How AI is Transforming Data Quality and Governance

With data-driven decision-making becoming critical across industries, organizations need access to high-quality data now more than ever. However, managing and governing large volumes of data is challenging with traditional methods. This is an area where artificial intelligence is having a huge impact by automating critical data quality and governance processes.

AI capabilities like machine learning, natural language processing, and cognitive services are being leveraged in various ways to improve data quality:

• Pattern recognition to automatically detect data errors and anomalies for correction
• Automated data profiling using ML algorithms to understand data sources and contexts
• Intelligent data testing tools that can clone human judgment in assessing quality?
• AI-powered data cleansing and standardization at scale

Data governance is also being enhanced using AI capabilities like:

• Automated processes to build, maintain and recommend glossary business terms
• Auto generation of data catalogs with metadata via NLP algorithms??
• Using ML to classify and manage data policies and standards
• Augmenting data stewardship with AI analytics and reporting

The benefits of applying AI for data quality and governance are plentiful:

• Increased trust in data due to higher quality standards
• Accelerated issue resolution by instantly surfacing anomalies
• Better visibility into data landscapes with comprehensive catalogs
• Greater access to data by embedding governance into workflows
• Continued governance improvements from AI feedback loops

The bottom line is that AI is a game changer for data quality and governance. Organizations should assess high-value use cases and pilot AI tools that can automate repetitive governance tasks. With the right strategy, AI can help create a robust data foundation for digital initiatives.