Programming & Scientific Computing · Databases & Data Engineering
Databases: Data quality, profiling, and cleaning — Statistical and algorithmic foundations
Public introduction · full guide in Eikos
Introduction
What this guide covers
Introduction Advanced Data Processing
Overview
Topics covered
- Introduction
- Quality, Profiling and Data Cleansing
- Formal dimensions of Data Quality
- Completeness
- Accuracy
- Consistency
Related concepts
Main connections
- Outliers & influence diagnostics
- Missing data & multiple imputation
- Mean & expected value
- Variance & standard deviation
- Median & robust location
- Maximum likelihood estimation
Compatible notation
Mathematical sample in LaTeX
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\text{Comp}(A_j) = \frac{1}{n}\sum_{i=1}^{n}\mathbb{1}[x_{ij} \notin \mathcal{M}]