How to attain DC

HOW to attain DC

- the preposition


The dimension How to attain DC provides continual improvements on competencies that have been proven by commonly accepted practice. That kind of (dialectical) practice gets along without any pre-requisite. It generates rules of common sense, that are quite solid and sustainable, finally composed and fixed by agreed basic principles. They are elaborated most commonly in a discourse and selected settings that fit best to acquire competencies in data.

  • Practice: Social practice is dialogue and (re-)conciliation of competing attitudes. Its intention is to elaborate rules. Thus, social practice elaborates conventional rules within dialectical exchange. Furthermore social practice (re-)uses principles in a dialectical way to evolve advanced conventional rules for higher developed cultures.


  • Rules: Rules are mature propositions, decorated with DC real life experience. Rules are elaborated through dialectical exchange. Rules become principles that are carved out during a discourse. Thus, a rule is an extended formulation and aggregation of principles. Rules are quite similar to principles, but with much more touch to details on dedicated actions within an organizational schema of people.


  • Principles: Like rules, principles are commonly acknowledged facts, but they are not further reducible. Principles are atomic facts. Principles are quite rigid, while rules are more dynamically evolved and updated. Principles guide users through a jungle of terms, taxonomies, articles, and definitions that are cumulated to rules and instructions.

Due to the diverse corporate cultures the service of HOW TO ATTAIN DC calls for deep root cause investigations and thorough customization. Please reach out for further details.

How to attain DC

- the proposition


The DC roadmap visualizes the process of rules and principles acquiring good data competencies. It is a data competencies journey that is composed by 6 phases of practice. The phases develop competencies and trust in data and its stakeholder. DC finally contributes together with DQ and DG to overall credibility.

  1. Analysis: Assess the maturity of data culture
  2. Competence: Define Roles & Responsibilities, and recruit data citizens
  3. Recruitment: Coach data moderator, mentors, and champions
  4. Program: Elaborate mental life cycle, form of life
  5. Engagement: Advertise socialized rules and principles
  6. Competencies: Support self-managing data culture group

This approach is representational and can lead to acknowledged competencies in data.


Know-how: "Train to practice dialogues that lead to cooperation with rules and principles and that equilibrate attitudes to a trustful and cooperative progress" 

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