With applications and devices constantly generating data it became necessary for organizations to re-architect their data pipelines and analytics platforms to cope with continuous analytics and real-time requirements. In this session will discuss common data architectures to handle both streaming and historical data and highlight emerging patterns.
- Common data architecture patterns
- Continuous analytics
- In-database machine learning
- Real-time analytics
Yassine Faihe is the Vertica Global Head of Field Engineering, helping customers to modernize their analytics capabilities and data pipelines. He has 25 years of industrial and academic experience, specializing in big data, data science and software architecture. Prior to that Yassine was a senior research scientist at Philips Research (NL) was leading a research program on adaptive systems. Yassine filed more than 15 patent applications among which 10 were granted as US Patents. He holds a master’s degree in engineering from the University of Mulhouse (F) and a Ph.D. in computer science from the University of Neuchâtel (CH).
Stage 1 | Data Strategy & Governance
Yassine Faihe – Global Director of Big Data and Analytics Sales Engineering | Vertica