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What 2025 Holds For Data And Analytics: 8 Predictions

Jan 10, 2025 - forbes.com
The article discusses predictions for the data and analytics landscape in 2025, highlighting several key trends. It anticipates a decline in the number of chief data officers (CDOs) in private-sector companies due to challenges in operationalizing AI, with many CDO functions moving under CTOs. Despite these struggles, off-the-shelf large language model (LLM) adoption is expected to rise. The hype around data catalogs will peak, driven by Ole Olesen-Bagneux's work on the "meta grid," which aims to bridge structured and unstructured data. Additionally, there will be a growing focus on knowledge management practices, particularly through retrieval-augmented generation (RAG) patterns that enhance LLM accuracy.

The article also predicts an increase in AI use for data management, despite CDOs' difficulties with GenAI. Data products are expected to decline in popularity due to their limited business value, while data fabric will gain momentum, especially with Microsoft's continued investments. AI governance will remain a hot topic, though practical implementation will be elusive. Sustainability in data will grow in Europe, but energy consumption issues in North American data centers will be largely overlooked. The article concludes with recommendations for data leaders to quantify business value, explore knowledge management, understand RAG patterns, and integrate GenAI for efficiency.

Key takeaways:

  • The number of chief data officers (CDOs) in private-sector companies is expected to decrease due to challenges in operationalizing AI.
  • Data catalog hype will increase, with a focus on bridging structured and unstructured data through next-gen data catalogs like the "meta grid."
  • There will be a growing awareness of knowledge management practices, driven by the popularity of retrieval-augmented generation (RAG) patterns that improve LLM accuracy.
  • AI governance will remain a hot topic, but there will be challenges in defining and implementing specific governance policies and rules at scale.
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