Lectures related to Accelerating Data Analytics: Innovations in Post-Moore Era

Advanced Spark Optimization Techniques: Managing Big Data

Discusses advanced Spark optimization techniques for managing big data efficiently, focusing on parallelization, shuffle operations, and memory management.

Data Wrangling with Hive: Managing Big Data Efficiently

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

Big Data Best Practices and Guidelines

Covers best practices and guidelines for big data, including data lakes, architecture, challenges, and technologies like Hadoop and Hive.

Cache Memory

Explores cache memory design, hits, misses, and eviction policies in computer systems, emphasizing spatial and temporal locality.

Data Wrangling Techniques: HBase and Hive Integration

Covers data wrangling techniques using HBase and Hive, focusing on integration and practical applications.

Data Virtualization Demo: SmartDataLake

Showcases a demo on adaptive data virtualization in SmartDataLake, focusing on assembling company profiles and executing join queries across datasets.

Water Consumption in Geneva

Explores water consumption data in Geneva, including charts on consumption and losses, available datasets, and data processing phases.

Introduction to Data Stream Processing: Concepts and Applications

Covers the principles of data stream processing and its applications in real-time data analysis.

Digital Transformation: Solutions and Data

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

Apache Spark Ecosystem: Basics and Operations

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

Data Management Challenges: Hardware and Query Optimization

Explores hardware changes, query optimization, workload distribution, and effective strategies for academia and work-life balance.

Handling Data: Intro to Pandas

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

Big Data: Processing and Dimensions

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

Introduction to R Programming for Genetics & Genomics

Introduces a course on Genetics & Genomics, focusing on R programming with interactive exercises.

Real-time Intelligence: Data Challenges and Hardware Evolution

Explores data challenges and hardware evolution for real-time intelligence in the era of big data.

Data Wrangling with Hadoop: Storage Formats and Hive

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

Analytics on Data at Rest and Data in Motion

Explores combining data at rest with data in motion, emphasizing the Lambda architecture complexities and quality assessment of streams and batches.

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Introduction to Data Stream Processing: Concepts and Applications

Covers data stream processing concepts, focusing on Apache Kafka and Spark Streaming integration, event time management, and project implementation guidelines.

Introduction to Applied Data Analysis

Introduces the Applied Data Analysis course at EPFL, covering a broad range of data analysis topics and emphasizing continuous learning in data science.