Who owns the customer master record: Data Governance for Customer 360
Effective customer data management requires clearly defined responsibilities for master record modifications, especially in the context of AI and cybersecurity.
INSIGHTS & PRACTICE
Export operations in practice: contracts, shipment documents, shared data, logistics and responsible AI.
9 publications
Effective customer data management requires clearly defined responsibilities for master record modifications, especially in the context of AI and cybersecurity.
By 2026, over 70% of new enterprise content management (ECM) systems will integrate artificial intelligence capabilities to automate processes and enhance efficiency. This will transform ECM from a passive repository into a proactive decision-making tool.
By 2026, over 70% of successful digital transformation initiatives will rely on an effective Data Governance strategy integrated with artificial intelligence capabilities. This will enable addressing data quality issues critical for system integration. The increasing complexity of enterprise IT land
The growing volume of unstructured data necessitates new archiving approaches. Scriptum.Repository, developed by InBase, integrates AI for efficient corporate archive management, ensuring rapid access and regulatory compliance.
By 2026, over 80% of large corporations will integrate AI capabilities into their electronic document management systems (EDMS) to automate routine operations and enhance efficiency. Megapolis.DocNet, as a key ECM platform, is actively developing in this direction.
Integrating enterprise systems via API is a key factor for quickly bringing new products and services to market. This approach ensures flexibility, scalability, and efficiency in data exchange across diverse IT landscapes.
Approximately 70% of corporate information remains unstructured, complicating document search, analysis, and management. Effective implementation of ECM systems is critical for optimizing business processes and ensuring regulatory compliance.
Increasing data volumes and stricter regulatory requirements necessitate that organizations implement comprehensive Data Governance approaches. Effective system integration is a key factor in realizing these strategies.
The integration of artificial intelligence into electronic document management systems, particularly Megapolis.DocNet, opens new opportunities for automating routine tasks, enhancing efficiency, and improving information security. This enables a reevaluation of approaches to archiving and corporate