CRM uye Dhata Mapuratifomu

Nei Kucheneswa Kwedata Kwakakosha uye Mashandisiro Aungaita Dhata Hutsanana Matanho uye Mhinduro

Hunhu husina kunaka hwedata inyaya iri kuwedzera kune vatungamiriri vebhizinesi vazhinji sezvavanotadza kuzadzisa zvinangwa zvavo. Chikwata chevanoongorora data - icho chinofanirwa kuburitsa ruzivo rwakavimbika rwedata - vanopedza 80% yenguva yavo kuchenesa nekugadzirira data, uye 20% chete yenguva chasara kuita ongororo chaiyo. Izvi zvine simba guru pakubudirira kwechikwata sezvo vachifanirwa kutsigira nemaoko mhando yedata yemaseti akawanda.

84% yevakuru vakuru vane hanya nezvemhando yedata yavari kuisa sarudzo dzavo pairi.

Global CEO Outlook, Forbes Insight & KPMG

Mushure mekutarisana nenyaya dzakadai, masangano anotarisa otomatiki, yakapusa, uye yakanyatsojeka nzira yekuchenesa nekumisa data. Mune ino blog, isu tichatarisa zvimwe zvezviitwa zvakakosha zvinobatanidzwa mukucheneswa kwedata, uye kuti ungazvishandise sei.

Chii chinonzi Data Cleansing?

Kucheneswa kwedata ishoko rakafara rinoreva maitiro ekuita kuti data rishandiswe kune chero chinangwa chaunoda. Iyo idhizaini yemhando yekugadzirisa iyo inobvisa ruzivo rwusina kururama uye rusina kufanira kubva kune dataset uye yakajairwa hunhu kuti uwane inowirirana maonero pane ese akasiyana masosi. Iyo nzira inowanzo sanganisira zvinotevera zviitiko:

  1. Bvisa uye chinja -Minda iri mudhatabheti kazhinji ine mavara anotungamira kana ekutevera kana manyorerwo asina basa uye anoda kutsiviwa kana kubviswa kuti iongororwe zviri nani (senge nzvimbo, zero, zvidimbu, nezvimwewo). 
  2. Rongedza uye batanidza - Dzimwe nguva minda ine akaunganidzwa data zvinhu, semuenzaniso, iyo adhiresi munda une Nhamba YemugwagwaZita reMigwagwamanzwiromamiriro, zvichingodaro. Muzviitiko zvakadaro, minda yakaunganidzwa inofanira kukamurwa kuita makoramu akasiyana, nepo mamwe makoramu achifanirwa kubatanidzwa kuti uwane maonero ari nani e data - kana chimwe chinhu chinoshanda pakushandisa kwako.
  3. Shandura mhando dzedata -Izvi zvinosanganisira kushandura mhando yedata yemunda, senge shanduko Nhamba yenhare munda waiva kare tambo to nhamba. Izvi zvinovimbisa kuti zvese zvakakosha mumunda ndezvechokwadi uye zvinoshanda. 
  4. Simbisa maitiro - Mimwe minda inofanirwa kutevedzera patani yakakodzera kana fomati. Nekuda kweizvozvo, maitiro ekuchenesa data anoona maitiro azvino uye anoashandura kuti ave nechokwadi. Somuenzaniso, the US Phone nhamba kutevera muenzaniso: AAA-BBB-CCCC
  5. Bvisa ruzha -Manda edata anowanzo aine mazwi asingawedzere kukosha uye nekudaro, suma ruzha. Semuyenzaniso, funga aya mazita ekambani 'XYZ Inc.', 'XYZ Incorporated', 'XYZ LLC'. Mazita ese ekambani akafanana asi maitiro ako ekuongorora anogona kuaona seakasarudzika, uye kubvisa mazwi akaita seInc., LLC, uye Incorporated kunogona kuvandudza chokwadi chekuongorora kwako.
  6. Matanidza data kuti uone zvakapetwa -Datasets kazhinji ine akawanda marekodhi echinhu chimwe chete. Kusiyanisa kushoma mumazita evatengi kunogona kutungamira timu yako kuita akawanda manyorerwo mudhatabhesi revatengi vako. Iyo yakachena uye yakamisikidzwa dataset inofanira kunge iine marekodhi akasarudzika - rekodhi rimwe pane chimwe chinhu. 

Yakagadziriswa inopesana neUnstructured Data

Imwe yemazuva ano yedhijitari data ndeyekuti haina kuenderana mukukodzera mundima yenhamba kana kukosha kwemavara. Yakamisikidzwa data ndiyo iyo makambani anowanzo kushanda nayo - kuwanda data yakachengetwa mune mamwe mafomati semaspredishiti kana matafura ekushanda nawo zviri nyore. Nekudaro, mabhizinesi ari kushanda neasina kurongeka data zvakanyanya uye zvakanyanya zvakare… izvi ndizvo hunhu date.

Muenzaniso we data isina kurongeka mutauro wechisikigo kubva pane zvinyorwa, odhiyo, uye vhidhiyo masosi. Imwe yakajairika mukushambadzira ndeyekuunganidza brand manzwiro kubva online wongororo. Sarudzo yenyeredzi yakarongeka (semuenzaniso chikamu che1 kusvika ku5 nyeredzi), asi mhinduro haina kurongeka uye iyo data yemhando inofanirwa kugadziriswa kuburikidza nemutauro wechisikigo kugadzirisa (NLP) algorithms kuti aumbe kukosha kwehuwandu hwemanzwiro.

Nzira Yekuita Sei Yakachena Data?

Iyo inonyanya kushanda nzira yekuve nechokwadi chakachena dhata ndeyekuongorora yega yega yekupinda mumapuratifomu ako uye nekuagadziridza iwo nehurongwa kuti ive nechokwadi chekuti data rapinda nemazvo. Izvi zvinogona kuitwa nenzira dzakawanda:

  • Inoda minda - kuve nechokwadi chekuti fomu kana kubatanidzwa kunofanirwa kupfuura minda chaiyo.
  • Kushandisa field data types -Kupa mazita mashoma ekusarudzwa, mataurirwo enguva dzose kufomati data, uye kuchengetedza data mumhando dzakakodzera dzedata kumanikidza data kune iyo fomati yakakodzera uye mhando yakachengetwa.
  • Kubatanidzwa kwebasa rechitatu - kubatanidza zvishandiso zvechitatu-bato kuti uone kuti data yakachengetedzwa zvakanaka, sendima yekero inosimbisa kero, inogona kupa inowirirana, yemhando data.
  • Kugutsikana -Kuita kuti vatengi vako vasimbise nhamba yavo yefoni kana email kero inogona kuve nechokwadi chekuti data chaiyo inochengetwa.

Nzvimbo yekupinda haifanire kungova fomu, inofanirwa kunge iri yekubatanidza pakati pese system inopfuudza data kubva kune imwe system kuenda kune imwe. Makambani anowanzo shandisa mapuratifomu kuburitsa, kushandura, uye kurodha (ETL) data pakati pemasisitimu kuona kuti data rakachena rachengetwa. Makambani anokurudzirwa kuita kuwanikwa kwedata ongororo yekunyora ese ekupinda mapoinzi, kugadzirisa, uye mapoinzi ekushandisa kune data riri mukati mekutonga kwavo. Izvi zvakakosha kuti uve nechokwadi chekutevedzwa nemitemo yekuchengetedza uye mitemo yekuvanzika zvakare.

Nzira yekuchenesa sei data rako?

Nepo kuve nedata rakachena kungave kwakaringana, masisitimu enhaka uye chirango chekupinza uye kutora data kazhinji chiripo. Izvi zvinoita kuti kuchenesa data kuve chikamu chezviitwa zvezvikwata zvekushambadzira. Isu takatarisa mukati memaitiro ayo data yekuchenesa maitiro anosanganisira. Hedzino nzira dzekusarudzika iyo sangano rako rinogona kuita kuchenesa data:

Sarudzo 1: Kushandisa A Code-Based Approach

Python uye R mitauro miviri inowanzo shandiswa yekuronga macoding mhinduro dzekushandisa data. Kunyora zvinyorwa kuti uchenese data zvinogona kuita sezvinobatsira kubva paunosvika pakugadzirisa maalgorithms zvinoenderana nerudzi rwe data rako, zvakadaro, zvinogona kunetsa kuchengetedza zvinyorwa izvi nekufamba kwenguva. Uyezve, dambudziko guru nenzira iyi nderekukodha mhinduro yakajairika inoshanda nemaseseti akasiyana siyana, pane kuomarara-coding chaiwo mamiriro. 

Sarudzo 2: Kushandisa Platform Integration Tools

Mapuratifomu mazhinji anopa programmatic kana codeless zvabatanidza kufambisa data pakati pemasisitimu mune yakakodzera fomati. Akavakirwa-mukati otomatiki mapuratifomu ari kuwana mukurumbira kuitira kuti mapuratifomu abatanidze nyore pakati pezvishandiso zvekambani yavo. Zvishandiso izvi zvinowanzo batanidza zvakakonzeresa kana zvakarongwa maitiro anogona kuitwa pakupinza, kubvunza, kana kunyora data kubva kune imwe system kuenda kune imwe. Mamwe mapuratifomu, senge Robotic Maitiro Ekushandisa (RPA) mapuratifomu, anogona kutopinza data mumasikirini kana kubatanidzwa kwedata kusipo.

Sarudzo 3: Kushandisa Artificial Intelligence

Real-world datasets akasiyana zvakanyanya uye kushandisa zvipingaidzo zvakananga paminda zvinogona kupa mhedzisiro isina kururama. Apa ndipo pane artificial intelligence (AI) inogona kubatsira zvikuru. Kudzidzira modhi pane chaiyo, inoshanda, uye data data uyezve kushandisa mamodhi akadzidziswa pane anouya marekodhi anogona kubatsira mureza anomalies, kuona mikana yekuchenesa, nezvimwe.

Mamwe maitiro anogona kuvandudzwa neAI panguva yekuchenesa data anotaurwa pazasi:

  • Kuona zvisizvo muchikamu.
  • Kuziva zvisizvo zvehukama zvinoenderana.
  • Kutsvaga duplicate rekodhi kuburikidza nekubatanidza.
  • Kusarudza master marekodhi zvichibva pane yakaverengerwa mukana.

Sarudzo 4: Kushandisa Self-Service Data Quality Tools

Vamwe vatengesi vanopa akasiyana emhando yedata mabasa akaiswa semidziyo, senge data yekuchenesa software. Ivo vanoshandisa indasitiri inotungamira pamwe neyevaridzi algorithms kuprofiling, kuchenesa, kuenzanisa, kuenzanisa, uye kubatanidza data munzvimbo dzakasiyana. Zvishandiso zvakadaro zvinogona kuita seplug-uye-kutamba uye zvinoda shoma shoma yenguva yekukwira kana zvichienzaniswa nedzimwe nzira. 

Dare Dhata

Mhedzisiro yemaitiro ekuongorora data yakanaka semhando ye data yekuisa. Nechikonzero ichi, kunzwisisa zvinonetsa zvemhando yedata uye kushandisa yekupedzisira-yekupedzisira mhinduro yekugadzirisa zvikanganiso izvi zvinogona kubatsira kuchengetedza data rako rakachena, rakamira, uye rinoshandiswa kune chero chinangwa chinangwa. 

Data Ladder inopa chinhu-chakapfuma toolkit chinokubatsira kubvisa hunhu husingaenderani uye husina kunaka, kugadzira uye kusimbisa mapatani, uye kuwana maonero akamisikidzwa pane ese madhata zvinyorwa, kuve nechokwadi chemhando yepamusoro yedata, huchokwadi, uye kushandiswa.

Data Ladder - Data Kuchenesa Software

Shanyira Data Ladder Kuti uwane Rumwe Ruzivo

Zara Ziad

Zara Ziad muongorori wekushambadzira kwechigadzirwa pa Dare Dhata ine nhoroondo muIT. Ane shungu nekugadzira dhizaini yekugadzira yemukati inosimbisa chaiyo-yepasirese data hutsanana nyaya dzakatarisana nemasangano mazhinji nhasi. Iye anogadzira zvirimo kuti ataure mhinduro, matipi, uye maitiro anogona kubatsira mabhizinesi kuita uye kuwana inherent data mhando mumabhizinesi avo ehungwaru maitiro. Anoyedza kugadzira zvemukati zvakanangidzirwa kune vakasiyana siyana yevateereri, kubva kuvashandi vehunyanzvi kusvika kune yekupedzisira-mushandisi, pamwe nekuzvishambadza pamapuratifomu akasiyana siyana.

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