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DX-Solutions - Reclaim your IT freedom

Make your data reliable and usable

Good reporting, efficient processes and useful AI start with data you can rely on. We help you bring together, structure and manage your data.

Discuss your data challenge

Business systems

ERP, CRM and webshop

Files & sources

Bringing data together

Data platform

Collecting · structuring · quality

Reporting

One reliable foundation

Applications & AI

Making data usable

Data quality and ownership across the entire chain

Familiar challenges

  • Different figures

    Multiple versions of the same figures circulate within the organisation.

  • Scattered sources

    Data is spread across different systems and files.

  • Unclear definitions

    What is an ‘active customer’? Every department calculates it differently.

  • No ownership

    No one is responsible for the quality of a dataset.

Questions we help answer

  • How do we combine sales, stock and production figures?
  • How do we establish one consistent foundation for reporting?
  • How do we make historical data usable?
  • How do we organise data quality, definitions and ownership?

A data warehouse brings together structured data for reporting and analysis. A data lake also collects raw and diverse data for further processing. They often complement each other.

Expertise

Data management
Organising the lifecycle and processing of data.
Data governance
Agreements on definitions, ownership, quality and access.
Data warehouses
Bringing together structured data for reporting and analysis.
Data lakes
Collecting different types of data for further processing.
Data quality
Identifying missing, duplicate and inconsistent data.
Data flows and data modelling
Defining how data moves between systems and how it is structured for use.

From source to use

  1. 01

    Data sources

    • ERP
    • CRM
    • webshop
    • files

  2. 02

    Collection and processing

    • data flows
    • transformation
    • quality checks

  3. 03

    Storage and modelling

    • data warehouse
    • data lake
    • data model

  4. 04

    Use

    • reporting
    • applications
    • AI
Governance, data quality and access control apply across the entire chain
Illustrative model; the implementation depends on your environment.

Take control of your data

Reclaim your IT freedom applies to data too. Information that is only accessible through a single source application makes you dependent on that package for every report or new application.

By making data available in a structured way outside the application where it originates, the same information can support reporting, other applications and AI. Replacing a source system also becomes a more manageable exercise.

From agreements to implementation

Data governance also involves organisational work: who owns the data, which definitions apply and who gets access. This page focuses on the technical implementation of those agreements, in data models, checks and access control.

Looking for strategic guidance in defining those agreements? Explore data governance within Think.

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