Companies operating within the European Union (EU) face several significant challenges related to data security and compliance with the General Data Protection Regulation (GDPR). These challenges manifest in various forms and necessitate a multifaceted approach to mitigate potential risks and ensure compliance to regulatory requirements.

Complex compliance requirements:

• Regulatory complexity: GDPR establishes requirements regarding data protection, encompassing principles such as consent, data minimization, purpose limitation, and user rights. Navigating these complexities can be daunting for many organizations, particularly SMEs with limited resources.
• Continuous compliance: GDPR mandates ongoing compliance, requiring organizations to continually assess and adapt their data practices. This includes regular audits and updates to policies and procedures, which can strain resources and operational capabilities.

Data Breach Risks:

• Increased threat landscape: The digital transformation and increased reliance on data, present heightened risks of data breaches and cyberattacks. Organizations must implement robust security measures to protect data from unauthorized access, loss, or theft.

Data Management and processing challenges:

• Data inventory and mapping: Organizations must maintain comprehensive records of personal data processing activities to demonstrate compliance with GDPR. Establishing and keeping an updated data inventory can be challenging, especially for businesses with large volumes of diverse data.

To address the data-related challenges faced by companies in the European business landscape, a comprehensive Data Confidence Assessment solution is essential. The DAQUMA Data Confidence Assessment service comprises several key components designed to analyze, optimize, and enhance an organization’s data management practices.

• Assessment of current data landscape: Begin with a thorough assessment of existing data sources, systems, and architectures to identify silos, redundancies, and integration challenges. This includes evaluating data collection methods, storage, processing, and analysis practices.
• Mapping data flows: Create data flows within the organization to understand how data is currently moving and being utilized across departments.

Data governance framework:

• Implementation of governance policies: Establish clear data governance policies and procedures that define roles, responsibilities, and standards for data management, ensuring compliance with regulations like GDPR.
• Continuous monitoring: Introduce automated tools for ongoing data quality monitoring, ensuring sustained accuracy and reliability of data over time.