# abhishek-ch/around-dataengineering

A Data Engineering & Machine Learning Knowledge Hub

Repository: https://github.com/abhishek-ch/around-dataengineering
Canonical: https://ross.abutalabs.com/products/around-dataengineering
Language: Python
License Family: other
Topics: data-engineering, machine-learning, airflow, datascience, spark, mlops, devops, infrastructure
Last push: 2024-02-02T13:09:13+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2175, "days_push": 943, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1145, forks 222 (observed 2026-08-28T04:03:45.536243+00:00)

## What it is
A curated knowledge hub of articles, notes, and sketchnotes covering data engineering and machine learning topics such as databases, Spark, Airflow, and MLOps. It is a reading/reference collection rather than runnable software.

## Use cases
- learn data engineering concepts
- find curated articles on databases and distributed systems
- study Spark and Kubernetes operations
- explore MLOps and data pipeline reading lists
- prepare for data engineering interviews

## When to choose
- you want curated reading material on data engineering and ML
- you need architecture deep-dives on databases like FoundationDB, CockroachDB, and Riak
- you are building a self-study path in data engineering

## When to avoid
- you need runnable code or production tooling
- you expect maintained software with a license and releases
- you need structured tutorials rather than link collections

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: documentation, developer-tools
- domain: machine-learning, big-data, tutorials, awesome-lists
- platform: cross-platform
- tags: data-engineering, machine-learning, knowledge-hub, curated-links, spark, airflow, mlops, databases

## Member repositories
- abhishek-ch/around-dataengineering (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:45.536243+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 2026-08-30T06:34:26.273807+00:00, confidence not recorded.
  - readme: https://github.com/abhishek-ch/around-dataengineering (fetched 2026-08-28T04:03:45.536243+00:00, sha 78ceeec6015e)
- Data as of 2026-08-30T08:39:29.467469+00:00.