... Industry cloud platforms are reshaping life science technology strategy, providing numerous benefits such as solution integration, automation and data interoperability with other systems. CIOs should use this research to help make the benefit case for industry cloud platform adoption. Overview Strategic ...
Analyst(s): Jeff Smith
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... Software engineering leaders considering alternatives for Jira, Confluence, Jira Service Management, Bamboo, and Crowd must build clear criteria to guide the selection of replacement options. On-premises or self-managed options are limited and disruptive to user workflows and AI adoption. Insights at ...
Analyst(s): Rich Doheny | Nikos Drakos | Bill Blosen | Thomas Murphy | Keith Mann
... Access Insights Already a Gartner client? Cloud security demands more than lift-and-shift migration. Organizations that embrace cloud-native controls and automation achieve stronger resilience than those clinging to legacy security models. Cybersecurity leaders must adopt a cloud-native security strat ...
Analyst(s): Esraa ElTahawy | Dale Koeppen | Charlie Winckless
... Operationalizing agentic AI is impossible when data quality, governance and usage requirements are not clearly defined. Data and analytics leaders must formalize expectations through data contracts, creating machine-enforceable commitments that certify the consistent delivery of data products for AI and analytics. ...
Analyst(s): Michele Launi | Thornton Craig | Rahael Cherian | Michael Simone | Robert Thanaraj
... Many CMOs know the enterprise AI data fabric is coming but have no plan to join it. The fabric is the infrastructure. Marketing’s data mesh is how marketing takes part. Productize your customer data, set your data contracts (the gives and gets), and field agentic AI to stay in the decision loop. Insights ...
... guidance on evolving their existing data management practices to support AI readiness. We summarize some of the leading practices and steps that data management practitioners can take to integrate and extend their existing architecture and data foundation to deliver data management for AI. Insights at a ...
... The effective deployment of data agents requires an understanding of core cost drivers, use cases and infrastructure demands. Data and analytics leaders should use this methodology to classify data agents by expected cost and value impact to prioritize their agentic data and analytics deployments for ...
... roles and expectations for a data quality program using a simple RACI matrix is challenging due to the complex dependencies and priorities of the stakeholders involved. Data and analytics leaders can use this RASCI matrix to set expectations and accountability for their data quality programs. When to Use ...
... Data and analytics leaders should use a plan on a page to support their data, analytics and AI strategic planning process. This tool helps to quickly summarize key information from the data, analytics and AI strategy and target operating model and generate a one-page executive summary. When to Use Directions ...
Analyst(s): Michael Gabbard | Alan D. Duncan | Antonia Roesler | Soyeb Barot | Jamie O'Brien