技能 data-business-model-expert

📦

data-business-model-expert

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

內容修訂 r1 安全 📁 檔案系統存取⚙️ 外部命令🌐 網路存取

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.

支援: Claude Codex Code(CC)

🥉 77 銅級

Maintain this Skill? Claim it 🥉 77 銅級

使用我的智慧代理安裝

將此請求複製給你的智慧代理，其中包含權威 Skill 頁面和清單。

智能體請求

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.

你的智慧代理仍應顯示其計畫，並依安全政策請求必要確認。

Agent 可讀資源

當 AI Agent、爬蟲或腳本需要乾淨脈絡、而不是讀取完整頁面時，請使用這些連結。

Markdown 詳情 GET /skills/dhturing-data-business-model-expert.md 已簽名 manifest GET /api/skills/dhturing-data-business-model-expert/manifest 已簽名 lockfile GET /api/skills/dhturing-data-business-model-expert/lockfile

測試它

正在使用「data-business-model-expert」。 We provide custom data governance projects and want more recurring revenue.

預期結果:

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

正在使用「data-business-model-expert」。 Design a partner program for regional delivery firms.

預期結果:

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.

正在使用「data-business-model-expert」。 How can we test a DMaaS offer before a large investment?

預期結果:

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

安全審計

安全

v1 • 2026/9/27 開啟版本化報告

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.

已掃描檔案

450

分析行數

複核項目

已忽略的誤報

風險因素

📁 檔案系統存取 (2)

profile.md:38 profile.md:38

⚙️ 外部命令 (3)

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

🌐 網路存取 (2)

SKILL.md:6 SKILL.md:12

最近一次完成的靜態與語意稽核未偵測到已確認的安全發現。這並不能證明該 Skill 沒有副作用。

審計單位: codex

分享與引用此報告

分享版本化評估報告、中性徽章、嵌入卡片與引用。Skillstore 只報告證據，不判斷該 Skill 是否安全。

開啟版本化報告

複製報告連結

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

Markdown 徽章

[![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 徽章

<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>

嵌入卡片

<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>

學術引用 (APA · BibTeX · CFF)

APA 引用

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 引用

@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 評分

評分依據證據置信度: 中

架構

可維護性

內容

社群

規範符合度

你可以打造什麼

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.

試試這些提示

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.

最佳實務

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.

避免

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.

常見問題

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.