Introduction
• Introduction to the Big Data
Database
• Introduction to databases: E-R models, SQL
• Distributed query evaluation, NoSQL databases, graph databases
Big data methods
• Programming frameworks: MapReduce/Hadoop, Spark
Data mining
• Association Analysis
• Clustering
• Graph Analytics (centrality measures, scale-free/Power-law graphs, small world phenomenon, uncertain graphs)
• Similarity and diversity search
Lab & tools
• tools and methodologies for collecting, processing, visualizing and analyzing large amounts of data (Big Data).
o extract unstructured data from web (import.io, kimono, etc.)
o manage and manipulate data in tabular format (google spreadsheet, excel, etc.)
o explore and present static data (RAWGraphs, Gephi, illustrator, etc.)
o explore and build interactive data visualizations (Tableau Public, Carto)