ETL+ Extraction from All Data Sources

One can use their DataSelf solution to extract ALL of digital data into their BI and AI platforms.

Below are the primary data-extraction methods supported by DataSelf ETL+:

1. Automated ETL+ No-Code Extraction

ETL+ provides fully automated, no-code data extraction from 400+ data sources (click here for the list of ETL+ no-code sources).
This approach typically requires no programming to set up or maintain. ETL+ automatically pulls the data into your data warehouse and refreshes your analytics platforms (Power BI, Tableau, Excel, and others) on a scheduled basis or on demand.

2. Semi-Automated ETL+ Extraction (No-Code / Manual Pull)

Some data sources do not provide an API or automated extraction method but allow exports in formats such as Excel, JSON, or CSV. In these cases:

You manually download or export the data (e.g., weekly or monthly), and
ETL+ automates everything after the download, including ingestion, transformation, modeling, and refreshing downstream BI dashboards.

This is ideal when automation isn’t possible at the data-source level but efficiency is still needed in the BI pipeline.

3. Automated ETL+ API Integration (Coding Required)

For data sources that require custom API calls—often REST/GraphQL APIs that require C#, Python, or another language—users can develop or reuse their extraction scripts and run them from within ETL+ (scheduled or on demand).
This method allows ETL+ to orchestrate and monitor even complex or custom-built data pipelines.

4. ETL+ with Advanced or Unstructured Extraction Methods

Some data sources fall outside the categories above—for example:

Unstructured content like PDFs, emails, documents
Specialized systems lacking exports or APIs
AI-assisted extraction pipelines

These scenarios typically require custom logic or third-party extraction tools. ETL+ can incorporate those scripts or tools seamlessly, allowing them to run as part of an automated or on-demand ETL+ job sequence.