# Data-Learn/data-engineering

Getting Started with Data Enngineering

Repository: https://github.com/Data-Learn/data-engineering
Canonical: https://ross.abutalabs.com/products/data-engineering
Language: Python
License: MIT
License Family: permissive
Last push: 2025-04-20T18:40:30+00:00

## Health v2 (maintenance only)
Score: 40/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 17, release rhythm 35, longevity 100
- inputs: {"age_days": 2303, "days_push": 500, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1332, forks 576 (observed 2026-08-28T04:04:24.424946+00:00)

## What it is
Data Learn is a free open educational resource and course series teaching data engineering and analytics, covering BI tools, databases, ETL, SQL, cloud computing, and machine learning fundamentals. It is maintained by industry practitioners and includes video lessons, podcasts, and hands-on materials aimed at helping learners build careers in data roles.

## Use cases
- learn data engineering from scratch for free
- become a BI developer or analyst
- understand ETL tools and data warehousing
- prepare for a data engineer job interview
- get started with machine learning and data science
- transition careers into data analytics
- learn SQL and business intelligence basics
- study cloud data platforms hands-on

## When to choose
- you want a structured, free curriculum for data engineering fundamentals
- you prefer learning from experienced practitioners with real-world case studies
- you are a beginner with no prior data experience
- you want career guidance alongside technical training
- you learn better with video lessons and podcasts in Russian

## When to avoid
- you need an official certification or accredited credential
- you require advanced, cutting-edge data engineering topics beyond the fundamentals
- you cannot work with Russian-language materials
- you want a self-paced code-only reference rather than a guided course
- you need enterprise-grade support or SLAs

## Facets
- artifact type: learning-resource
- maturity: active
- function: etl, data-science, developer-tools
- domain: tutorials, education, data-science, big-data
- platform: cross-platform, python
- tags: data-engineering-course, free-course, russian-language, bi, sql, cloud-computing, career-development, podcast, beginner-friendly, analytics, data-engineering

## Member repositories
- Data-Learn/data-engineering (main) score 40

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:24.424946+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:44:56.271044+00:00, confidence not recorded.
  - readme: https://github.com/Data-Learn/data-engineering (fetched 2026-08-28T04:04:24.424946+00:00, sha 23d94c14caa5)
- Data as of 2026-08-30T08:39:29.467469+00:00.