JOURNAL / DATA + CAREER
Ideas, guides & practical career notes
Practical notes on Data Analytics, interviews, career growth and building a smarter way of working.
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Weekly Data Analyst Practice Routine: A Simple System That Compounds
A practical weekly Data Analyst practice routine covering SQL, business analysis, dashboards, AI-assisted work, communication and career development.
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Data Analyst Portfolio System: Turn One Project Into Multiple Proof Points
Learn how to build a stronger Data Analyst portfolio by turning one substantial project into evidence for SQL, analytics, dashboards, communication and interviews.
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Data Analyst Job Search Tracker: What to Track Beyond Applications
Build a Data Analyst job search tracker that captures applications, requirements, evidence, interview feedback and skill gaps so you can improve the process.
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Data Analyst Learning Plan: What to Learn in Your Next 90 Days
A practical 90-day Data Analyst learning plan covering SQL, data analysis, dashboards, business thinking, AI-assisted workflows and portfolio evidence.
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The AI-Assisted Analyst Workflow: From Business Question to Decision
A complete AI-assisted analyst workflow from business question to decision: frame, prepare, build, verify, explain and systematize.
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AI for Python Data Analysis: What Analysts Should Automate and What They Should Check
Use AI with Python for data analysis without losing control of transformations. Check data types, filters, missing values, joins and output shape.
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How to Use AI to Write SQL Without Losing SQL Skills
Use AI to draft and debug SQL without losing SQL skills. This guide covers grain, joins, aggregation, validation and deliberate practice.
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10 AI Prompts Data Analysts Can Use Without Replacing Their Judgment
Ten useful AI prompt patterns for Data Analysts, with guidance on when to use them, what to verify, and how to avoid turning prompts…
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How to Use AI for Data Analysis Without Blindly Trusting the Answer
A verification-first workflow for using AI in data analysis: define context, inspect assumptions, test outputs, check edge cases and document decisions.
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Dashboard Storytelling: What a Data Analyst Should Put on the First Screen
Learn how Data Analysts can design dashboard first screens around decisions, KPI context, trends, drivers and clear storytelling instead of visual clutter.
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