Data Modeling: Concepts and Applications

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Related lectures (32)

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Introduces the fundamentals of handling data, emphasizing the importance of Pandas and data modeling for effective analysis.

Data Wrangling with Hive: Managing Big Data Efficiently

Covers data wrangling techniques using Apache Hive for efficient big data management.

Data Modeling: Concepts and Applications

Explores data modeling concepts, SQL implementations, and practical applications in handling missing data.

Data Wrangling with Hadoop

Covers data wrangling techniques using Hadoop, focusing on row versus column-oriented databases, popular storage formats, and HBase-Hive integration.

Handling Data: Data Models and Wrangling

Explores data handling fundamentals, including models, sources, and wrangling, emphasizing the importance of understanding and addressing data problems.

Relational Model: Basics

Introduces the relational model, SQL, keys, integrity constraints, ER translation, weak entities, ISA hierarchies, and SQL vs. noSQL.

Data: Clouds and Things

Covers the fundamentals of data, cloud storage, and the Internet of Things.

Data, big data, clouds and IoT

Explores data representation, databases, cloud computing, and challenges in the cloud environment.

Data Wrangling with Hadoop: Storage Formats and Hive

Explores data wrangling with Hadoop, emphasizing storage formats and Hive for big data processing.

Database Management Systems: Fundamentals

Introduces the fundamentals of database management systems, covering relational model, storage options, data integrity, queries, and data manipulation languages.