Category: Data Governance

Structure Enforcement

Structure enforcement is the practice of ensuring that information, data, or processes follow a specific format or set of rules. This makes data easier to manage, understand, and use. By enforcing structure, mistakes and inconsistencies can be reduced, and systems can work together more smoothly. It is commonly applied in fields like software development, databases,…

Input Sanity

Input sanity refers to the practice of checking and validating data that comes into a system or application to ensure it is correct, safe, and expected. This process helps prevent errors, security issues, and unexpected behaviour by catching bad or malicious data early. By applying input sanity checks, developers can make their software more reliable…

AI for Compliance

AI for Compliance refers to the use of artificial intelligence technologies to help organisations follow laws, regulations and internal policies. This can include monitoring transactions, analysing documents or spotting unusual activity that could signal a rule has been broken. By automating these tasks, AI can help reduce errors, save time and make it easier for…

Decentralized Data Validation

Decentralised data validation is a method of checking and confirming the accuracy of data by using multiple independent sources or participants rather than relying on a single authority. This process distributes the responsibility of verifying data across a network, making it harder for incorrect or fraudulent information to go unnoticed. It is commonly used in…

Decentralized Data Validation

Decentralised data validation is a process where multiple independent participants check and confirm the accuracy of data, rather than relying on a single authority. This approach is often used in systems where trust needs to be distributed, such as blockchain networks. It helps ensure data integrity and reduces the risk of errors or manipulation by…

Data Compliance Automation

Data compliance automation refers to the use of software tools and systems to automatically ensure that an organisation’s data handling practices follow relevant regulations and policies. This might include monitoring, reporting, and managing data according to rules like GDPR or HIPAA. By automating these processes, companies reduce manual work, lower the risk of human error,…

Cloud Governance Metrics

Cloud governance metrics are measurable values that help organisations track how well their rules, policies, and procedures for cloud usage are working. These metrics can include things like cost efficiency, security compliance, resource allocation, and data privacy. By monitoring these numbers, businesses can make sure their cloud systems are safe, efficient, and following company guidelines.

AI for Compliance

AI for Compliance refers to the use of artificial intelligence tools and techniques to help organisations follow rules, regulations, and standards. These systems can automatically check documents, monitor transactions, or flag activities that might break the law or company policies. By automating routine checks and reviews, AI can reduce human error and speed up compliance…

Data Compliance Metrics

Data compliance metrics are measurements used to track how well an organisation follows rules and regulations for handling data. These metrics help ensure that sensitive information is collected, stored, and processed in ways that meet legal and industry standards. Organisations use these metrics to identify gaps, reduce risks, and prove their data practices are compliant…