From fragmented data to a connected environment

Fragmented business information

Companies often accumulate business data across multiple systems as their operations grow.

Customer information may live in a CRM, operational data in an ERP, financial information in accounting, and production or warehouse data in separate systems.

The problem is not necessarily the amount of data. The problem is that the information can become fragmented, inconsistent and difficult to use across business processes.

This creates challenges when teams need to:

  • Combine information from different systems
  • Support operational workflows
  • Prepare reliable reports
  • Exchange data through EDI
  • Migrate legacy data to modern environments
  • Prepare company information for AI initiatives
  • Control access to sensitive business information

The objective was to create a more connected data environment without requiring the company to replace every existing system.

Connected data architecture

We designed a company-data architecture that connects relevant internal systems through available APIs and other appropriate interfaces.

The approach covers data migration, data integration, data preparation for AI, and reporting, big data and EDI processes.

The exact architecture is defined according to the company's existing systems, data sources, processes, interfaces and security requirements.

Partner
   |
   v
B2B Portal
   |
   +-------------------+
   |         |         |
   v         v         v
Orders    Account   Documents
   |         |         |
   +---------+---------+
             |
             v
      Business processes
             |
      +------+------+
      |             |
      v             v
     CRM           SAP
      |             |
      +------+------+
             |
             v
      External APIs

Key Features

1

Data integration across ERP, CRM, accounting, production and warehouse systems

2

Data migration to cloud and modern systems

3

Data preparation for AI to improve consistency and usefulness

4

Connected business workflows using information from multiple sources

5

Reporting and decision support based on connected business information

6

EDI data processing

The Result

Before

Business information was distributed across separate systems, making it harder to combine, manage and reuse consistently.

After

Relevant information can be connected across systems and made available where it is needed - in workflows, reporting, decision support and AI initiatives.

Key outcomes

  • Data from different systems can be connected in relevant workflows
  • Business information becomes more usable across teams
  • Data quality and consistency can be addressed before AI implementation
  • Existing environments can be modernized or migrated to the cloud
  • Access can reflect business roles and security requirements
  • Data can support reporting, decision-making and EDI
  • Connected information creates a foundation for further automation

These outcomes reflect the service's documented benefits rather than measured project KPIs; the source does not provide numerical performance improvements for a specific implementation.

Key Takeaway

The most important decision is to connect and prepare business data before trying to automate everything around it. A well-structured data foundation makes the same information more useful across operational workflows, reporting, integrations and AI initiatives.

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FAQ

What is a Company Data project?

It is a service for migrating, integrating and preparing business information for operational processes, reporting and AI.

Can existing ERP and CRM systems be connected?

Yes. Relevant systems can be connected through available APIs or other suitable interfaces.

Does the company need to replace its existing systems?

Not necessarily. The approach is based on connecting relevant existing systems and modernizing or migrating data where appropriate.

Can the data be prepared for AI?

Yes. Data can be reviewed and prepared to improve consistency and usefulness for AI initiatives.

Can the solution support manufacturing?

Yes. The approach can connect production, warehouse, ERP, EDI and other business data for operational, reporting or AI use cases.

Can the solution support EDI?

Yes. EDI-related data processing can be included within the project scope.

How is data access controlled?

Access-management requirements are considered according to the data, connected systems, required roles, processes and intended use.

How does a project start?

The process begins by assessing relevant data sources, systems, business processes and access requirements. The appropriate migration, integration, preparation and security approach is then defined.

Technologies

ERP · CRM · Accounting Systems · Production Systems · Warehouse Systems · APIs · Cloud Systems · EDI · Data Integration · Data Migration · Data Preparation · Reporting · AI Data Foundations

Related Services

Data integration · Data migration · AI data preparation · ERP integration · CRM integration · EDI · Business reporting · Custom B2B systems · Business process automation · Enterprise AI