... Employee productivity is not enough. If you want value from AI, you need to reengineer processes, change team structures, renegotiate contracts with providers or change insource/outsource labor mixes. But these pathways to value can vary greatly in effort. Join this session where you’ll learn about ...
Analyst(s): Hung LeHong
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... Successful data and analytics governance requires engagement across technical and business functions. Technical professionals should use best practices to engage, partner with, and continually assess their level of engagement with business teams to overcome common stakeholder reluctance factors. Insi ...
... The coming onslaught of AI agents will challenge traditional identity and access controls. AI leaders must collaborate with IAM program management to enhance machine identity controls, distinguishing between beneficial and malicious agents through dynamic, contextual, and real-time measures for both ...
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... Lakehouse, a design approach, combines the architecture and capabilities of a data warehouse and data lake. Data and analytics technical professionals can leverage this assessment to identify their use cases for the lakehouse and match those use cases to a vendor’s approach to the lakehouse. Overview ...
... Access Research Already a Gartner client? Log management is an important but undervalued tool when planning threat detection, investigation and response (TDIR) operations. Cybersecurity leaders must consider the adoption of log management for security operations when SIEM adoption is not feasible. Insi ...
... An AI portfolio should reflect the organization’s ambition for using artificial intelligence and align with its level of maturity in this area. CIOs and AI leaders should plan for the portfolio to follow the organization’s AI trajectory — progressing from internal, tactical projects to more external ...
... Unclear or misleading names for data artifacts create confusion and increase the chance of errors. This research provides data and analytics technical professionals with naming conventions that support AI use cases, engineering use cases and user-facing programs such as data literacy and data govern ...
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