Data Analytics Analysis: Data Preparation

A set of vocabulary flashcards based on key concepts in data preparation as discussed in the provided lecture notes.

Data Profiling

The process of investigating data quality and structure.

Extract-Transform-Load (ETL)

A process that involves extracting data, transforming it for analysis, and loading it into a data processing system.

Data Quality

Refers to the suitability of data for decision-making.

Data Structure

The organization of data to improve analytics and facilitate easy access.

Data Cleansing

The process of correcting or removing inaccuracies from data.

Data Completeness

A characteristic of data indicating that all necessary information is present for analysis.

Composite Column

A column that combines two or more characteristics, making it harder for analysis.

Single-Valued Column

A column where each cell contains one value describing one characteristic.

Flat Table

A table structure without subtotals or hierarchies, preferred for data analysis.

Star Schema

A data model that organizes data into fact and dimension tables for efficient analysis.

Fact Table

A table that stores quantitative data for analysis, typically containing business transaction data.

Dimension Table

A table that provides context to the data in a fact table, describing attributes related to the facts.

Data Integration

The process of connecting related data from various sources to provide a unified view.

Data Anomaly

A deviation from the expected pattern, indicating potential data quality issues.

Data Loading

The process of transferring cleaned and transformed data into the software for analysis.

Data Validation

The confirmation that data meets the required standards and is accurate.

Data Relationships

Connections between data points that help define how data elements relate to each other.

Data Imputation

The method of substituting estimated values for missing data.

Data Merging

The process of combining data elements or columns from different tables.