Understand the Basics⦁ Learn what data analytics is & key roles (analyst, scientist, engineer)
⦁ Know the types: descriptive, diagnostic, predictive, prescriptive
⦁ Explore the data analytics lifecycle
Learn Excel / Google Sheets⦁ Master formulas, pivot tables, VLOOKUP/XLOOKUP
⦁ Clean data, create charts & dashboards
⦁ Automate with basic macros
Learn SQL⦁ Understand SELECT, WHERE, GROUP BY, JOINs
⦁ Practice window functions (RANK, LAG, LEAD)
⦁ Use platforms like PostgreSQL or MySQL
Learn Python (for Analytics)⦁ Use Pandas for data manipulation
⦁ Use NumPy, Matplotlib, Seaborn for analysis & viz
⦁ Load, clean, and explore datasets
Master Data Visualization Tools⦁ Learn Power BI or Tableau
⦁ Build dashboards, use filters, slicers, DAX/calculated fields
⦁ Tell data stories visually
Work on Real Projects⦁ Sales analysis
⦁ Customer churn prediction
⦁ Marketing campaign analysis
⦁ EDA on public datasets
Learn Basic Stats & Business Math⦁ Mean, median, standard deviation, distributions
⦁ Correlation, regression, hypothesis testing
⦁ A/B testing, ROI, KPIs
Version Control & Portfolio⦁ Use Git/GitHub to share your projects
⦁ Document with Jupyter Notebooks or Markdown
⦁ Create a portfolio site or Notion page
Learn Dashboarding & Reporting⦁ Automate reports with Python, SQL jobs
⦁ Build scheduled dashboards with Power BI / Looker Studio
Apply for Jobs / Freelance Gigs⦁ Analyst roles, internships, freelance projects
⦁ Tailor your resume to highlight tools & projects
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