Big Data: Processing and Dimensions

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Related lectures (32)

Page 3 of 4

Distributed Computing: Challenges and Solutions

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

Data Cleaning Challenges: Optimizing Error Detection

Addresses challenges in data cleaning for analysis, proposing optimizations to reduce processing time.

Data Warehouses: Introduction and Challenges

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

Data Protection Laws in Switzerland

Covers Swiss data protection laws, including the Federal Data Protection Act and the roles defined in the legislation.

Data Modeling: Concepts and Applications

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

Data Wrangling with Hadoop: Storage Formats and Hive

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

Accelerating Data Analytics: Innovations in Post-Moore Era

Covers advancements in data analytics systems and the role of hardware-software co-design in enhancing performance in the Post-Moore era.

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: Intro to Pandas

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

Introduction to Spark Runtime Architecture

Introduces Apache Spark, covering its architecture, RDDs, transformations, actions, fault tolerance, deployment options, and practical exercises in Jupyter notebooks.