SQLBits 2024
Navigating Data Governance in the Age of Generative AI
In the rapidly evolving world of data analytics, the emergence of Large Language Models (LLMs) has sparked a debate: Are LLMs signaling the end of traditional data analytics? This session delves into the heart of this question, exploring the fundamental workings of LLMs and their transformative impact on the analytics landscape. Attendees will gain insights into the advantages and potential pitfalls of integrating LLMs into their data strategies. We'll discuss the innovative use cases LLMs unlock and emphasize the paramount importance of governance and lineage in harnessing their full potential. Whether you're intrigued by the brilliance of LLMs or wary of their implications, this session will equip you with a balanced perspective to navigate the future of data analytics.
In the rapidly evolving world of data analytics, the emergence of Large Language Models (LLMs) has sparked a debate: Are LLMs signaling the end of traditional data analytics? This session delves into the heart of this question, exploring the fundamental workings of LLMs and their transformative impact on the analytics landscape.
Attendees will gain insights into the advantages and potential pitfalls of integrating LLMs into their data strategy. We'll discuss the innovative use cases LLMs unlock and emphasize the paramount importance of governance and lineage in harnessing their full potential. Whether you're intrigued by the brilliance of LLMs or wary of their implications, this session will equip you with a balanced perspective to navigate the future of data analytics.
This session will explore:
The Rise of Generative AI: A quick overview of the development and potential of generative AI technologies, including GPT, DALL-E, and generative adversarial networks (GANs).
Shifting Paradigms: How generative AI is challenging the established norms in data analytics, from data collection to decision-making.
The Importance of Data Governance: Why and how to establish robust data governance models when integrating generative AI into your existing data ecosystem.
Data Strategy Reimagined: Tools and tactics for formulating a forward-thinking data strategy in an age where data can be generated rather than merely analyzed.
Data Lineage in a Generative World: The importance of tracing data lineage for credibility, quality control, and ethical considerations, especially when generative AI is part of the equation.
Attendees will gain insights into the advantages and potential pitfalls of integrating LLMs into their data strategy. We'll discuss the innovative use cases LLMs unlock and emphasize the paramount importance of governance and lineage in harnessing their full potential. Whether you're intrigued by the brilliance of LLMs or wary of their implications, this session will equip you with a balanced perspective to navigate the future of data analytics.
This session will explore:
The Rise of Generative AI: A quick overview of the development and potential of generative AI technologies, including GPT, DALL-E, and generative adversarial networks (GANs).
Shifting Paradigms: How generative AI is challenging the established norms in data analytics, from data collection to decision-making.
The Importance of Data Governance: Why and how to establish robust data governance models when integrating generative AI into your existing data ecosystem.
Data Strategy Reimagined: Tools and tactics for formulating a forward-thinking data strategy in an age where data can be generated rather than merely analyzed.
Data Lineage in a Generative World: The importance of tracing data lineage for credibility, quality control, and ethical considerations, especially when generative AI is part of the equation.