1. Rapid cloud adoption

The global cloud application market is expected to reach 168.6 billion US dollars by 2025. It has aggressively taken over the data governance industry due to its cost-effectiveness and simplified data-sharing capabilities.

Cloud data governance is the practice of setting up policies and processes that streamline data accessibility, usability, integrity, and security within a cloud computing environment. It adds enhanced layers of protection around data security and access. Most cloud solutions adhere to GDPR, CCPA, HIPAA, and other important compliance regulations. Businesses have more visibility and control over their data with cloud-based data governance solutions.

2. Increasing AI integration

The global artificial intelligence market is predicted to hit US$ 1591.03 billion by 2030. AI is a major enabler for businesses to use data efficiently and accelerate data governance initiatives. Several industries leverage AI to study data, derive insights, and enhance operations.

For instance, AI sub-categories like predictive and prescriptive analytics are taking the higher education sector by storm. While predictive analytics will predict potential future outcomes, prescriptive analytics will tell the right methods to achieve the predicted results. Think of a university that uses predictive analysis to find out that 48% of students are likely to enroll in a mental health awareness program. Now, the university can further use prescriptive analytics to realize the prediction.

Another key capability of artificial intelligence is to add automation to core governance processes like data privacy and security. With machine learning algorithms, AI-based data governance solutions can easily detect cyber threats and notify business authorities in time. Modern AI and ML tools tend to reduce data cleansing time and monitor data effectively while enabling businesses to focus on core company operations.

3. Emergence of data democratization

Data democratization means the availability of reliable data to all the people within an organization. People across all departments of an organization have access to the accurate information they need, exactly when they require it. It helps, especially, the non-technical users to gather and analyze data. Simply put, everyone can make sense of data.

When data is connected and put in context throughout the organization, it becomes easier to build a data knowledge graph. The graph can be used to comprehend data about customers, products, employees, and more. A standardized view of data further helps businesses break the rigidity of a traditional data governance framework having data silos. The shift to self-service data and analytics helps improve data governance processes.