{"id":5839,"date":"2025-12-10T16:09:25","date_gmt":"2025-12-10T14:09:25","guid":{"rendered":"https:\/\/vpc.lv\/?p=5839"},"modified":"2025-12-18T16:45:19","modified_gmt":"2025-12-18T14:45:19","slug":"datu-kuratori-izzina-maksliga-intelekta-iespejas-datu-parvaldiba-konference-lietuva","status":"publish","type":"post","link":"https:\/\/vpc.lv\/lv\/datu-kuratori-izzina-maksliga-intelekta-iespejas-datu-parvaldiba-konference-lietuva\/","title":{"rendered":"Datu kuratori izzina m\u0101ksl\u012bg\u0101 intelekta iesp\u0113jas datu p\u0101rvald\u012bb\u0101 konferenc\u0113 Lietuv\u0101"},"content":{"rendered":"

No 17. l\u012bdz 21. novembrim Vi\u013c\u0146\u0101, Lietuv\u0101 norisin\u0101j\u0101s konference Big Data Conference Europe 2025, kuru apmekl\u0113ja ar\u012b pieci Latvijas datu kuratori: Oksana Zaiceva no R\u012bgas Tehnisk\u0101s universit\u0101tes un Ilm\u0101rs Dukulis, Ingus \u0160mits, J\u0101nis Judrups un Nikolajs B\u016bmanis no Latvijas Biozin\u0101t\u0146u un tehnolo\u0123iju universit\u0101tes.<\/p>\n

Konference pulc\u0113ja vair\u0101k nek\u0101 60 run\u0101t\u0101jus un 700 dal\u012bbniekus no desmitiem valstu un ietv\u0113ra pla\u0161u tematisko loku\u202f- no datu kvalit\u0101tes un p\u0101rvald\u012bbas l\u012bdz m\u0101ksl\u012bg\u0101 intelekta (MI) a\u0123entiem, automatiz\u0101cijai, datu platform\u0101m un organiz\u0101ciju digit\u0101lajai transform\u0101cijai.<\/p>\n

Kopum\u0101 konferenc\u0113 notika septi\u0146as praktisk\u0101s darbn\u012bcas, no kur\u0101m div\u0101s tika uzsv\u0113rta MI izmanto\u0161ana praks\u0113. Darbn\u012bc\u0101 AI For Leaders: Turn Chaos into Clarity \u2013 A Get-it-Done Game Plan for Leaders Who Want Results Yesterday bija iesp\u0113ja apskat\u012bt MI iniciat\u012bvas no vad\u012bbas perspekt\u012bvas\u202f- k\u0101 at\u0161\u0137irt kr\u0101\u0161\u0146us eksperimentus no projektiem ar skaidru biznesa ietekmi un k\u0101 defin\u0113t 3\u20136 m\u0113ne\u0161u ce\u013ca karti pirmaj\u0101m iniciat\u012bv\u0101m. Savuk\u0101rt darbn\u012bc\u0101 Analyse your workflows and upgrade them with AI tika kart\u0113ti savi re\u0101lie darba pl\u016bsmas posmi un identific\u0113tas iesp\u0113jas manu\u0101lus, laikietilp\u012bgus so\u013cus aizst\u0101t ar automatiz\u0101ciju vai MI asistentiem, neiesaistot programm\u0113\u0161anu.<\/p>\n

Galven\u0101s konferences laik\u0101 g\u016bt\u0101s atzi\u0146as:<\/p>\n

    \n
  1. Datu kvalit\u0101te nosaka MI projektu pan\u0101kumus. Ja dati ir nekonsekventi, neprec\u012bzi vai nepiln\u012bgi, MI sist\u0113mas k\u013c\u016bd\u0101s un to rezult\u0101ti nav reproduc\u0113jami, t\u0101p\u0113c MI projekti bie\u017ei netiek realiz\u0113ti \u0101rpus pilotstadijas. Datu kvalit\u0101tes kontrolei j\u0101b\u016bt nep\u0101rtrauktam procesam ar skaidr\u0101m metrik\u0101m un p\u0101rskat\u0101miem testiem gan ra\u017eo\u0161anas sist\u0113m\u0101s, gan p\u0113tniec\u012bbas datu kop\u0101s un studiju projektos.<\/li>\n
  2. Datu l\u012bgumi (data contracts) nodro\u0161ina stabilu pamatu MI ekosist\u0113m\u0101m. Tie defin\u0113 skaidrus noteikumus par datu strukt\u016bru, kvalit\u0101ti un pieg\u0101des atbild\u012bbu starp komand\u0101m un sist\u0113m\u0101m. Tas iev\u0113rojami samazina k\u013c\u016bdas datu pl\u016bsm\u0101s un \u013cauj visiem str\u0101d\u0101t ar vienotu izpratni par datiem. Rezult\u0101t\u0101 MI risin\u0101jumi k\u013c\u016bst stabil\u0101ki un viegl\u0101k uzturami. Datu kuratoriem j\u0101veicina \u0161o l\u012bgumu izstr\u0101de un ievie\u0161ana. \u0160\u0101du l\u012bgumu ideja ir noder\u012bga ar\u012b p\u0113tniec\u012bbas projektos un kursu izstr\u0101d\u0113, lai jau s\u0101kum\u0101 b\u016btu skaidri datu izmanto\u0161anas nosac\u012bjumi.<\/li>\n
  3. Metadatu p\u0101rvald\u012bba un datu izcelsmes izseko\u0161ana ir kritiska moderniem MI risin\u0101jumiem. Bez sak\u0101rtotiem metadatiem MI sist\u0113mas nesp\u0113j saprast kontekstu vai interpret\u0113t datus korekti. RAG, MI a\u0123enti un personaliz\u0113tie m\u0101c\u012bbu ce\u013ci balst\u0101s uz skaidri defin\u0113tu datu semantiku un uzticamu datu katalogu. Tas vienl\u012bdz attiecas uz organiz\u0101ciju datu platform\u0101m, p\u0113tniec\u012bbas datu repozitorijiem un m\u0101c\u012bbu piem\u0113ros izmantotajiem datiem.<\/li>\n
  4. MI projekti bie\u017ei neizdodas datu precizit\u0101tes, nevis tehnolo\u0123ijas d\u0113\u013c. Organiz\u0101cijas nereti koncentr\u0113jas uz mode\u013ciem un r\u012bkiem, aizmirstot sak\u0101rtot datu pl\u016bsmas un atbild\u012bbas. Rezult\u0101t\u0101 MI tiek pieg\u0101d\u0101ti nekvalitat\u012bvi, nesagatavoti dati, kas padara risin\u0101jumus neuzticamus.<\/li>\n
  5. MI iniciat\u012bv\u0101m j\u0101s\u0101kas ar skaidri defin\u0113tu probl\u0113mu. Ja projekts s\u0101kas no r\u012bka, nevis probl\u0113mas, MI rezult\u0101ti ir fragment\u0113ti un mazv\u0113rt\u012bgi. Pareizi defin\u0113ta probl\u0113ma un piesaiste KPI vai citiem m\u0113r\u012bjumiem \u013cauj izv\u0113l\u0113ties piem\u0113rot\u0101ko pieeju un prec\u012bzi nov\u0113rt\u0113t ieguvumus.<\/li>\n
  6. MI j\u0101padara pieejams netehniskiem darbiniekiem, lai t\u0101 v\u0113rt\u012bba tiktu realiz\u0113ta piln\u0101 apjom\u0101. Ja MI izmanto tikai tehnisk\u0101s komandas, organiz\u0101cija zaud\u0113 liel\u0101ko da\u013cu potenci\u0101l\u0101 ieguvuma. Datu kuratoru uzdevums ir nodro\u0161in\u0101t, ka \u0161ie r\u012bki ir savienoti ar pareiziem un saprotamiem datu avotiem, k\u0101 ar\u012b defin\u0113t dro\u0161as lieto\u0161anas robe\u017eas.<\/li>\n
  7. Uzved\u0146u (prompts) vadl\u012bnijas un standarti ir b\u016btiski organiz\u0101cijas l\u012bmen\u012b. Bez vienotiem principiem MI rezult\u0101ti ir nekonsekventi un gr\u016bti kontrol\u0113jami. Kop\u012bgas vadl\u012bnijas nodro\u0161ina kvalit\u0101ti, atk\u0101rtojam\u012bbu un produktivit\u0101ti. T\u0101s ir j\u0101uztver k\u0101 ofici\u0101la, dz\u012bva dokument\u0101cija. Pareizi formul\u0113ti piepras\u012bjumi \u013cauj efekt\u012bvi izmantot MI r\u012bkus datu klasifik\u0101cijai, metadatu \u0123ener\u0113\u0161anai un satura kopsavilkumiem.<\/li>\n
  8. MI a\u0123enti str\u0101d\u0101 uzticami tikai tad, ja procesi un dati ir skaidri defin\u0113ti. A\u0123enti balst\u0101s uz prec\u012bziem API, dokumentiem un datu strukt\u016br\u0101m, t\u0101p\u0113c haotiski dati un neform\u0101li \u201capvedce\u013ci\u201d tie\u0161i p\u0101rv\u0113r\u0161as k\u013c\u016bdain\u0101 uzved\u012bb\u0101.<\/li>\n
  9. Cilv\u0113ku prasmju att\u012bst\u012bba ir b\u016btiska MI v\u0113rt\u012bbas realiz\u0113\u0161anai. Pat modern\u0101kais MI r\u012bks nesp\u0113j dot v\u0113rt\u012bbu, ja komandas nezina, k\u0101 ar to str\u0101d\u0101t un k\u0101 interpret\u0113t rezult\u0101tus. Apm\u0101c\u012bbas un praktiska pieredze ir kritisks produktivit\u0101tes pa\u0101trin\u0101t\u0101js. Datu kuratori un p\u0113tnieki \u0161eit var k\u013c\u016bt par zin\u0101\u0161anu nes\u0113jiem \u2013 demonstr\u0113t lab\u0101s prakses, piem\u0113rus un ierobe\u017eojumus, kas j\u0101\u0146em v\u0113r\u0101, str\u0101d\u0101jot ar datiem un MI.<\/li>\n
  10. MI j\u0101integr\u0113 produktu un pakalpojumu lo\u0123ik\u0101 k\u0101 strat\u0113\u0123isks elements. Kad MI tiek izmantots tikai \u201cpapildu funkcijas\u201d veid\u0101, t\u0101 potenci\u0101ls netiek realiz\u0113ts. Efekt\u012bvie uz\u0146\u0113mumi veido MI k\u0101 centr\u0101lu biznesa v\u0113rt\u012bbas komponenti, nevis kosm\u0113tisku uzlabojumu. Tas nodro\u0161ina m\u0113rogojam\u012bbu un ilgtermi\u0146a konkur\u0113tsp\u0113ju. Datu kuratoriem un p\u0113tniekiem tas noz\u012bm\u0113 dom\u0101t par datiem un mode\u013ciem ne tikai k\u0101 par resursu, bet k\u0101 par da\u013cu no konkr\u0113tiem produktiem un pakalpojumiem.<\/li>\n<\/ol>\n

    Kopum\u0101 konferences saturs vedina secin\u0101t, ka MI projekti nerobe\u017eojas ar mode\u013ciem un platform\u0101m, bet gan balst\u0101s uz cilv\u0113kiem, kas tos izstr\u0101d\u0101, kuru uzdevums vispirms ir ieviest k\u0101rt\u012bbu datos, proced\u016br\u0101s un atbild\u012bbu sadal\u0113. Datu kuratori, p\u0113tnieki un m\u0101c\u012bbsp\u0113ki kop\u0101 sekm\u0113 \u0161\u0101du datu k\u0101rt\u012bbu, skaidr\u012bbu un dro\u0161\u012bbu.<\/p>\n<\/div><\/div><\/div><\/div><\/div>\n","protected":false},"excerpt":{"rendered":"

    No 17. l\u012bdz 21. novembrim Vi\u013c\u0146\u0101, Lietuv\u0101 norisin\u0101j\u0101s konference Big Data Conference Europe 2025, kuru apmekl\u0113ja ar\u012b pieci Latvijas datu kuratori: Oksana Zaiceva no R\u012bgas Tehnisk\u0101s universit\u0101tes un Ilm\u0101rs Dukulis, Ingus \u0160mits, J\u0101nis Judrups un Nikolajs B\u016bmanis<\/p>\n","protected":false},"author":3,"featured_media":5840,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[33],"tags":[],"class_list":["post-5839","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-jaunumi"],"_links":{"self":[{"href":"https:\/\/vpc.lv\/lv\/wp-json\/wp\/v2\/posts\/5839","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/vpc.lv\/lv\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/vpc.lv\/lv\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/vpc.lv\/lv\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/vpc.lv\/lv\/wp-json\/wp\/v2\/comments?post=5839"}],"version-history":[{"count":2,"href":"https:\/\/vpc.lv\/lv\/wp-json\/wp\/v2\/posts\/5839\/revisions"}],"predecessor-version":[{"id":5895,"href":"https:\/\/vpc.lv\/lv\/wp-json\/wp\/v2\/posts\/5839\/revisions\/5895"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/vpc.lv\/lv\/wp-json\/wp\/v2\/media\/5840"}],"wp:attachment":[{"href":"https:\/\/vpc.lv\/lv\/wp-json\/wp\/v2\/media?parent=5839"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/vpc.lv\/lv\/wp-json\/wp\/v2\/categories?post=5839"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/vpc.lv\/lv\/wp-json\/wp\/v2\/tags?post=5839"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}