Data Nkasa Nkyerɛ Wo
Nsɛm a wɔka
Mewayz Team
Editorial Team
Data Nkasa Nkyerɛ Wo
Wɔ nnɛyi adwumayɛ tebea mu no, yɛtaa te nsɛmfua te sɛ "data-driven decision making" ne "ma data no nkasa." Nea ɛkyerɛ ne sɛ data yɛ oracle a emu da hɔ, a emu nna hɔ, a wasiesie ne ho sɛ ɔbɛda n’ahintasɛm adi sɛ yɛhwɛ no denneennen sɛnea ɛsɛ kɛkɛ a. Eyi yɛ adwene a ɛnteɛ a asiane wom. Raw data, wɔ ne spreadsheets a ɛtrɛw ne dashboard ahorow a enni awiei mu no yɛ komm. Ɛnkasa; ɛwɔ hɔ ara kwa. Mfaso ankasa—ne adwuma ankasa—gyina saa kommyɛ no nkyerɛase mu, nsɛm a ɛfata a wobebisa de adaadaa asɛm bi a ntease wom no so. Sɛ nsɛm a ɛfa ho, nkyerɛase, ne nhyehyɛe a emu da hɔ a wɔde bɛte ase nni hɔ a, data yɛ dede ara kwa.
Nsɛm a Ɛda N’ankasa Ho Ho Nsusuwii
Fa no sɛ wɔde nɔma biako rekyerɛ wo: nkɔanim 15% wɔ wɛbsaet no so wɔ ɔsram a etwaam no mu. Wɔ n’ankasa mu no, saa data point yi yɛ mum. So saa nkɔso yi ye anaasɛ enye? Egyina so. So ɛyɛ nea efii aguadi ɔsatu bi a edii yiye mu bae, anaasɛ mfiridwuma mu mfomso bi maa bot akwantu yɛɛ kɛse? So ɛma wɔtɔn nneɛma pii, anaasɛ na nsrahwɛfo no mfa wɔn a w’ani si wɔn so no ho? Data nsɛntitiriw te sɛ nsɛmfua ankorankoro a wɔatwe afi ayɛsɛm mu. Sɛ kasamu ne nkyekyem ahorow a atwa ho ahyia—nsɛm a ɛfa ho—no nni hɔ a, nea ɛkyerɛ ankasa no yera. Yɛtɔ afiri a ɛne sɛ yɛbɛsusu sɛ data yɛ nea ɛda adi ankasa ɛfiri sɛ yɛtaa fa yɛn ankasa animhwɛ so hwɛ no, na yɛhunu deɛ yɛgye di dedaw no ho si so dua sene sɛ yɛbɛhunu deɛ ebia data no rebɔ mmɔden sɛ ɛbɛka ankasa.
Ɛsɛ sɛ Wobisa Nsɛm a Ɛfata
Esiane sɛ data nkasa nti, ɛsɛ sɛ yɛbɛyɛ nsɛmbisafo a wɔn ho akokwaw. Adeyɛ a ɛma wonya nhumu no nyɛ atie a wɔnyɛ hwee; ɛyɛ nkɔmmɔbɔ a ɛyɛ nnam, ɛtɔ mmere bi a ɛyɛ den. Ɛsɛ sɛ wubisa sɛ: "Dɛn ntia?", "Enti dɛn?", ne "Na sɛ?". Eyi ne baabi a nsakrae a efi data so kɔ nyansa so no ba.
- Nkitahodi vs. Nea ɛde ba: Esiane sɛ metric abien bom tu nti, ɛnkyerɛ sɛ biako na ɛde foforo ba. Nsukyenee a wɔtɔn a ɛkɔ soro no ne nsu a ɛtɔ gu nsu mu no wɔ abusuabɔ, nanso biako mfa ɔfoforo no mma; awɔw bere mu ɔhyew ne ade a ahintaw.
- Nsɛm a ɛfa ho no yɛ Ɔhene: Adetɔn a ɛso atew 10% wɔ ɔmantam biako mu no yɛ hu a nsɛm a ɛfa ho nni mu. Nanso sɛ wuhu sɛ akansifo kɛse bi fii ase yɛɛ ɔsatu kɛse bi a wɔtew nneɛma so wɔ hɔ a, asɛm no sesa koraa.
- Bisa Fibea no ho asɛm: Ɛhe na saa data yi fi bae? So edi mũ, ɛyɛ pɛpɛɛpɛ, na wɔaboaboa ano bere nyinaa? Data a mfomso wom ma wonya nsɛm a mfomso wom, ɛmfa ho sɛnea nkyerɛasefo no ho akokwaw.
Botaeɛ ne sɛ yɛbɛkɔ akyiri asen "dɛn" no na yɛada "dɛn ntia" no adi, adane akontabuo a wɔanhyɛ da ayɛ no nimdeɛ a wɔtumi de yɛ adwuma.
Asiane a Ɛwɔ Nkyerɛase a ɛnteɛ ne Animhwɛ mu
Sɛ yɛfa data sɛ ɛnne a mfomsoɔ nni mu a, yɛde yɛn ho to asiane mu sɛ yɛbɛkyerɛ aseɛ a ɛntene kɛseɛ. Yɛn adwene mu animhwɛ nya sɛnea yɛkenkan akontaahyɛde ahorow no so nkɛntɛnso kɛse. Confirmation bias de yɛn kɔ cherry-pick data a ɛfoa yɛn hypotheses a na ɛwɔ hɔ dedaw no so bere a yebu yɛn ani gu adanse a ɛbɔ abira so no. Nkwagye ho animhwɛ ma yɛde yɛn adwene si nea efi mu ba a edi mu a yebetumi ahu nkutoo so, na yebu yɛn ani gu nsɛm a ɛho hia a efi huammɔdi ahorow mu a ɛtaa yɛ nkyerɛkyerɛ kɛse no so. Wobetumi adi mfomso aka sɛ anomalies yɛ nneɛma a ɛkɔ so, na wobetumi akyerɛ nsakrae a ɛba bere tiaa mu ase sɛ nsakrae a ɛba bere tenten. Eyi nti na ɔkwan a wɔateɛ so, a wɔahyehyɛ no yiye a wɔfa so hwehwɛ data mu no nyɛ nea wontumi nsusuw ho no. Ɛyɛ ɔkwan baako pɛ a yɛbɛfa so ama dede a ɛwɔ yɛn ankasa nsusuwii mu no ayɛ komm na yɛate nokware sɛnkyerɛnne a ɛyɛ mmerɛw a ɛwɔ data no mu.
Data yɛ adwinnade a ɛma nkateɛ yɛ kɛseɛ, ɛnyɛ sɛ wɔde besi ananmu. Akontaabu no de adanse no ma, nanso onipa adwene de asɛm a wɔka, ɔkwan a wɔfa so yɛ ade, ne nyansa a wɔde bɛyɛ ade ma.
Nkɔmmɔbɔ Nhyehyɛe a Wobɛkyekye: W’adwuma OS Dwuma
Sɛ wopɛ sɛ wo ne wo data bɛbɔ nkɔmmɔ a ɛsow aba a, wuhia pii sen anigye a wubehu ara kwa; wuhia nhyehyɛe bi a wɔde bɛyɛ nhyehyɛe. Eyi ne baabi a adwumayɛ nhyehyɛe a wɔaka abom bɛyɛ nea ɛho hia kɛse. Tech stack a apaapae—a data a wɔde ahyɛ silo ahorow mu ma adetɔn, aguadi, ne adwumayɛ—ma ɛkame ayɛ sɛ wontumi bisabisa nsɛm. Woaka kasamu a enni mũ ne nokware fã.
Wɔayɛ platforms te sɛ Mewayz sɛ ɛbɛbubu saa silos yi, ayɛ central modular hub a data a ɛfiri w’adwuma no fã biara mu no bata ho na ɛwɔ contextualized. Mewayz mma data no nkasa, nanso ɛma wo nnwinnade a wode bisa nsɛm a eye. Ɛdenam wo CRM, adwuma no sohwɛ, ne sikasɛm ho nsɛm a wode bɛka nokware fibea biako ho so no, wubetumi akɔ akyiri asen metrics a atew ne ho na woahu w’adwuma no ho asɛm a ɛka bom. Wubetumi abisa nsɛm a ɛyɛ den te sɛ, "Ɔkwan bɛn so na yɛn nneɛma a aba foforo a yɛde too gua no nyaa adetɔfo mmoa tekiti dodow ne sika a wɔsan nya no so nkɛntɛnso?" Saa adwene a ɛfa biribiara ho yi ne fapem a wɔde bɛdan data a ɛnyɛ komm ayɛ no nkɔmmɔbɔ a ɛfa ɔkwan a wɔfa so yɛ adwuma.
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Start Free →Awieeɛ: Yɛ Data Asɛm Kafoɔ
Ɛnsɛ sɛ mantra ma nnɛyi adwumayɛfo kannifo no yɛ "ma data no nkasa," na mmom "Mɛtie yiye na mabisabisa nsɛm kɔ akyiri." Data ne raw material, adanse a ɛwɔ asɛm a woresi no mu. Wo dwumadie yɛ detective, analyst, ne abasɛm kyerɛwfoɔ. Ɛdenam gye a wugye tom sɛ data yɛ komm so no, woma wo ho tumi sɛ wubehu ne nne. Wosua sɛnea wobɛkyekyere asɛm no, wobɛka nsensanee no abom, na woanya nhumu a ɛkanyan adeyɛ a nyansa wom. Sɛ wowɔ atenaeɛ a wɔahyehyɛ te sɛ Mewayz a ɛde stage no ma a, wobɛtumi ahwɛ sɛ nkɔmmɔdie a ɛne wo data no mu da hɔ, ɛne ne ho hyia, na awieeɛ koraa no, ɛyɛ nsakraeɛ ma w’adwuma.
