Data management

Related lectures (32)

Page 1 of 4

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

Explores the ETL process, data wrangling stages, and common issues.

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

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

Covers the introduction and challenges of data warehouses, including integrating data, managing metadata, and optimizing query performance.

Covers data wrangling stages, structuring techniques, and common issues in data preparation.

Covers the fundamentals of big data ecosystems, focusing on technologies, challenges, and practical exercises with Hadoop's HDFS.

Covers the process of data wrangling, focusing on transforming and preparing data for analysis.

Explores challenges in distributed computing, data growth, and data types, emphasizing the battle against the three Vs in big data.

Explores data warehouses, decision support systems, OLAP, data lakes, multidimensional data models, and query optimizations.