Gartner’s Innovation Insight: How generative AI is transforming data management solutions
More and more, data and analytics leaders around the world are seeking ways to transform data access and reduce the technical skills barrier using generative AI. This blog post will discuss the key takeaways from the Gartner complimentary report “Innovation Insight: How Generative AI Is Transforming Data Management Solutions” an in-depth look into the potential of generative AI (genAI) to transform the future of data management, showing what to expect from vendors and how to identify potential risks.
You can access the entire complimentary Gartner report to uncover more information about these trends and what we can expect from big data & AI in 2024 here!
Three main benefits and uses of generative AI for data
Generative AI is transforming data management activities through natural language interfaces, making data management and analytics more widely accessible. Integration with metadata management tools will serve to increase future productivity and cost optimization and lower the barrier of entry for data management positions.
Metadata discovery & documentation
Generative AI and language learning models (LLMs) bring a new approach to extending augmented metadata management capabilities that can help extract semantic meaning and identify context in data usage. These capabilities for metadata discovery and knowledge-building are emerging for multiple use cases, including:
- Supporting a data catalog
- Data governance
- Increasing data quality
- Enterprise knowledge management
- Participation in a data fabric structure
GenAI can also be used for generating data management code documentation for queries or data pipelines, making it easier to maintain the overall data management landscape. Data & analytics leaders considering working with generative AI products should remember to always:
- Evaluate the resources and skills supporting human intervention in the process and the ability to leverage specific industry knowledge
- Test documentation generation capabilities as needed and assess their overall impact on your data management teams
Data exploration & code generation
LLM code generation capabilities will transform the way we interact with data, and software vendors are increasingly fine-tuning these LLMs to support enterprise use cases.
- Human-centric interfaces & self-service data: The main benefit identified of these capabilities is to empower any user to interact with data. When combined with graphic generation and data visualization, these capabilities can transform the entire data analytics process.
- Code generation & correction: GenAI can help data professionals create and identify errors in the coding used to organize data and metadata. This code generation allows a new generation of data engineers with increased productivity and a reduced barrier to entry for data jobs. Of course, standard base code knowledge will be needed to ensure there is no logical error or issue in the code generated over time.
Generative AI for administration, optimization, and operational activities
GenAI can be particularly useful in activities that require a more natural language approach to find and organize information including administrative and operational work with everything from data pipelines to system health monitoring. While users will welcome all of these capabilities regardless of their skill level, the capabilities will impact only the user experience and won’t fundamentally change the way data management is being operated.
However, over time, it can be expected that in combination with other AI techniques and code-generation capabilities, much more of the administration and deployment will be automated leading toward self-healing, self-tuning, and cost-optimized systems.
Access the full Gartner report
Looking for even more information about the future of generative AI and data management? For more content like this, discover the Gartner report Innovation Insight: How Generative AI Is Transforming Data Management Solutions – A deep dive into Garter’s research about the potential of AI to change the future of data management.
—
Learn even more about using your data as an asset to achieve higher levels of data governance and data quality with DataGalaxy! Book a demo today to get started on your organization’s journey to complete data lifecycle management and begin your first use case in 90 days or less.
