... The gap between what datascience wants to convey and what business stakeholders understand is hindering data-driven decision making. With data storytelling best practices, D&A leaders can effectively deliver insights to any stakeholder, thus demonstrating D&A’s business impact and investment value. ...
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... Unstructured data quality issues — such as fragmented metadata, inconsistent semantics, ROT, and data/model drift — all limit AI scalability. Address quality issues by improving governance, enriching metadata, early assessment of source quality, reusing existing content practices and strengthening cross-functional ...
... Generative AI for Synthetic Data Access one-minute insights on how to improve model outcomes Generative AI is currently in the spotlight with the release of ChatGPT, but it has already been making significant contributions to data and analytics (D&A) through synthetic data. This solution can help fill ...
... address AI-driven data hoarding and generation, cybersecurity leaders must deploy a pragmatic retention framework. This research outlines the implementation of risk-based retention policies with clear metrics that weigh risks against actual utility, to systematically retire obsolete data. Insights at a ...
Analyst(s): Stefan Dumitrescu | Nader Henein | Shadrock Roberts
... Inventory trend analysis reveals the importance of prioritizing value over stock turns. This research provides evidence by comparing five life science and industrial materials segments that inventory value as a percentage of revenue is the most appropriate financial performance indicator. Insights at ...
Analyst(s): Paul Lord | Corwin Hee | Maria Nieradka
... Access Insights Already a Gartner client? Life science supply chains remain in the early stages of agentic AI adoption. This research identifies three key implementation barriers and offers clear recommendations to help CSCOs build strong foundations and choose qualified partners for effective agentic ...
... enterprise, she outlines the critical shifts data and analytics leaders need to make now, from building trusted data and context foundations to rethinking workforce design, governance, and the role of AI agents in decision-making. You’ll learn: Why trusted data will become the primary sources of AI differentiation ...
... both changing and expanding the data engineering role. To capture the full value of this shift, D&A leaders must reskill data engineers to support AI-ready data products, promote AI literacy, empower decentralized teams and operationalize automated governance in data engineering workflows. Insights at ...
... This presentation features 70 use cases from the 2026 Gartner Eye on Innovation Awards in healthcare and life sciences. CIOs and other leaders can use these examples to inspire AI and technology innovation, address industry challenges, and achieve measurable results. How to Use This Presentation Gartner ...
Analyst(s): Jeff Smith | Lachezar Manasiev | Animesh Gandhi | Evun Wyer | Barry Runyon | Saru Mehta | Austynn Eubank | Anthony Mullen | Amanda Dall'Occhio | Faith Adams | Reuben Harwood | Connie Salgy | Laura Craft