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Premium Research Jun 2025
... overlooking the massive opportunity to use alternative data and composite AI, a key component of the AI race, to address important business problems. Product leaders need to invest in new data science methods and processes, along with alternative data, and create intelligent apps to outpace competitors ...

Analyst(s):   John Santoro   |   Balaji Abbabatulla   |   Jim Hare   |   Dennis Gaughan   |   Alys Woodward   |   Annette Zimmermann   |   Kevin Quinn   |   Eric Goodness
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Premium Research Aug 2025
... blockers such as fragmented workflows, knowledge silos and AI skills gaps contribute to AI project failures. Data and analytics leaders should embed generative AI tools to increase data science and machine learning workflow visibility, automate documentation and support upskilling. Overview Strategic ...

Analyst(s):   Diarmuid Curran   |   Priya Sundararaman   |   David Pidsley
Research Apr 2026
... Gartner client? HCLS CIOs must address strict privacy regulations that stall data sharing and AI innovation. Synthetic data offers a powerful opportunity to create compliant datasets. This strategic guide helps CIOs use synthetic data to enhance AI capabilities, maintain privacy, and drive operational efficiency ...

Analyst(s):   Saru Mehta   |   Jeff Smith
Premium Research Oct 2026
... This comparison plots 20 of the most prominent AI use cases for life science enterprises against value and feasibility. Life science CIOs can use this assessment to start a strategic conversation that helps guide investment decisions in this technology. Overview How to Use Use-Case Scoring Breakdown ...

Analyst(s):   Reuben Harwood   |   Animesh Gandhi   |   Jeff Smith   |   Michael Shanler   |   Evun Wyer
Research Nov 2025
... client? Data and analytics leaders are seeking cloud analytics databases to address the new demands for modern analytics, including AI and data science, alongside traditional analytics. This report showcases the capabilities of cloud analytics databases and reviews use cases, including enterprise data warehouse ...

Analyst(s):   Aaron Rosenbaum   |   Henry Cook   |   Xingyu Gu   |   Ramke Ramakrishnan   |   Masud Miraz
Premium Research Jun 2025
... AI leaders responsible for implementation of data science and machine learning can leverage the power of large language models with the robustness of knowledge graphs for fault-tolerant AI applications. These downloadable slides provide architecture guidance on a diverse set of design patterns for GraphRAG ...

Analyst(s):   Afraz Jaffri   |   Yogesh Bhatt
Premium Research Jun 2025
... Data science, ML and AI leaders who use AI engineering practices outperform peers across a variety of business and delivery metrics. Use this interactive chart to compare AI model performance across different metrics, by region, industry, organizational size and frequency of AI engineering use. Data ...

Analyst(s):   Carlie Idoine   |   Di Wang   |   Afraz Jaffri   |   Sumit Agarwal
Premium Research Jul 2025
... Use this tool to rate your GenAI strategy against top tech providers. Based on data science analysis of provider survey data, the tool identifies the key practices of leading AI providers to help tech CEOs benchmark their readiness, prioritize investments and gain a competitive edge. When to Use Directions ...

Analyst(s):   Vuk Janosevic
Webinar On-Demand
... Organizations increasingly recognize the potential of data and analytics to drive transformation, but scaling these capabilities requires an organizational model that balances agility with consistency. As demand grows, D&A leaders face challenges such as skills shortages, strained capacity and rising ...

Analyst(s):   Jorgen Heizenberg
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