Data Analytics Career 2-Year Roadmap: Excel, SQL, Python & AI
A step-by-step, execution-focused strategy to build a high-growth data analytics career over 24 months.
By Discover Talent Editorial Team
Phase 1: First 6 Months — Build Strong Foundations
- Master Excel: advanced formulas, pivot tables, dashboards.
- Understand key business metrics: Revenue, Margin, CAC, LTV, Churn.
- Practice structured problem-solving weekly.
- Start immediately — consistency compounds.
Phase 2: 6–12 Months — Move Beyond Basics
- Learn SQL to work directly with datasets.
- Build interactive dashboards and reporting systems.
- Gain hands-on experience through internships or live projects.
- Create a results-driven portfolio — impact over resume.
Phase 3: 1–2 Years — Strategic Growth & Acceleration
- Learn Python for analytics and automation.
- Understand AI fundamentals and business applications.
- Automate workflows to improve efficiency.
- Work on cross-functional strategic initiatives.
Why This Roadmap Works
Skills compound when applied consistently. A strong portfolio demonstrating measurable business impact will always outperform certifications alone. This structured timeline ensures progressive capability development aligned with modern analytics and AI-driven business needs.
Watch the Original YouTube Short
https://youtube.com/shorts/M9m5w4w6nJk
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