Radu Miclaus is a Senior Director in the Gartner Product Management team as part of the Technology and Service Provider Research and Advisory group. Radu covers topics relevant to Product Leaders and Managers for technology providers targeting customer experience, general analytics and BI (ABI), data science and machine learning. Radu assists technology customers with go-to-market strategy and messaging, product and roadmap planning, product development, life cycle management, competitive landscape, buyer dynamics and best practices for product leadership.
Radu has worked in the analytics and software space for over 15 years as an analyst, as an analytics sales engineering leader and in product management leadership at augmented BI vendor start-up as well as AI-powered search space. Based on past experience, Radu brings together technical skills related to AI/ML and infrastructure, analyst experience design, marketing and sales positioning and implementation best practices to address the Product Management persona needs.
In terms of specialization, Radu has experience in Customer Analytics applications, IOT, AI/ML Ops, Augmented BI, Search and Personalization engines across platforms like SAS, IBM, Salesforce Einstein, Lucidworks/SOLR and other various platforms. Radu is also a visiting lecturer at the Institute of Advanced Analytics at NC State University on subjects like analytics career planning and applications and analytics architecture and processes.
Presales Manager/ Principal Product Manager
Director of Product Management for AI applications
VP of Product
Analytics, BI and Data Science Solutions
Product/Service Organization and Leadership
Product/Service Design and Creation
Product/Service Introduction and Delivery
Product/Service Evolution and Management
M.S., Analytics, NC State University
MBA., Finance and Operations, University of Iowa
BS, Finance, University of Missouri
1What are the key trends in Analytics, BI and AI that will impact my business?
2Where are the fastest-growing segments and emerging opportunities in analytics and BI?
3How should I adapt my go-to-market strategy to respond to the market dynamics?
4What capabilities are end users looking for in analytics and BI?
5Competitive Landscape for Customer Analytics