ETL Services for E-commerce: From Webshop to Data Warehouse

Your webshop generates thousands of data points daily. Orders, customer behavior, inventory changes, marketing results. But where does that data go? In many e-commerce companies, valuable information remains locked in separate systems. ETL changes that.

What is ETL?

ETL stands for Extract, Transform, Load — the three steps to get data from one place to another.

Extract: Retrieve data from source systems. Think of your Shopify orders, Google Analytics sessions, or Lightspeed inventory.

Transform: Clean and structure data. Standardize date formats, remove duplicates, add calculations.

Load: Load data into your destination system. Usually a data warehouse like BigQuery, Snowflake, or Redshift.

Sounds simple. In practice, it is — if you use the right tools.

Why E-commerce Companies Need ETL

“We just export to Excel.” Sound familiar? It works — until it doesn’t.

The Problem with Manual Exports

• Time-consuming: Manually exporting data every week costs hours
• Error-prone: Copy-paste mistakes are inevitable
• Not real-time: You’re always looking at outdated data
• Not scalable: More products = more exports = more chaos

What ETL Solves

With automated ETL pipelines:

• Data flows automatically from source to destination
• Updates are near real-time (often hourly or faster)
• Historical data is preserved for trend analysis
• One central location for all your data

The result? Decisions based on current, complete data instead of gut feeling.

Popular ETL Tools for E-commerce

The ETL tools market has exploded in recent years. Here are the main options:

Fivetran

The standard for managed ETL. Fivetran has 400+ pre-built connectors, including:

• Shopify
• WooCommerce
• Google Ads
• Meta Ads
• Klaviyo
• and virtually every other tool you use

Pros:

• Zero maintenance — Fivetran manages the connectors
• 5-minute setup for standard sources
• Automatic schema updates

Cons:

• Expensive at higher volumes (per-row pricing)
• Less flexible for custom transformations

Best for: Companies wanting to start quickly without technical expertise.

Airbyte

Open-source alternative. Self-hosted or cloud, with 300+ connectors.

Pros:

• Free when self-hosting
• Open-source community
• More flexible than Fivetran

Cons:

• Requires technical knowledge for self-hosting
• Cloud version is also paid

Best for: Teams with development capacity who want control.

Stitch (by Talend)

Simple and affordable. Fewer connectors, but the basics are covered.

Pros:

• Predictable pricing
• Easy interface

Cons:

• Fewer advanced features
• More limited connector library

Best for: Small to medium webshops with standard tooling.

Custom ETL

Build yourself with Python, Airflow, or dbt. Maximum flexibility.

Pros:

• Exactly what you need
• No vendor lock-in
• Cost-efficient at high volumes

Cons:

• Requires developers
• Maintenance is your responsibility

Best for: Larger organizations with dedicated data teams.

From Shopify to Data Warehouse

Let’s get concrete. You have a Shopify webshop and want data in BigQuery.

The Components

• Source: Shopify (orders, products, customers)
• ETL Tool: Fivetran or Airbyte
• Data Warehouse: Google BigQuery
• Transformation: dbt (data build tool)
• Visualization: Looker Studio or Tableau

Step-by-Step

1. Shopify → ETL Tool Connect Shopify via OAuth. The tool automatically retrieves all relevant tables: orders, line_items, customers, products, inventory_levels.

2. ETL Tool → BigQuery Data is loaded into raw tables. Each table corresponds to a Shopify object.

3. Transformation with dbt This is where it gets interesting. With dbt, you build models that:

• Connect orders to marketing attribution
• Calculate CLV (Customer Lifetime Value)
• Aggregate product performance metrics
• Prepare cohort analyses

4. BigQuery → Dashboard Looker Studio connects directly to BigQuery. Build dashboards for:

• Daily revenue and orders
• Product performance
• Customer segmentation
• Marketing ROI per channel

Timeline

With a tool like Fivetran:

• Day 1: Enable Shopify connector
• Day 2: BigQuery tables populate
• Day 3-5: Build dbt models
• Day 5-7: Dashboards live

A fully working data pipeline in a week. Not a months-long project.

ETL vs ELT: What Fits You?

You also see “ELT” these days — Extract, Load, Transform. What’s the difference?

ETL (Traditional)

1. Extract
2. Transform (in the ETL tool)
3. Load

Data is transformed before it enters the warehouse.

ELT (Modern)

1. Extract
2. Load
3. Transform (in the warehouse)

Data is loaded “raw” first, transformation happens afterward with tools like dbt.

When to Use Which?

Choose ETL if:

• You have limited warehouse capacity
• Data volume is low
• You lack SQL/dbt expertise

Choose ELT if:

• You use a modern cloud warehouse (BigQuery, Snowflake)
• Data volume is high
• You want flexibility in transformations

For most e-commerce companies, ELT is the better choice. Cloud warehouses have become cheap, and the flexibility of transform-after-load is significant.

Self-service vs Managed ETL

The next question: do it yourself or have it managed?

Self-service

You buy a tool (Fivetran, Airbyte) and manage yourself:

• Enable connectors
• Schema mapping
• Error handling
• Write dbt models

Pros:

• Full control
• Cheaper with good internal knowledge

Cons:

• Requires technical capacity
• Problems are your responsibility

Managed ETL

A partner manages the complete stack:

• Setup and configuration
• Monitoring and error handling
• Transformations and models
• Dashboard development

Pros:

• No technical knowledge needed
• Fast time-to-value
• Someone else solves problems

Cons:

• Higher costs
• Less direct control

Our Recommendation

For SMB e-commerce companies with limited technical capacity: start managed. Let a partner set up the foundation. Take over later as your team grows.

Getting Started

Ready to streamline your data? Here are your options:

Do it yourself:

1. Choose an ETL tool (Fivetran for ease, Airbyte for control)
2. Start with one data source (e.g., your webshop)
3. Connect to BigQuery (free tier is often enough)
4. Build your first dashboard

Need help? At Duxly, we help e-commerce companies with complete data integration — from Shopify/Lightspeed to working dashboards. Contact us for a no-obligation conversation.

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ETL doesn’t have to be rocket science. With the right tools and approach, you’ll have a working data pipeline within weeks. The question isn’t whether you need this — but when you start.