Digital Transformation: Solutions and Data

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Related lectures (32)

Page 3 of 4

Stockage et transmission des données 1: introduction; besoin de structure

Discusses the importance of structuring data for efficient storage and retrieval.

Big Data: Processing and Dimensions

Explores Big Data generation, storage, processing, and dimensions, along with challenges in data analytics, cloud computing elasticity, and security.

Apache Spark Ecosystem: Basics and Operations

Provides an overview of the Apache Spark ecosystem, covering basics, operations, and key components.

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.

Integrating Scalable Data Storage and Map Reduce Processing with Hadoop

Covers the integration of scalable data storage and map reduce processing using Hadoop, including HDFS, Hive, Parquet, ORC, Spark, and HBase.

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.

Deep Learning: Principles and Applications

Covers the fundamentals of deep learning, including data, architecture, and ethical considerations in model deployment.

Headline Analysis: Language Impact & Success

Explores the influence of language on headline success through real-world data analysis and statistical testing.

Biomechanics: Velocity Analysis

Explores the analysis of velocity data in biomechanics using Excel for visualization and interpretation.

Introduction to Data Stream Processing

Covers the fundamentals of data stream processing, including real-time insights, industry applications, and practical exercises on Kafka and Spark Streaming.