Data Transformation to Enable AI Solutions

The organization faced significant challenges managing customer data spread across 12 different systems, including Navision, Salesforce, and SAP. Each department operated in its own silo, with no guidelines for how data was entered, holding inconsistent definitions of what counted as a “customer” and leaving data ownership fragmented as a result. Key issues included:

• Unclear customer classifications, such as B2B versus private
• Duplicate entries
• No standardized process for creating data

Without a centralized validation mechanism, the organization couldn’t maintain data quality or build a unified view of its customer base.

Darize led the effort to enable cross-system integration and improve data quality, giving the organization the structure to align its data strategy with practical execution. The work included:

• Identified and audited the key systems holding customer data
• Mapped processes from data creation through to use
• Developed a unified definition of a customer, based on user needs
• Designed a structure to support a single source of truth
• Introduced data governance to maintain quality data

The transformation laid the foundation for AI and advanced analytics, and prepared for future service portal development. This impact included:

• Enabled a single source of truth through cross-system integration
• Streamlined processes for a unified overview across functions
• Improved data quality and consistency
• Delivered structured data to support the training of AI models