What is ETL?

Extract – Transform – Load explained for modern data teams

TL;DR

ETL is the three‑step process that turns raw, siloed data into analytics‑ready gold.
Extract data from any source → Transform it into the right shape → Load it where your users (or apps) live.

ETL Workflow Diagram

Why do we still talk about ETL in 2025?

Data volumes keep doubling, formats keep multiplying, and business leaders still want answers now. Automating ETL:

slashes manual data wrangling time
enforces repeatable, documented pipelines
feeds BI dashboards, AI models, and downstream apps with clean, trusted data

In short: no ETL, no reliable insights.

The three steps at a glance

Step	What happens	Typical MapForce features
Extract	Connect to databases, SaaS APIs, files (CSV, JSON, XML, PDF, EDI…), log streams, NoSQL stores…	100+ built‑in connectors; one price – no extra “connector fees”
Transform	Filter, join, cleanse, pivot, aggregate, enrich, validate, convert data types & encodings	Graphical drag‑&‑drop mapping, visual function builder, AI‑assisted mapping
Load	Write to relational DBs, data warehouses/lakes, APIs, files, message queues, etc.	Parallel execution, bulk inserts, MapForce Server for high‑volume automation

ETL or ELT – which one and why?

Cloud warehouses make ELT fashionable, but the core questions haven’t changed:

Data gravity – Does it make sense (cost, latency) to land raw data first?
Compliance – Do regulations require data to be filtered/masked before it leaves an origin system?
Compute costs – Will heavy transforms blow up your warehouse bill?

A modern tool like MapForce supports both patterns, so you can pick per pipeline.

See ETL in action – free video series

Short, task‑oriented videos walk through:

CSV → Database mappings
XML ↔ JSON conversions
PDF table extraction
AI‑ready data preparation
…and more – all without hand‑coding.

Next steps

Ready to ditch fragile scripts and spreadsheets?

Try MapForce free for 30 days

And build your first ETL pipeline in minutes.