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2024 AI Strategy: Are You a Jellyfish or Flatworm Company?
Dan McCreary knows a thing or two about representing knowledge in a vast, complex organization. He built the world’s largest healthcare knowledge graph during his time as a distinguished engineer and founder of Optum’s Generative AI Center of Excellence. As your company maps out its 2024 AI strategy, McCreary’s unique
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Analytics Maturity Transition Guide: Stage 3 to 4
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2024 Predictions and Priorities: AI Edition
Join this powerhouse panel of IIA Experts where we explore emerging trends, technological shifts, and strategic considerations shaping AI strategy in 2024. This session will help you re-think old paradigms, cut through the AI noise, and plot pragmatic plans as you build your AI roadmap. Attendees who join this session
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Self-Service Analytics
If the dashboard ecosystem (i.e., Pulse) discussed in the last piece is the compass that guides strategy implementation and operations, ad hoc or exploratory analytics form the map of the ever-shifting business landscape used to evolve strategy and operations. The dashboard ecosystem streamlines and unifies decision-making by providing leaders at
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Knowledge Graphs Drastically Improve Accuracy of Large Language Models on Complex Data: New Research Proves
Natural language interfaces to databases have long been a holy grail of both industry and academia. Recently, advances in large language models (LLMs) like GPT-3 have brought this dream closer to reality. LLMs now have an impressive capacity to translate natural language questions into formal database queries. However, fundamental questions
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Why Business Intelligence Maturity Matters
The BI Sufficiency Problem For over a decade, IIA has assessed and evaluated the analytics maturity of hundreds of companies, guiding these enterprises in their transition to advanced analytics and AI. Recently, we closely examined a group of clients scoring below the midpoint of 3.0 on IIA's Analytics Maturity Assessment
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IIA’s Business Intelligence Maturity Framework
In the first installment of our BI maturity blog series, we explored why BI maturity matters and the achievements of BI-mature companies. We showed that BI insufficiency plays a key role in difficult transitions to advanced analytics and AI at the enterprise-level. In response to client challenges around BI—and getting
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Business Intelligence Maturity Market Study and Recommendations
Organizations today face an increasingly challenging business environment. Across industries, new companies and nimble competitors are taking advantage of advanced analytics and AI and disrupting traditional business models and markets. Cloud computing and open source have caused fundamental changes in business intelligence (BI) and analytics infrastructure, enabling the introduction of
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AI Leadership Dilemma: Finding a Home on the Org Chart
When headlines announcing the word of the year hit the news (hello “authentic,” hello “rizz”), I was surprised “AI” didn’t make the cut. Artificial intelligence has obviously been a major topic among the data and analytics professionals IIA interacts with, but it’s also been a major topic everywhere. A natural
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Leading the Expedition
We have talked about a great many things in this series: the changing business landscape and the need to accelerate our analytics and AI journey, the operating model and entrepreneurial mindset that makes this possible, how to get started, and the platform, frameworks, and technology that will enable the journey.