Topics
Agentic Analytics in Supply Chain
Time Series Analysis
Agentic Flows
Market Access Analytics
Analytics Stack
Search-Driven Analytics
Analytics Copilot
Knowledge Layer
Semantic Search in Analytics
AI Orchestration
Agent Composer
Insight Graph
Guided Insights
Agentic Analytics
Business Metrics
AI Agents
Prescriptive Analytics
Predictive Analytics
Natural Language Generation (NLG)
Insight Narratives
Natural Language Query (NLQ)
Workflow Automation
Data Integration
Business Logic
Data Preparation
Semantic Layer
Federated Data Governance
Data Products
Data Fabric
API Integrations
Data Democratization
White-Label BI
Ad Hoc Analysis
AI Analytics
Business Intelligence (BI)
Conversational Analytics
Zero Data Movement
Data Lakehouse
Cloud Data Warehouse
Live Query / Federated Query
In-Memory Query Engine
ETL / ELT (Extract, Transform, Load)
Data Transformation
Data Pipeline
Data Modeling
Data Mesh
Embedded Analytics
Search-Driven Analytics
Decision Intelligence
Data Storytelling
Dashboard
KPI (Key Performance Indicator)
Exploratory Data Analysis (EDA)
Self-Service Analytics

ETL / ELT (Extract, Transform, Load)

ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) are data integration methods for preparing data for analytics.

  • ETL transforms data before loading it into the warehouse.
  • ELT loads raw data first, then transforms it inside the warehouse—ideal for cloud-native architectures. Tellius supports both models, or bypasses them entirely with live querying for zero data movement.

ETL and ELT provide flexible strategies for delivering prepared data to analytics platforms. Choosing the right method—or bypassing both with live querying—can dramatically improve efficiency, cost, and speed.