Big Data and Stream Data Analysis at Politecnico di Milano
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This document discusses the work of Marco Brambilla and Emanuele Della Valle in analyzing big data. They are professors who specialize in data science, social media analysis, and stream computing. Their work involves collecting and fusing data from various sources, analyzing it using stream reasoning to gain real-time insights, and applying these insights in domains like smart cities, contact centers, and oil operations.
![[source: IBM, 2012]
Big Data dimensions
Marco Brambilla and Emanuele Della Valle - Big Data Analysis](https://image.slidesharecdn.com/bigdataanalysis-brambilla-dellavalle-161021094044/85/Big-Data-and-Stream-Data-Analysis-at-Politecnico-di-Milano-3-320.jpg)
Big Data and Stream Data Analysis at Politecnico di Milano
- 1. Big Data Analysis Marco Brambilla, Emanuele Della Valle @marcobrambi @manudellavalleData Science Lab
- 2. Who we are • Marco Brambilla • Associate Professor at Computer Science Dept. (DEIB) • Expert in data science, social media analysis, conceptual modeling • Inventor of IFML international standard for user interaction with data • Emanuele Della Valle • Assistant Professor at Computer Science Dept. (DEIB) • Expert in semantic technologies and stream computing • Brander of stream reasoning, tackling velocity and variety of Big Data • 15 years experience in research and industrial projects • Startuppers: fluxedo.com, webratio.com • R&D advisors: socialometers.com, semioty.com, ifml.org 2
- 3. [source: IBM, 2012] Big Data dimensions Marco Brambilla and Emanuele Della Valle - Big Data Analysis
- 7. Data Fusion Scenario • Social Media Data • Opinion mining • Telecommunications Data • WI-FI Log • IoT • 3D Cameras • Any other IoT enabled sensors • Possibly embedded in industrial productsMarco Brambilla and Emanuele Della Valle - Big Data Analysis
- 10. … and it’s just the beginning • CRM + IoT • User Engagement • Recommendation • Resource management • Predictive maintenance Company Object Customer Marco Brambilla and Emanuele Della Valle - Big Data Analysis
- 11. Stream Reasoning research Tame Variety and Velocity simultaneously Marco Brambilla and Emanuele Della Valle - Big Data Analysis TRADITIONAL APPROACH Data “in-motion” Data “in-motion” Registered analysis Insights “in-motion” Data put “at-rest” in DWH Analysis Analysis Insight PANOPTIQUE APPROACH Ontology + Mappings Traditional approach StreamReasoning
- 12. Paradigmatic change enabled by Stream Reasoning Tame Variety and Velocity simultaneously Marco Brambilla and Emanuele Della Valle - Big Data Analysis TRADITIONAL APPROACH Data “in-motion” Data “in-motion” Registered analysis Insights “in-motion” Data put “at-rest” in DWH Analysis Analysis Insight PANOPTIQUE APPROACH Ontology + Mappings Traditional approach StreamReasoning
- 13. Our Stream Reasoner Uses logical window Connects to a variety of data streams Real-time predictive and actionable insights Stream Reasoner for data "in-motion" (In-memory) Store data "at-rest" (distributed) post-hoc analysis optimizes joins
- 15. – Off-shore oil operations: – Smart Cities – Global Contact Center – Social networks At work with our partners Marco Brambilla and Emanuele Della Valle - Big Data Analysis
- 16. At work with our partners Marco Brambilla and Emanuele Della Valle - Big Data Analysis – Events: Fashion and Design – Utilities, Resources, Wholesale – Sharing Economy