_reading_time":7,"_editorskit_is_block_options_detached":false,"_editorskit_block_options_position":"{}","footnotes":""},"categories":[562],"tags":[],"class_list":["post-31936","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-google-cloud-platform-ro"],"_links":{"self":[{"href":"https:\/\/fotc.com\/ro\/wp-json\/wp\/v2\/posts\/31936","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/fotc.com\/ro\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/fotc.com\/ro\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/fotc.com\/ro\/wp-json\/wp\/v2\/users\/43"}],"replies":[{"embeddable":true,"href":"https:\/\/fotc.com\/ro\/wp-json\/wp\/v2\/comments?post=31936"}],"version-history":[{"count":0,"href":"https:\/\/fotc.com\/ro\/wp-json\/wp\/v2\/posts\/31936\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/fotc.com\/ro\/wp-json\/wp\/v2\/media\/75163"}],"wp:attachment":[{"href":"https:\/\/fotc.com\/ro\/wp-json\/wp\/v2\/media?parent=31936"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/fotc.com\/ro\/wp-json\/wp\/v2\/categories?post=31936"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/fotc.com\/ro\/wp-json\/wp\/v2\/tags?post=31936"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}