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Data Representations and Processing

Covers data representations, challenges of imbalanced data, and strategies for data normalization and cleaning.

Representativeness, Reliability, and Contribution

Discusses data quality evaluation, reliability, representativeness, and process contribution in Life Cycle Assessment.

Entity Resolution: Techniques and Applications

Explores entity resolution techniques for identifying and aggregating different entity profiles across datasets, covering challenges and solutions.

Transformations of Input or Output

Covers handling missing data, feature engineering, and output transformations in machine learning.

Data Wrangling with Hadoop: Advanced Techniques

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

Entity Resolution Techniques

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

Data Warehousing: Overview and Challenges

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

Data Wrangling Techniques: HBase and Hive Integration

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

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.

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.