Covers data wrangling techniques using Hadoop, focusing on row versus column-oriented databases, popular storage formats, and HBase-Hive integration.
Introduces fundamental concepts of data management, including data models, databases, and key tasks.
Introduces the fundamentals of handling data, emphasizing the importance of Pandas and data modeling for effective analysis.
Introduces the relational model, SQL, keys, integrity constraints, ER translation, weak entities, ISA hierarchies, and SQL vs. noSQL.
Covers the origins, properties, and types of NoSQL databases, focusing on MongoDB and the CAP theorem.
Covers Spark Data Frames, distributed collections of data organized into named columns, and the benefits of using them over RDDs.
Covers the overview of information systems, data modeling, managing data, and the distinction between data and information.
