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Concept

Data cleansing

Related lectures (32)

Data Modeling: Concepts and Applications

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

Handling Data: Data Models and Wrangling

Explores data handling fundamentals, including models, sources, and wrangling, emphasizing the importance of understanding and addressing data problems.

General Introduction to Data Science

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

Digital Urban History: Lausanne Time Machine

Explores the digital urban history of Lausanne in 1832, focusing on data intersection, search engine creation, and profession classification.

Data Wrangling with Hive: Managing Big Data Efficiently

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

Building DH Portal: Data Platform for Researchers

Showcases Haeeun Kim's internship experience in enhancing researchers' data cleaning and organizing processes.

Data Wrangling and Analysis

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

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.

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.

Data Wrangling Techniques: HBase and Hive Integration

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

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.

Handling Data: Intro to Pandas

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

Data Cleaning Challenges: Optimizing Error Detection Log in to Mediaspace to watch this video

Addresses challenges in data cleaning for analysis, proposing optimizations to reduce processing time.

Feature Engineering: Polynomial Regression Log in to Mediaspace to watch this video

Covers fitting linear regression on features of the original predictors for flexible feature representation.

Data Wrangling: Structuring and Cleaning Data Log in to Mediaspace to watch this video

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

Data Wrangling: Transforming Data for Analysis Log in to Mediaspace to watch this video

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

Data Structuring: Intrarecord and Interrecord Techniques Log in to Mediaspace to watch this video

Covers data structuring techniques, error detection, and functional dependencies within records.