Lectures related to Data mapping

Data Modeling: Concepts and Applications

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

Offers a comprehensive introduction to Data Science, covering Python, Numpy, Pandas, Matplotlib, and Scikit-learn, with a focus on practical exercises and collaborative work.

Data Wrangling: ETL Process and Wrangling Issues

Explores the ETL process, data wrangling stages, and common issues.

Data Wrangling: Transforming Data for Analysis

Covers the process of data wrangling, focusing on transforming and preparing data for analysis.

Data Ingestion Layer: SmartDataLake

Explores the data ingestion process in SmartDataLake, including datasets and the RAW platform.

Data Wrangling and Analysis

Covers a homework assignment on data wrangling and analysis using Python's pandas library for real-world datasets.

Data Wrangling with Hive: Managing Big Data Efficiently

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

Introduction to Data Stream Processing: Concepts and Applications

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

Data Science: Python for Engineers - Part II

Explores data wrangling, numerical data handling, and scientific visualization using Python for engineers.

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.

Real-time Intelligence: Data Challenges and Hardware Evolution

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

Architecture Trade-offs in a Planet-scale Queueing System

Explores the trade-offs in a planet-scale queueing system, emphasizing the importance of relaxing semantics to manage complexity.

Temporality and Entity Resolution

Explores challenges in data temporality and techniques for entity resolution.

Entity Resolution Techniques

Explores entity resolution techniques, data deduplication, similarity metrics, computational cost, blocking techniques, and scaling out similarity joins.

Data Wrangling with Hadoop: Advanced Techniques

Covers advanced data wrangling techniques using Hadoop, focusing on Hive and HBase integration.

Data formats and data wrangling with Hadoop

Explores Apache Hive for data warehousing, data formats, and partitioning, with practical exercises in querying and connecting to Hive.

Data Stream Processing: Apache Kafka and Spark

Covers data stream processing with Apache Kafka and Spark, including event time vs processing time, stream processing operations, and stream-stream joins.

Data Wrangling: Structuring and Cleaning Data

Explores data wrangling techniques, error detection, functional dependencies, denial constraints, and data temporality.

Data Wrangling Techniques: HBase and Hive Integration

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

Emerging Memory II

Explores challenges in memory hierarchies, TB-scale address spaces, and optimizing performance through near-memory processing.