Catalog
concept#Data#Analytics#Data Processing

Extract, Load, Transform (ELT)

A data processing method where data is extracted from various sources, loaded, and then transformed.

ELT is an approach to data integration that allows for efficient processing of large volumes of data.
Established
Medium

Classification

  • Medium
  • Technical
  • Architectural
  • Advanced

Technical context

DatabasesCloud ServicesAnalytics Tools

Principles & goals

Improve Data LearningOffer FlexibilityEnable Real-Time Analytics
Build
Enterprise, Domain

Use cases & scenarios

Compromises

  • Data Integrity Risks
  • High Resource Costs
  • Data Loss During Migration
  • Regularly review data sources.
  • Create documentation for processes.
  • Enable automation for frequent tasks.

I/O & resources

  • Identify Data Sources
  • Set Access Rights
  • Check System Configuration
  • Transformed Data
  • Analytical Insights
  • Real-Time Reporting

Description

ELT is an approach to data integration that allows for efficient processing of large volumes of data. After loading the data into a target system, the transformation occurs, providing flexibility in analysis and reporting.

  • Increased Data Availability
  • Better Decision-Making
  • Cost Efficiency

  • Complexity in Implementation
  • Dependency on Infrastructure
  • Potential Performance Issues

  • Data Load Time

    Time taken to load data into the target system.

  • Data Quality Assessment

    Assessment of the integrity and accuracy of the loaded data.

  • System Availability

    Availability rate of the involved systems during data processing.

Data Transfer in a Large Retailer

A large retailer uses ELT to aggregate sales data daily.

Financial Data Analysis

A financial service provider uses ELT to analyze market trends.

Data Integration for an E-commerce Company

An e-commerce company integrates data from various sales platforms.

1

Analyze data sources.

2

Perform preparatory actions.

3

Implement ELT process.

⚠️ Technical debt & bottlenecks

  • Outdated Technologies
  • Lack of Documentation
  • Missing Best Practices
Infrastructure DependencyPerformance LimitationsComplex Data Structures
  • Storing Data Without Transformation
  • Using Unauthorized Data Sources
  • Skipping Required Steps in the Process
  • Faulty Data Integration
  • Lack of Testing Before Production
  • Unrealistic Timelines for Implementation
Database ManagementData AnalysisETL Tools Knowledge
Growing Data VolumesIncreasing Data Analysis RequirementsNeed for Real-Time Processing
  • Operating System Dependent Services
  • Compliance Requirements
  • Data Format Standards