Lectures related to Data virtualization

Data Warehouses and Decision Support Systems

Explores data warehouses, decision support systems, OLAP, data lakes, multidimensional data models, and query optimizations.

Data Warehousing: Overview and Challenges

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

Data Virtualization: SmartDataLake

Explores data virtualization in SmartDataLake project, covering query optimization, storage tiering, and challenges in processing heterogeneous data.

Data Ingestion Layer: SmartDataLake

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

Data Management Challenges: Hardware and Query Optimization

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

SmartDataLake: Distributed Analytics over Heterogeneous Data

Discusses challenges in scalable analytics over heterogeneous Big Data and introduces SmartDataLake for efficient handling of raw data.

Data Virtualization Demo: SmartDataLake

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

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.

Big Data Ecosystems: Technologies and Challenges

Covers the fundamentals of big data ecosystems, focusing on technologies, challenges, and practical exercises with Hadoop's HDFS.

Data Warehouses and Data Lakes

Covers data warehouses, data lakes, OLTP vs. OLAP, data quality, and the Data Lakehouse concept.

Model Database Resolution

Covers model database resolution, hydrology, GIS, connections, transitions, and validation using various datasets.

Data Warehouses: Introduction and Challenges

Covers the introduction and challenges of data warehouses, including integrating data, managing metadata, and optimizing query performance.

Data Wrangling: Structuring and Wrangling Issues

Covers data wrangling stages, structuring techniques, and common issues in data preparation.

Knowledge Inference

Explores knowledge inference, embedding techniques, and schema matching in data integration.

Input/Output: Basics & Files

Introduces input/output operations in C++, including file handling and data formatting.

River Hydraulics and Modeling: Semi-Distributed Approach

Explores river hydraulics, modeling, and calibration using a semi-distributed approach for accurate forecasting and water resource management.