Session 3-C
The CDO's Guide to Implementing Gen AI for Analytics: Using Data Fabric to Accelerate Time to Value
The introduction of Generative AI (Gen AI) in the enterprise heralds a new era of advanced analytics and operational efficiency. By harnessing the sophisticated capabilities of Gen AI, businesses can significantly accelerate their decision-making processes and empower their employees across multiple dimensions. Gen AI enables intricate data analysis, natural language processing (NLP), and decision-making with just a few prompts, facilitating faster innovation and competitive advantage.
However, implementation and optimization of Gen AI for enterprise analytics use cases present several challenges. Gen AI is hard to put into production, due to the complexities associated with data integration and secure data access. Additionally, enterprise struggle to tune and deliver consistently high quality and compelling responses to AI-driven questions
A data fabric is a new architecture that can help accelerate GenAI implementations while reducing their risk. A data fabric presents a unified interface for data management, integrating disparate data sources and ensuring consistent data governance and analytics. Gen AI models typically cannot access multiple data management solutions from different vendors and coordinate the complex workflows required to find, retrieve, build, and analyze distributed or unstructured data.
With a modern data fabric, businesses can efficiently manage and analyze data in its existing state while ensuring compliance with regulatory standards and leveraging Gen AI.
Evaluation of data fabrics should focus on four key capabilities:
- Natural Language Interface: From its inception, Promethium has been envisioned with a search-based and natural language interface. This design philosophy aligns perfectly with the operational dynamics of Gen AI, enabling seamless integration and interaction. For Promethium’s data fabric, Gen AI functions as another user querying the system.
- Data Preparation and Querying: By applying NLP to data preparation, query building, data access, pipeline generation, and visualization creation, Promethium reduces the time and complexity associated with data exploration and analysis, making it more accessible to users with varying levels of technical expertise.
- Robust Data Governance: Promethium’s data fabric provides a robust framework for data governance, ensuring that data usage adheres to regulatory and organizational policies. This prevents irrelevant or inaccurate responses by ensuring that governed and trusted data are used.
- Virtual Data Access and Security: The data fabric allows for virtual data access, meaning that data does not need to be transferred to the Gen AI model, thus providing the necessary data security that enterprises require. This aspect is crucial for maintaining trust and compliance, especially in industries with stringent data privacy and security regulations.
- High quality and predictability of AI responses: The Promethium data fabric leverages rich business context and metadata to ensure high quality responses to natural language questions by business users. This problem is particularly acute when NLP questions depend on multiple heterogeneous data sources (cloud data warehouses, SaaS applications, or on-premises data stores). Ensuring trust is critical when rolling out GenAI in production.
While Gen AI presents a paradigm shift in enterprise analytics, its full potential can only be realized with the support of an effective data fabric. Data fabrics should have a search-based natural language interface that is inherently compatible with GenAI. They should be able to quickly access data and provide robust governance, while allowing data teams to rapidly iterate and support self-service NLP and data products for the business users. As a representative example, Promethium data fabric offers all the five capabilities above and delivers fast time to value for business users to get insight from enterprise data, while allowing the strapped data teams to amplify their resources and productivity.
Speaker
kaycee lai
Founder, Promethium
