Aya maviri Data Science buzzwords anovhiringa vanhu vazhinji. Data Mining inowanzosanzwisiswa sekubvisa uye kudzoreredza data, asi chokwadi chakanyanya kuoma. Mune ino positi, ngatiite dot Mining uye tigoona mutsauko uripo pakati peData Mining uye Kubvisa Dhata.
Chii chinonzi Data Mining?
Data mining, inonziwo Ruzivo Kuwanikwa muDatabase (KDD), inzira inowanzoshandiswa kuongorora huwandu hwe data uchishandisa nhamba uye masvomhu maitiro ekutsvaga akavanzwa maitiro kana maitiro uye kubvisa kukosha kubva kwavari.
Chii chaungaite neData Mining?
Nekuita otomatiki maitiro, inogona kuongorora dhatabhesi uye kunyatsoona mapatani akavanzika. Kune mabhizinesi, kucherwa kwedata kunowanzo shandiswa kuona mapatani uye hukama mune data kubatsira kuita zvirinani bhizinesi sarudzo.
Mienzaniso yekushandisa
Mushure mekunge kucherwa kwedata kwakapararira muma1990s, makambani ari mumaindasitiri akasiyana siyana, anosanganisira zvitoro, mari, hutano hwehutano, zvekufambisa, telecommunication, e-commerce, nezvimwewo, akatanga kushandisa nzira dzekuchera data kuti awane ruzivo kubva pane data. Kuchera data kunogona kubatsira chikamu vatengi, kuona hutsotsi, kufungidzira kutengesa, uye zvimwe zvakawanda.
- Customer segmentation
Nekuongorora dhata revatengi uye nekuona hunhu hwevatengi vanovavarira, makambani anogona kuvanangisa muboka rakasiyana uye nekupa zvakakosha zvinosangana nezvido zvavo. - Market Basket Analysis
Iyi nzira inobva pane dzidziso yokuti kana iwe ukatenga rimwe boka rezvigadzirwa, iwe unogona kutenga rimwe boka rezvigadzirwa. Mumwe muenzaniso wakakurumbira: apo vanababa vanotengera vana vanapukeni, vanowanzotenga doro pamwe chete nemanapukeni. - Kufanotaura kwekutengesa
Inogona kuita seyakafanana nekuongorora bhasikiti yemusika, asi ino nguva yekuongorora data inoshandiswa kufanotaura apo mutengi achatenga chigadzirwa zvakare mune ramangwana. Semuenzaniso, murairidzi anotenga gaba reprotein rinofanira kugara kwemwedzi mipfumbamwe. Chitoro chinotengesa protein iyi chinoronga kuburitsa chitsva mumwedzi ye9 kuitira kuti murairidzi atenge zvakare. - Kuonekwa kwehutsotsi
Kuchera data kunobatsira mumamodheru ekuvaka kuona hutsotsi. Nekuunganidza sampuli dzehutsotsi uye zviri pamutemo mishumo, mabhizinesi anopihwa simba rekuona kuti ndezvipi kutengeserana kuri kufungidzira. - Kuonekwa kwemaitiro mukugadzira
Muindasitiri yekugadzira, kuchera data kunoshandiswa kubatsira kugadzira masisitimu nekuona hukama pakati pechigadzirwa chivakwa, chimiro, uye zvinodiwa nevatengi. Kuchera data kunogona zvakare kufanotaura nguva yekuvandudza chigadzirwa uye mutengo.
Uye aya angori mashoma mashoma ekushandisa kuchera data.
Matanho ekuchera data
Kuchera dhata ndiyo yakazara maitiro ekuunganidza, kusarudza, kuchenesa, kushandura uye kubvisa data kuti uongorore mapatani uye pakupedzisira kubvisa kukosha.
Kazhinji, iyo yese yekuchera data maitiro inogona kupfupikiswa kuita 7 matanho:
- Data kuchenesa
Munyika chaiyo, data haiwanzocheneswa uye yakarongeka. Kazhinji dzine ruzha, dzisina kukwana, uye dzinogona kunge dziine zvikanganiso. Kuti uve nechokwadi chekuti mhedzisiro yekuchera data ndeyechokwadi, iwe unofanirwa kutanga wachenesa iyo data. Dzimwe nzira dzekuchenesa dzinosanganisira kuzadza hunhu husipo, otomatiki uye manyorero ekudzora, zvichingodaro. - Data Integration
Iyi ndiyo nhanho iyo data kubva kwakasiyana masosi inotorwa, yakabatanidzwa uye yakabatanidzwa. Zvinyorwa zvinogona kunge zviri dhatabhesi, mameseji mafaira, maspredishiti, zvinyorwa, multidimensional datasets, Internet, zvichingodaro. - Data sampling
Kazhinji, haisi yese data yakabatanidzwa inodiwa mukuchera data. Data sampling ndiyo nhanho iyo chete inobatsira data inosarudzwa uye inotorwa kubva kune yakakura database. - Kushandurwa kwedata
Kana iyo data yasarudzwa, inoshandurwa kuita mafomu akakodzera kumigodhi. Iyi nzira inosanganisira normalization, aggregation, generalization, nezvimwe. - Data Mining
Pano panouya chikamu chakakosha chekuchera data - kushandisa nzira dzakangwara kuwana mapatani mavari. Maitiro acho anosanganisira kudzoreredza, kupatsanura, kufanotaura, kubatanidza, kudzidza kushamwaridzana, nezvimwe. - Kuongorora kwemuenzaniso
Danho iri rine chinangwa chekuona maitiro anogona kubatsira, ari nyore kunzwisisa, pamwe nemapatani anotsigira fungidziro. - Kumiririrwa Nezivo
Padanho rekupedzisira, ruzivo rwakawanikwa runoratidzwa nenzira inoyevedza uchishandisa ruzivo rwekumiririra uye nzira dzekuona.
Kuipa kweData Mining
- Kudyara kukuru kwenguva nebasa
Sezvo kuchera data inguva yakareba uye yakaoma, inoda basa rakawanda kubva kuvanhu vanogadzira uye vane hunyanzvi. Vanochera data vanogona kutora mukana wezvishandiso zvine simba zvekuchera data, asi zvinoda nyanzvi kuti dzigadzirire data uye dzinzwisise mhedzisiro. Nekuda kweizvozvo, zvinogona kutora nguva kugadzirisa ruzivo rwese. - Kuvanzika uye kuchengetedzwa kwedata
Sezvo kuchera data kunounganidza ruzivo rwevatengi kuburikidza nenzira dzemusika, zvinogona kukanganisa kuvanzika kwevashandisi. Uye zvakare, hackers vanogona kuwana data yakachengetwa mune data mining masisitimu. Izvi zvinounza kutyisidzira kune kuchengetedzwa kwevatengi data. Kana data yakabiwa ikashandiswa zvisizvo, inogona kukuvadza vamwe nyore.
Izvo zviri pamusoro apa ishumo pfupi yekuchera data. Sezvandambotaura, kuchera data kune nzira yekuunganidza nekubatanidza data, iyo inosanganisira nzira yekubudisa data (data extraction). Muchiitiko ichi, zvakachengeteka kutaura kuti kubviswa kwedata kunogona kuve chikamu chenguva refu yekuchera data.
Chii chinonzi Data Extraction?
Iyo inozivikanwawo se "web data mining" uye "web scraping", chiitiko ichi chiito chekutora data kubva (kazhinji isina kurongeka kana kurongeka zvisina kurongeka) zvinyorwa zve data munzvimbo dzepakati uye centralization munzvimbo imwechete yekuchengetedza kana kuenderera mberi kugadzirisa. Kunyanya, asina kurongeka data masosi anosanganisira mapeji ewebhu, email, zvinyorwa, mafaera ePDF, zvinyorwa zvakaongororwa, mainframe mishumo, reel mafaera, zviziviso, zvichingodaro. Kuchengetera kwepakati kunogona kuve kwenzvimbo, gore kana hybrid. Zvakakosha kuyeuka kuti kubudiswa kwedata hakusanganisi kugadzirisa kana kumwe kuongorora kunogona kuitika gare gare.
Chii chaungaita neData Extraction?
Chaizvoizvo, zvinangwa zvekubvisa data zvinowira muzvikamu zvitatu.
- Archive
Kudhirowa kwedata kunogona kushandura data kubva kumhando dzemuviri senge mabhuku, mapepanhau, invoice kuita mafomati edhijitari akadai sedhatabhesi rekuchengetedza kana backup. - Kuchinja data format
Paunenge uchida kutamisa data kubva kune yako saiti kuenda kune imwe nyowani iri kuvandudzwa, unogona kuunganidza data kubva kune yako saiti nekuibvisa. - Data analysis
Kuwedzera kuongororwa kweiyo data yakabviswa kuti uwane nzwisiso yakajairika. Izvi zvingaita sezvinenge zvakafanana nekuchera data, asi ramba uchifunga kuti kuchera data ndicho chinangwa chekuchera data, kwete chikamu chayo. Uyezve, iyo data inoongororwa zvakasiyana. Mumwe muenzaniso: Varidzi vezvitoro zvepamhepo vanobvisa ruzivo rwechigadzirwa kubva kune e-commerce saiti seAmazon kutarisa mazano evanokwikwidza munguva chaiyo. Kufanana nekuchera data, kudhirowa kwedata inzira yeotomatiki ine mabhenefiti akawanda. Kare vanhu vaikopota nekunamira data nemaoko kubva kune imwe nzvimbo kuenda kune imwe, izvo zvaitora nguva zvakanyanya. Kutorwa kwedata kunomhanyisa kuunganidzwa uye kunovandudza zvakanyanya kurongeka kweiyo data yakatorwa.
Mimwe mienzaniso yekushandisa Data Extraction
Zvakafanana nekuchera data, kuchera data kunoshandiswa zvakanyanya mumaindasitiri akasiyana. Pamusoro pekutarisa mitengo mu e-commerce, kuchera data kunogona kubatsira mukutsvagisa kwako, kuunganidza nhau, kushambadzira, zvivakwa, kufamba uye kushanya, kubvunza, mari nezvimwe zvakawanda.
- Mutungamiriri wechizvarwa
Makambani anogona kutora data kubva kumadhairekitori: Yelp, Crunchbase, Yellowpages uye kugadzira inotungamira yekusimudzira bhizinesi. Unogona kutarisa vhidhiyo pazasi kuti udzidze nzira yekubvisa data kubva kuYellowpages uchishandisa . - Aggregation yezvinyorwa uye nhau
Zvemukati aggregation mawebhusaiti anogona kugashira nzizi dze data kubva kune akati wandei masosi uye kuchengetedza mawebhusaiti avo ari maererano. - Sentiment Analysis
Mushure mekutora ongororo, makomendi, uye zvipupuriro kubva pasocial network se Instagram ne Twitter, nyanzvi dzinogona kuongorora maitiro ari pasi uye kuwana ruzivo rwekuti rudzi, chigadzirwa, kana chiitiko chinoonekwa sei.
Data Kutorwa Matanho
Kubvisa dhata ndiyo nhanho yekutanga yeETL (Kubvisa, Shandura, Kutakura: Kubvisa, Shandura, Kutakura) uye ELT (Kubvisa, Kutakura, uye Shandura). ETL neELT ivo pachavo chikamu cheyakazara data yekubatanidza zano. Mune mamwe mazwi, kuburitsa data kunogona kuve chikamu chekutora kwavo.
Bvisa, shandura, takura
Nepo kuchera data kuri pamusoro pekubvisa ruzivo kubva kune yakawanda data, kudhirowa kwedata ipfupi uye iri nyore maitiro. Inogona kuderedzwa kusvika pamatanho matatu:
- Kusarudza nzvimbo yedata
Sarudza kwaunoda kubvisa data kubva, senge webhusaiti. - Data collection
Tumira chikumbiro che "GET" kune saiti uye patsanura mhedzisiro HTML gwaro uchishandisa programming mitauro yakaita sePython, PHP, R, Ruby, nezvimwe. - Dhata yekuchengetedza
Sevha data mudura renzvimbo yako kana chengetedzo yegore kuti ushandise mune ramangwana. Kana iwe uri mugadziri ane ruzivo anoda kuburitsa data, matanho ari pamusoro angaite seakapusa kwauri. Nekudaro, kana ukasakodha, nzira yekudimbudzira ndeye kushandisa maturusi ekubvisa data, semuenzaniso. . Maturusi ekubvisa data, senge maturusi ekuchera data, akagadzirirwa kuchengetedza simba uye kuita kuti kugadzirisa kwedata kuve nyore kune wese munhu. Zvishandiso izvi hazvisi zvehupfumi chete, asiwo zvekutanga-ane hushamwari. Vanobvumira vashandisi kuunganidza data mukati memaminitsi, kuichengeta mugore, uye kuitumira kune akawanda mafomati: Excel, CSV, HTML, JSON, kana kune dhatabhesi pane saiti kuburikidza neAPI.
Zvakashata zveData Extraction
- Server crash
Paunenge uchibvisa data pamwero mukuru, sevha yewebhu yenzvimbo inotarirwa inogona kunge yakawandisa, izvo zvinogona kutungamirira kune kuparara kwevhavha. Izvi zvinokuvadza zvido zvemuridzi wesaiti. - Kurambidzwa neIP
Kana munhu akaunganidza data kakawanda, mawebhusaiti anogona kuvharisa IP kero yavo. Chinhu chinogona kurambidza zvachose IP kero kana kurambidza kupinda nekuita kuti data ive isina kukwana. Kuti utorezve data uye udzivise kuvharira, unofanirwa kuzviita nekumhanya zvine mwero uye kushandisa mamwe maitiro e-anti-blocking. - Matambudziko nemutemo
Kubvisa data kubva pawebhu kunowira munzvimbo yegrey kana zvasvika kune zviri pamutemo. Masayiti makuru akadai seLinkedin neFacebook anotaura zvakajeka mumashoko avo ekushandisa kuti chero otomatiki kutorwa kwedata kunorambidzwa. Pakave nematare akawanda pakati pemakambani nekuda kwezviitiko zve bot.
Misiyano Yakakosha Pakati peData Mining uye Kubvisa Dhata
- Kucherwa kwedata kunonziwo kuwanikwa kweruzivo mumadhatabhesi, kuburitsa ruzivo, data/pattern analysis, kuunganidza ruzivo. Kudhirowa kwedata kunoshandiswa zvakasiyana newebhu data kudhirowa, webhu peji scanning, kuunganidza data, zvichingodaro.
- Tsvagiridzo yekuchera dhata inowanzoenderana nedata rakarongeka nepo kuchera data kunowanzo kutorwa kubva kune zvisina kurongeka kana kurongeka zvisina kunaka.
- Chinangwa chekuchera data ndechekuita kuti data iwedzere kubatsira pakuongorora. Kutora data kuunganidzwa kwedata munzvimbo imwechete kwarinogona kuchengetwa kana kugadziriswa.
- Ongororo mukucherwa kwedata kwakavakirwa panzira dzemasvomhu dzekuziva mapatani kana mafambiro. Kudhirowa kwedata kunoenderana nemitauro yekuronga kana maturusi ekubvisa data kunzvenga masosi.
- Chinangwa chekuchera data ndechekutsvaga chokwadi chaive chisati chazivikanwa kana kufuratirwa, nepo kutorwa kwedata kunobata neruzivo rwuripo.
- Kuchera data kwakanyanya kuoma uye kunoda mari yakakura mukudzidzisa vanhu. Kutora data nechishandiso chakakodzera kunogona kuve nyore zvakanyanya uye kudhura.
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