Covers the fundamentals of database systems, including data modeling, information processing, and the challenges of managing large volumes of data.
Covers Spark Data Frames, distributed collections of data organized into named columns, and the benefits of using them over RDDs.
Covers the analysis of air pollution data, focusing on R basics, visualizing time series, and creating summaries of pollutant concentrations.
Explores storage management challenges in transitioning to data lakes, addressing software and hardware heterogeneity, unified storage design, and performance optimization.
Explores Big Data generation, storage, processing, and dimensions, along with challenges in data analytics, cloud computing elasticity, and security.
Explores cache memory design, hits, misses, and eviction policies in computer systems, emphasizing spatial and temporal locality.
