Data Governance

Gain, shape and retain systematic control over all your digital assets, including data, algorithms or automated decisions.

Data Management

Develop your capabilities in systematic and scalable planning, mining, distribution, and management of your data assets and algorithms – always in compliance with applicable regulatory requirements for data and information assets.

Data Architecture

Bring order to the data chaos, structurally and organizationally. Create a modern, holistic view of your information and data. Anchor data architecture expertise, principles and design guidelines in your existing business and IT architecture (Enterprise Architecture Management).

Data Strategy

Build Data Strategy competency across all levels— transformational, transactional, operational, conceptual—and address the constant call for new data strategies. The right data at the right time, in the right quality, in the right place, with the right person, and at the right price.

Building and Supporting Data Organizations

Design, develop, and lead a modern data organization with high-performing data teams. Integrate data management and engineering, BI, and analytics units into one powerful group. Solve bottlenecks and empower employees, teams, and organizational units. Make your data organization plannable, controllable, and manageable.

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Our Competencies and Capabilities


Design, build, transform and grow your data organization towards effectiveness and performance. Optimize and integrate data processes into your general business, trim for measureable scalability. Don’t let experts tell you it doesn’t work.

Build strong data teams and integrate new data capabilities into the existing organizational set-up.

Identify, evaluate, plan and implement appropriate methods,procedures and technical tools to professionalize and scale your data organization.

Understanding and addressing gaps in data excellence. Transform the non-specific buzzword “Data Literacy” into effective learning.

Data Governance

  • Gain authority over your data-based assets such as data, algorithms, and data-driven processes.
  • Ensure compliance with the growing number of regulatory requirements for operations in different legal settings.
  • Integrate new control and risk measures into your existing governance and compliance environment.
  • Enable enterprise-wide control and governance of your data and support it efficiently with professional data management.

Data Management

  • Align, update and define your data management operations strategy & roadmap.
  • Build operational capabilities around key data management disciplines within one entereprise and/or across multiple organizations and partner networks.
  • Perform structured analysis (Requirements Engineering) at the business, process and technology levels for design and implementation.
  • Identify, evaluate and integrate appropriate tools, software and methods within and outside of the cloud to manage and govern your data assets.

Data Architecture

  • Define your data landscape, current assignment of data assets and data flow. Define, integrate and govern data models for conceptual and coherent architecture.
  • Build in new Enterprise Data Architecture capabilities and integrate them into your established Enterprise Architecture Management standards (including EDA process, artefacts, operating model, standards, principles etc.)
  • Tailor and assign company-wide data asset and other architecture artifacts
  • Enable, qualify and distribute data architecture capabilities and data architects as resources for you digital teams

Data Strategy

  • Determine your data strategy. But be aware that this inflationary term has a vague definition in terms of content or structure. We analyzed 12 publicly available data strategies, and all of them suggested something different.
  • Agree on the dimensions of your data strategy: transformative, transactional, operational or conceptual – you can not have a little of everything.
  • First, carefully formulate, collect and organize the key points of your desired data strategy.
  • Create boundaries and clarity around expectations for future strategic artifacts and an ongoing data strategy process.
  • Define your strategic cornerstones, establish a viable link between business and data strategy, and secure the capabilities needed to execute them.
  • Use modern methods and processes from design thinking for fast and iterative implementations. In doing so, we cooperate with selected partners (e.g. Datentreiber).

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