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New here? Start with Career Paths: Data Analyst vs. Data Engineer (2026). Everything else on this hub is organised using the tier framework defined there: Junior, Mid-level, Senior+.
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Which track fits you, the 2026 AI-aware lens, and the tier framework.
IDEs, Git and Python environments: get set up once, properly.
AWS, GCP and Azure compared, and what's actually free (and what isn't).
SQL → Python → BI → dbt/GitHub → engineering fundamentals, by tier.
SQL → pipelines → orchestration → formats → modelling → quality, by tier.
Coding assistants, PR review, and using AI without losing your judgement.
Every free and open-source tool worth knowing, grouped by the problem it solves.
Fast lookups for terminal, Git, SQL and Python. No teaching, just the reference.
The jargon, decoded, in plain English.
Portfolio-worthy projects by tier, with what to actually write up.
SQL, stats, system design and behavioural interviews: frameworks, not scripts.
New content drops on TikTok and Instagram: @george_abi_ and @george_abi_tech. This hub grows alongside the content. If something here has helped, the best way to say thanks is to share it with one person who would find it useful.
Career Paths: Data Analyst vs. Data Engineer (2026)
Skill Guide: Data Analyst (2026)