Data Modeling: Concepts and Applications

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Related lectures (32)

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Data Wrangling with Hive: Managing Big Data Efficiently

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

Handling Data: Data Models and Wrangling

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

Handling Data: Intro to Pandas

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

Data Wrangling with Hadoop

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

Data Modeling: Concepts and Applications

Introduces data modeling concepts, SQL usage, and Pandas library applications for efficient data processing.

Data Wrangling with Hadoop: Storage Formats and Hive

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

Knowledge Representation: Semantics and Data Structures

Explores knowledge representation, data structures, semantics, and the challenges of searching for data on the web.

Data Warehousing: Overview and Challenges

Introduces data warehousing fundamentals, challenges, and the innovative concept of a 'lakehouse'.

Real-time Intelligence: Data Challenges and Hardware Evolution

Explores data challenges and hardware evolution for real-time intelligence in the era of big data.

Relational Model: Basics

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