Introduces semantic modelling through tabular data and RDF, covering relational databases, schema migration, future-proof schemata, SPARQL querying, and metaknowledge limitations.
Introduces the fundamentals of handling data, emphasizing the importance of Pandas and data modeling for effective analysis.
Introduces the Entity-Relationship model for designing databases with a focus on conceptual and relational aspects.
Covers data wrangling techniques using Hadoop, focusing on row versus column-oriented databases, popular storage formats, and HBase-Hive integration.
Covers Spark Data Frames, distributed collections of data organized into named columns, and the benefits of using them over RDDs.
