Big Data: Processing and Management

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Related lectures (32)

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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.

Machine learning: Physics and Data

Delves into the intersection of physics and data in machine learning models, covering topics like atomic cluster expansion force fields and unsupervised learning.

Digital Transformation: Solutions and Data

Explores digital transformation opportunities, big data, analytics, and technology innovations in business and research.

Big Data Challenges: Scaling to Massive Data

Explores challenges of handling massive data in the era of big data, discussing solutions like MapReduce and Spark.

Data Warehousing: Overview and Challenges

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

Data Wrangling with Hadoop: Storage Formats and Hive

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

Data Characterization: PCA & Spike Sorting

Explores PCA for data simplification and Spike Sorting for shape identification.

Data Science Essentials

Covers the essentials of data science, including data handling, visualization, and analysis, emphasizing practical skills and active engagement.

Graph Mining: Social Networks and Data Analysis

Explores graph mining in social networks, covering data analysis and community detection.

Introduction to Data Stream Processing

Covers the fundamentals of data stream processing, including tools like Apache Storm and Kafka, key concepts like event time and window operations, and the challenges of stream processing.