AI Technologies , Generative AI , Large Language Models

Gen AI's Impact on Analytics Programs in Enterprises

Digital Planet's Dominic Albrecht on Transforming Data Into Narrative-Driven Format
Gen AI's Impact on Analytics Programs in Enterprises
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With the potential to significantly enhance data accessibility, generative AI is shaping the future of analytics programs within organizations. The data industry has long emphasized the importance of data literacy, yet progress has been limited. Large language models, LLMs, could be the missing piece of the puzzle, adding a layer of context to data, making it more understandable, usable and accessible, said Dominic Albrecht, head of analytics at Digital Planet, a South Africa-based company focusing on enabling e-commerce for enterprises.

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The variability in how people phrase their questions or input prompts has long been a challenge for analytics technology. Drawing upon his background in support function, Albrecht highlighted that a question - when spoken and written - can lead to distinct interpretations, adversely impacting the quality of analytics insights.

Natural language queries hold a significant potential in this space, said Albrecht. "LLMs such as ChatGPT can play a crucial role in facilitating natural language queries, making data more accessible. It also makes the interpretation of data simple and more straightforward," he said. "It's ability to enhance intuitiveness benefits both the way the questions are posed, and the insights provided by AI."

From a user perspective, it simplifies the process of asking questions and extracting insights from data. It also aids in interpreting complex graphs and understanding trends. Albrecht emphasized the issue of personal bias and varying interpretations when different individuals view the same graph. Generative AI-generated insights help eliminate some of these biases, making data analysis more objective and comprehensible.

Some of the visualization tools are now incorporating contextual layers using LLMs, transforming data into a narrative-driven format. This approach transforms raw data, charts and graphs into a more narrative format, making it more accessible and actionable.

By enhancing data accessibility and lucidity, generative AI will be a significant catalyst for data adoption, literacy and monetization in the coming years. Enterprises that harness the potential of generative AI stand to gain a competitive edge in an increasingly data-driven world.

Generative AI is poised to redefine the future of analytics programs within organizations. The synergy between generative AI and enterprise analytics offers promising prospects. As enterprises continue to explore and implement generative AI in analytics, the data landscape is on the brink of a new era where it drives informed and intelligent decision-making.


About the Author

Shipra Malhotra

Shipra Malhotra

Managing Editor, ISMG

Malhotra has more than two decades of experience in technology journalism and public relations. She writes about enterprise technology and security-related issues and has worked at Biztech2.com, Dataquest and The Indian Express.




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