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Data, big data, clouds and IoT
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Related lectures (32)
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Data: Clouds and Things
Covers the fundamentals of data, cloud storage, and the Internet of Things.
Data Wrangling with Hive: Managing Big Data Efficiently
Covers data wrangling techniques using Apache Hive for efficient big data management.
Distributed Information Systems: Overview and Models
Covers Distributed Information Systems, key tasks, methods, projects, evaluation, and exam support.
Introduction to Database Systems
Covers the basics of database systems, including data modeling, DBMS, data independence, and the course overview.
Data Wrangling with Hadoop
Covers data wrangling techniques using Hadoop, focusing on row versus column-oriented databases, popular storage formats, and HBase-Hive integration.
Model Representation: Structures and Functions
Covers the representation of mathematical models, functions, and data structures in information systems.
General Introduction to Big Data
Covers data science tools, Hadoop, Spark, data lake ecosystems, CAP theorem, batch vs. stream processing, HDFS, Hive, Parquet, ORC, and MapReduce architecture.
Data Modeling: Concepts and Applications
Introduces data modeling concepts, SQL usage, and Pandas library applications for efficient data processing.
Knowledge Representation: Semantics and Data Structures
Explores knowledge representation, data structures, semantics, and the challenges of searching for data on the web.
Privacy: Threat Modeling and Differential Privacy
Explores the significance of privacy, risks of targeted advertising, and the concept of differential privacy.
