Compétences data-business-model-expert

📦

data-business-model-expert

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

Révision du contenu r1 Sûr 📁 Accès au système de fichiers⚙️ Commandes externes🌐 Accès réseau

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.

Prend en charge: Claude Codex Code(CC)

🥉 77 Bronze

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Installer avec mon Agent

Copiez cette demande dans votre Agent. Elle contient la page Skill de référence et le manifeste.

Demande d’agent

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.

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Ressources lisibles par les agents

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Détail Markdown GET /skills/dhturing-data-business-model-expert.md manifest signé GET /api/skills/dhturing-data-business-model-expert/manifest lockfile signé GET /api/skills/dhturing-data-business-model-expert/lockfile

Tester

Utilisation de « data-business-model-expert ». We provide custom data governance projects and want more recurring revenue.

Résultat attendu:

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

Utilisation de « data-business-model-expert ». Design a partner program for regional delivery firms.

Résultat attendu:

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.

Utilisation de « data-business-model-expert ». How can we test a DMaaS offer before a large investment?

Résultat attendu:

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

Audit de sécurité

Sûr

v1 • 27/09/2026 Ouvrir le rapport versionné

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.

Fichiers analysés

450

Lignes analysées

Éléments à examiner

Faux positifs ignorés

Facteurs de risque

📁 Accès au système de fichiers (2)

profile.md:38 profile.md:38

⚙️ Commandes externes (3)

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

🌐 Accès réseau (2)

SKILL.md:6 SKILL.md:12

Le dernier audit statique et sémantique terminé n’a détecté aucun constat de sécurité confirmé. Cela ne prouve pas que le skill est sans effets secondaires.

Audité par: codex

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Ouvrir le rapport versionné

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

Badge Markdown

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Badge HTML

<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>

Carte intégrable

<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>

Citations académiques (APA · BibTeX · CFF)

Citation APA

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

Citation BibTeX

@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"

Score Skillstore

Pourquoi ce score Niveau de confiance des preuves: Moyen

Architecture

Maintenabilité

Contenu

Communauté

Conformité aux spécifications

Ce que vous pouvez créer

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.

Essayez ces prompts

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.

Bonnes pratiques

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.

Éviter

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.

Foire aux questions

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.