Dataiku
PulseAugur coverage of Dataiku — every cluster mentioning Dataiku across labs, papers, and developer communities, ranked by signal.
5 day(s) with sentiment data
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AI adoption challenge: Change management over new models
Sophie Dionnet of Dataiku highlighted that the primary obstacle in enterprise AI adoption is not the technology itself, but the difficulty of change management. She noted that organizations often get caught up in the ex…
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Dataiku's Sophie Dionnet on AI value: People, orchestration, and governance are key
Sophie Dionnet, from Dataiku, discussed the critical factors for successful enterprise AI implementation. She emphasized that people, effective orchestration, and governance that acts as an accelerator, rather than a hi…
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Dataiku executive outlines AI business value strategy: People, orchestration, governance
Sophie Dionnet of Dataiku discussed how to translate AI into tangible business value, emphasizing that the key lies not solely in technology but in people, orchestration, and robust governance for scalability. She highl…
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Dataiku expert outlines 3 keys to AI value: people, orchestration, governance
Sophie Dionnet of Dataiku discussed the essential components for deriving genuine value from AI in a recent podcast episode. She highlighted that successful AI implementation hinges on having the right people, effective…
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AI's 'gold rush' is about change, not just tech, says Dataiku expert
The rapid advancement of AI models is often compared to a gold rush, but the true difficulty lies not in the technology itself, but in implementing the necessary organizational changes. Sophie Dionnet from Dataiku empha…
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Big Tech's AI Infrastructure Spending Reaches $3 Trillion, Lacking ROI Visibility
Major technology companies are making substantial, often off-balance-sheet, financial commitments for AI infrastructure, totaling trillions of dollars. While these commitments secure future revenue for suppliers and ena…
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Dataiku expert outlines key AI success factors: people, orchestration, governance
Sophie Dionnet of Dataiku discussed the essential components for transforming AI into practical value. She highlighted the importance of having skilled personnel, efficient operational workflows, and scalable governance…
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Dataiku exec: Enterprise AI adoption hindered by change management, not tech
Sophie Dionnet of Dataiku suggests that the current enterprise AI enthusiasm, often termed a "gold rush," overlooks the practical challenges of implementation. She argues that the true difficulty lies not in the technol…
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AI's real challenge is adoption, not new models, says Dataiku exec
The true challenges in artificial intelligence lie not in the development of new models, but in the practical implementation and adaptation of existing AI technologies within organizations. Sophie Dionnet of Dataiku emp…
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Enterprise AI success hinges on discipline, not just new models
Sophie Dionnet of Dataiku emphasizes that organizations often do not need the absolute latest AI models to implement necessary changes. She suggests that the real challenge in enterprise AI lies in disciplined execution…
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Dataiku executive outlines AI value drivers: people, tech, governance
Sophie Dionnet of Dataiku discussed the key components for successfully implementing AI within an organization. She emphasized that true value from AI is derived from a combination of skilled people, effective technolog…
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Dataiku Platform Urged for Data Scientists Building AI/ML Pipelines
Dataiku is highlighted as a potentially overlooked platform for data scientists involved in building AI/ML pipelines. The article suggests that the importance of selecting the correct platform for these tasks is often u…
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Dataiku exec: AI adoption hinges on culture, not just new models
Sophie Dionnet of Dataiku emphasized that organizational changes often hinge on people, process, and culture rather than solely on adopting the latest AI models. She suggested that the focus on new AI technologies might…
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AI Value Hinges on People, Tools, and Governance, Not Just Models
Value derived from AI hinges on more than just the model itself, according to Sophie Dionnet of Dataiku. She emphasizes three critical components: individuals possessing both technical and business acumen, the effective…
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Humanitarian AI: Trust and Impact Over Efficiency, Says Singapore Red Cross
AI in humanitarian work should prioritize trust and impact over pure efficiency, according to Nur Hafiza Mutalif of the Singapore Red Cross. She emphasizes a "do no harm" principle, explaining that AI should not be trea…
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Dataiku's Sophie Dionnet: People, Orchestration, Governance Key to Enterprise AI Value
Sophie Dionnet from Dataiku, featured on the Analyse Podcast, discussed that the true value of enterprise AI stems not solely from the technology itself, but from a combination of factors. She emphasized the critical ro…
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CEOs admit they 'rent' AI, not own it, due to external control risks
CEOs are increasingly realizing they do not truly own the AI systems their companies rely on, despite claiming to drive AI strategy. A recent survey indicates that while 70% of CEOs believe they lead AI strategy, only 6…
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IPO market set to broaden beyond AI mega-deals in late 2026
The IPO market is poised for a significant expansion in the latter half of 2026, moving beyond the dominance of AI and semiconductor mega-deals. Following a strong first half bolstered by companies like SpaceX and SK Hy…
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CEOs shift AI focus from productivity to revenue amid vendor lock-in fears
CEOs are increasingly concerned about over-investing in AI, with revenue growth now surpassing productivity as the primary measure of success. A significant shift has occurred, as leaders now worry more about the risks …
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Bank Risk Intelligence Engine Relies on MLOps and Data Analytics Tools
This article details the daily tasks of a Risk Data Analytics professional within a modern bank, focusing on the MLOps pipeline. The role involves utilizing tools like Python, SQL, and Jupyter Notebooks to manage and an…