Lectures related to Data Warehousing and Decision Support

Data Warehouses and Decision Support Systems

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

Data Warehouses and Data Lakes

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

OLAP Queries and Optimizations

Covers OLAP queries, examples of comparisons, ranking, and optimizations for query performance.

Data Warehousing: Overview and Challenges

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

Data Wrangling: Structuring and Wrangling Issues

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

OLAP: Overview and Queries

Introduces OLAP concepts, schemas, queries, and optimizations for efficient data analysis.

Data Wrangling with Hive: Managing Big Data Efficiently

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

Data Warehouses: Introduction and Challenges

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

Views: Simplifying SQL Queries

Explores views in SQL, covering creation, materialization, maintenance, cube building, and top-k queries optimizations.

Data Warehouses and Decision Support Systems

Explores views in data warehouses, materialization tradeoffs, top-k queries optimizations, and the impact of column stores.

OLAP Data Model: Multidimensional and Relational Approaches

Explains OLAP data models, focusing on multidimensional and relational approaches.

Data Wrangling with Hadoop: Storage Formats and Hive

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

Digital Transformation: Solutions and Data

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

Probability and Statistics

Covers fundamental concepts in probability and statistics, emphasizing data analysis techniques and statistical modeling.

Data Lakes: Structure and Optimization

Explores data lakes, data structure, and optimization for effective querying.

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.

Statistics: Exploratory Data Analysis

Introduces statistics basics, including data analysis and probability theory, emphasizing central tendency, dispersion, and distribution shapes.

Data-Intensive Applications and Systems: Overview

Covers the exponential growth of data, challenges in processing technology, data variety, cleaning, approximate query processing, multi-query analytics, and hybrid transaction processing.

Distributed Computing: Challenges and Solutions

Explores challenges in distributed computing, data growth, and data types, emphasizing the battle against the three Vs in big data.

Data Wrangling with Hadoop: Advanced Techniques

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