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What is Data?

Data work is about turning raw information into useful decisions.

Typical questions in data roles:

  • What happened?
  • Why did it happen?
  • What is likely to happen next?
  • What should we do now?
  • Data Analyst: creates reports and dashboards, explains trends.
  • Data Engineer: builds pipelines and data infrastructure.
  • Data Scientist: builds models and experiments.

If you are just starting, Data Analyst is usually the most accessible entry point.

  1. SQL
    • Querying tables, joins, grouping, filtering.
  2. Spreadsheets
    • Fast analysis with formulas and pivot tables.
  3. Python (or R)
    • Basic data cleaning and analysis scripts.
  4. Data visualization
    • Build clear charts and dashboards.
  5. Statistics basics
    • Mean, median, variance, hypothesis basics.
  1. Month 1-2
    • SQL fundamentals and spreadsheet fluency.
  2. Month 3-4
    • Python basics, pandas, and small analysis projects.
  3. Month 5
    • Dashboard tools (Power BI, Tableau, or Looker Studio).
  4. Month 6
    • Build 2 portfolio projects and publish case studies.
  • Sales dashboard from public CSV data.
  • Customer churn analysis notebook.
  • Product KPI weekly report with SQL queries.
  • A/B test result summary and recommendation.
  • SQL databases: PostgreSQL, BigQuery, MySQL
  • Notebooks: Jupyter, Colab
  • BI tools: Power BI, Tableau, Looker Studio
  • Version control: Git and GitHub

Data is a strong path if you like analysis and decision-making. Start with SQL and one dashboard tool, then publish practical projects.