스킬 data-business-model-expert

📦

data-business-model-expert

Name: data-business-model-expert
Author: 图灵数盟

콘텐츠 리비전 r1 안전 📁 파일 시스템 접근⚙️ 외부 명령어🌐 네트워크 접근

Design Sustainable Data Business Models

Data teams often struggle to turn technical capabilities into repeatable revenue. This skill structures positioning, offerings, revenue, partnerships, defensibility, and phased growth.

지원: Claude Codex Code(CC)

🥉 77 브론즈

Maintain this Skill? Claim it 🥉 77 브론즈

내 에이전트로 설치

이 요청을 에이전트에 복사하세요. 공식 Skill 페이지와 매니페스트가 포함되어 있습니다.

에이전트 요청

Review the Skillstore skill "data-business-model-expert" from https://skillstore.io/skills/dhturing-data-business-model-expert.md and its manifest at https://skillstore.io/api/skills/dhturing-data-business-model-expert/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.

에이전트는 계속해서 계획을 표시하고 보안 정책에서 요구하는 확인을 요청해야 합니다.

에이전트가 읽기 쉬운 리소스

AI 에이전트, 크롤러, 스크립트가 전체 페이지 대신 정리된 컨텍스트만 필요할 때 이 링크를 사용하세요.

Markdown 상세 GET /skills/dhturing-data-business-model-expert.md 서명된 manifest GET /api/skills/dhturing-data-business-model-expert/manifest 서명된 lockfile GET /api/skills/dhturing-data-business-model-expert/lockfile

테스트해 보기

"data-business-model-expert" 사용 중입니다. We provide custom data governance projects and want more recurring revenue.

예상 결과:

Position: managed data monetization partner. Start with a repeatable governance assessment, add annual monitoring, and track recurring revenue share by quarter.

"data-business-model-expert" 사용 중입니다. Design a partner program for regional delivery firms.

예상 결과:

Create basic, professional, and strategic partner tiers.
Link benefits to training, qualified leads, delivery capacity, and verified outcomes.
Base revenue sharing on sourced demand, delivery responsibility, and collection risk.

"data-business-model-expert" 사용 중입니다. How can we test a DMaaS offer before a large investment?

예상 결과:

Run a small paid pilot with one customer segment. Validate willingness to pay, delivery effort, conversion potential, compliance needs, and renewal intent.

보안 감사

안전

v1 • 2026. 9. 27. 버전별 보고서 열기

All 12 static findings are false positives caused by Markdown syntax, documented installation paths, ordinary website links, and the entropy profile of Chinese text. No executable code, network request, obfuscated payload, prompt injection, or malicious intent was found.

스캔된 파일

450

분석된 줄 수

검토 항목

오탐 무시됨

위험 요인

📁 파일 시스템 접근 (2)

profile.md:38 profile.md:38

⚙️ 외부 명령어 (3)

SKILL.md:20 SKILL.md:26 SKILL.md:33

🌐 네트워크 접근 (2)

SKILL.md:6 SKILL.md:12

가장 최근에 완료된 정적·의미론적 감사에서 확인된 보안 발견 사항이 감지되지 않았습니다. 이는 스킬에 부작용이 없음을 증명하지 않습니다.

감사자: codex

이 보고서 공유 및 인용

버전이 지정된 평가 보고서, 중립 배지, 임베드 카드 및 인용을 공유하세요. Skillstore는 근거를 보고하지만 이 Skill의 안전 여부를 판단하지 않습니다.

버전별 보고서 열기

보고서 링크 복사

https://skillstore.io/skills/dhturing-data-business-model-expert/audits/1?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_report

Markdown 배지

[![Skillstore security assessment](https://skillstore.io/badges/skills/dhturing-data-business-model-expert/security.svg)](https://skillstore.io/skills/dhturing-data-business-model-expert?utm_source=security_passport_badge)

HTML 배지

<a href="https://skillstore.io/skills/dhturing-data-business-model-expert?utm_source=security_passport_badge"><img src="https://skillstore.io/badges/skills/dhturing-data-business-model-expert/security.svg" alt="Skillstore security assessment" loading="lazy"></a>

임베드 카드

<iframe src="https://skillstore.io/embed/skills/dhturing-data-business-model-expert.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>

학술 인용 (APA · BibTeX · CFF)

APA 인용

图灵数盟. (2026). data-business-model-expert security audit report (audit version 1) [Author version unspecified]. Skillstore. https://skillstore.io/skills/dhturing-data-business-model-expert/audits/1

BibTeX 인용

@techreport{dhturing-data-business-model-expert-2026,
  author = {图灵数盟},
  title = {data-business-model-expert security audit report (audit version 1)},
  institution = {Skillstore},
  year = {2026},
  number = {1},
  url = {https://skillstore.io/skills/dhturing-data-business-model-expert/audits/1},
  note = {Author version unspecified}
}

CITATION.cff

cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "data-business-model-expert security audit report (audit version 1)"
version: "unspecified"
type: report
authors:
  - name: "图灵数盟"
date-released: "2026-09-27"
url: "https://skillstore.io/skills/dhturing-data-business-model-expert/audits/1"
identifiers:
  - type: other
    value: "skillstore:dhturing-data-business-model-expert:audit:1"
    description: "Skillstore immutable audit report identifier"

Skillstore 점수

이 점수의 이유 증거 신뢰도: 중간

아키텍처

유지보수성

콘텐츠

커뮤니티

사양 준수

만들 수 있는 것

Shape a Data Venture

Compare strategic positions and create an initial architecture, offer portfolio, and revenue mix.

Productize Data Services

Convert repeated custom delivery into standard products, recurring revenue, and measurable transition stages.

Build a Partner Model

Define membership tiers, channel roles, partner benefits, and practical revenue-sharing rules.

이 프롬프트를 사용해 보세요

Assess My Current Model

Review our current data business. Identify our position, revenue sources, strongest assets, major gaps, and three immediate priorities.

Design a Revenue Architecture

Design a 1+4+N business architecture for [company]. Include target customers, services, six revenue types, assumptions, dependencies, and validation steps.

Plan Productization

Create a five-stage roadmap from custom projects to a product and platform model. Define milestones, metrics, reusable assets, owners, and decision gates.

Stress-Test the Business Model

Challenge this proposed data business model: [model]. Test demand, economics, compliance, delivery capacity, partner incentives, defensibility, and failure scenarios. Propose experiments.

모범 사례

Provide verified facts about customers, capabilities, costs, credentials, and regulatory constraints.
Separate evidence, assumptions, recommendations, and open questions in every deliverable.
Validate the model through small paid pilots before funding broad platform development.

피하기

Do not present unverified credentials, partnerships, market figures, or policy claims as facts.
Do not treat membership fees as sustainable revenue without recurring member value.
Do not pursue platform scale before proving repeatable demand and delivery economics.

자주 묻는 질문

What information should I provide?

Provide customer segments, current services, revenue mix, costs, delivery capacity, credentials, partnerships, and growth goals.

What is DMaaS?

DMaaS means Data Monetization as a Service. It covers the path from data preparation through products, transactions, financing, and ongoing operations.

What does 1+4+N mean?

It combines one entry capability, four related service areas, and multiple industry scenarios to support expansion.

Can this skill create financial forecasts?

It can structure assumptions and revenue scenarios. Users must validate prices, costs, conversion rates, and forecasts with current evidence.

Does this skill provide compliance advice?

No. It can identify compliance questions, but qualified legal, accounting, valuation, and regulatory professionals must review decisions.

How should recommendations be validated?

Use interviews, paid pilots, delivery measurements, unit economics, renewal signals, and documented decision gates.