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Data Cleaning
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Data Cleaning

Definition updated on November 2023

What is data cleaning?

Correcting or removing incomplete, duplicated, inaccurate, damaged, badly structured, or damaged data from a dataset is known as data cleaning. There are numerous ways for data to be duplicated or incorrectly labeled when merging multiple data sources.

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Multi-Dimensional Analysis
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Metadata Harvesting
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Machine Data
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Logical Data Model
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Legacy Data Integration
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Linked Data
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Lagrangian Data Analysis
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JSON Data Interchange Format
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In-Memory Computing
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Internet of Things (IoT) Data
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Information Theory
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Feature Extraction
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Indexing and Searching
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Incremental Learning
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Differential Privacy
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Graph Databases
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Federated Learning
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Extract, Load, Transform (ELT)
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Entity Resolution
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Document Storage
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Diagnostic Analytics
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Descriptive Analytics
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Data Visualization Tools
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Decision Support Systems
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Database Design
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Database Indexing
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Data Utilization
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Data Traffic Analysis
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Data Transformation Services
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Data Transmutation
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Data Taxonomy
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Data Tracing
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Data Subsetting
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Data Structuring
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Data Streaming
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Data Steward
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Data Serialization
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Data Semantics
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Data Science Platforms
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Data Retention
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Data Reconciliation
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Data Resilience
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Data Recovery
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Data Readiness Levels
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Data Refinement
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Data Registries
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Data Reduction
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Data Quality Assurance
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Data Orchestration
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Data Operations (DataOps)
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Data Obfuscation
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Data Literacy
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Data Discovery
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Data Curation
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Data Blending
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Data Migration
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Data Normalization
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Data Deduplication
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Data Profiling
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Data Mashup
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Data Enrichment
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Master Data Management
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Data Staging
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Data Cleansing
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Data Lifecycle Management
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Data Standards
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Quantitative Analysis
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Metadata Management
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Data Federation
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Knowledge Discovery
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Data Provenance
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Information Retrieval
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Data Marts
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Data Modeling
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