Ga cikakken bayani mai laushi daga shafin yanar gizon Freightos:
Yin Bayanai na Logistics Ƙarfin Aiki: Abubuwan da aka Koya daga Freightos da Gryn
A ranar 7 ga Yuli, 2025, a karfe 07:51, Freightos Blog ya wallafa wani labarin mai taken “Yin Bayanai na Logistics Ƙarfin Aiki: Abubuwan da aka Koya daga Freightos da Gryn”. Labarin ya yi bayani dalla-dalla kan yadda kamfanoni za su iya canza yawan bayanai da ake samu a cikin harkokin jigilarda zuwa abubuwan da za a iya yin aiki da su, ta hanyar amfani da hanyoyin da Freightos da Gryn suka gabatar.
Babban manufar labarin shi ne bayyana mahimmancin amfani da bayanai don inganta ayyukan jigilarda, rage farashi, da kuma samar da ingantaccen shawara ga masu ruwa da tsaki. Freightos, a matsayinta na dandalin sayar da kaya ta yanar gizo, da kuma Gryn, wani kamfani da ke samar da mafita ta fasaha, sun hada kai don nuna yadda ake samun damar yin amfani da bayanai ta hanyar fasaha ta zamani.
Labarin ya tattauna batutuwa masu zuwa:
- Matsalar Bayanai a Harkokin Jigilarda: An fara bayyana cewa harkokin jigilarda na samar da bayanai da dama, amma yawancin wadannan bayanai ba su da inganci ko kuma ba a iya fahimtarsu. Wannan na iya haifar da rashin iya yanke shawara mai kyau da kuma tsadar ayyuka.
- Hanyoyin Magance Matsalar: Freightos da Gryn sun gabatar da mafita da dama, ciki har da:
- Samun Dama ga Bayanai: Yadda ake tattara bayanai daga tushe daban-daban da kuma samar da tsarin da zai ba da damar samun su cikin sauki.
- Tsarin Bayanai (Data Standardization): Muhimmancin tsarin bayanai ta yadda duk bayanai suka kasance a wani tsari guda domin a iya kwatanta su da kuma bincika su.
- Bayanai masu Girma (Big Data) da Nazarin Bayanai (Data Analytics): Yadda za a yi amfani da fasaha don nazarin wadannan bayanai, gano abubuwan da ke tasowa, da kuma hasashen abubuwan da za su iya faruwa a nan gaba.
- Fasahar AI da Machine Learning: Yadda ake amfani da kecijallan hankali (AI) da koyarwar inji (Machine Learning) wajen sarrafa bayanai, gano kasusuwan matsala, da kuma samar da shawarwari masu inganci.
- Sarrafa da Tsinkaya (Visibility and Forecasting): Yadda ake amfani da bayanai don sanin inda kayayyaki suke a kowane lokaci da kuma yin hasashen lokutan isarwa da wadanda za’a samu.
- Manufar Bayanai Ƙarfin Aiki: A ƙarshe, labarin ya jaddada cewa manufar ita ce a mai da bayanai zuwa abubuwan da za a iya amfani da su wajen yanke shawara, inganta ayyuka, da kuma bunkasa kasuwanci. Lokacin da bayanai suka zama ƙarfin aiki, kamfanoni za su iya:
- Ragewa Farashin Jigilarda
- Inganta Tsarukan Ayyuka
- Samar da Gamsuwa ga Abokan Ciniki
- Fitar da Sabbin Hanyoyi da Tsare-tsare
Labarin ya kasance wani sanarwa ga masu ruwa da tsaki a harkokin jigilarda kan yadda fasaha da nazarin bayanai za su iya taimakawa wajen fuskantar kalubalen duniya na yau da kuma inganta ayyuka sosai.
Making Logistics Data Actionable: Insights from Freightos and Gryn
AI ta bayar da labari.
An yi amfani da tambayar mai zuwa don samar da amsa daga Google Gemini:
‘Making Logistics Data Actionable: Insights from Freightos and Gryn’ an rubuta ta Freightos Blog a 2025-07-07 07:51. Da fatan za a rubuta cikakken bayani mai laushi. Da fatan za a amsa a cikin Hausa tare da labarin kawai.