All roadmapsRoadmap · 2026

Data Analytics Roadmap 2026

The complete Data Analytics roadmap in 7 stages — Foundational Skills, Data Manipulation & Analysis, Data Visualization & Reporting, Advanced Analytics & Machine Learning Basics, Cloud & Big Data Fundamentals, Projects & Portfolio Building and Job Preparation & Interview Skills. Open any stage in the mind map to see the topics and tools inside it, or download the whole roadmap as an image.

Mind map

Data Analytics Roadmap

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Data Analytics roadmap, stage by stage

01Foundational Skills
- Mathematics & Statistics
  - Descriptive Statistics
  - Inferential Statistics
  - Probability Theory
  - Linear Algebra Basics
- Programming Fundamentals
  - Variables and Data Types
  - Control Flow Statements
  - Functions and Modules
  - Object-Oriented Programming Basics
- Database Fundamentals
  - Relational Databases Concepts
  - Database Design Principles
  - SQL Query Basics
  - NoSQL Databases Overview
- Spreadsheet Software
  - Excel Functions
  - Pivot Tables
  - Data Validation
  - Google Sheets
02Data Manipulation & Analysis
- SQL for Data Analysis
  - SELECT, FROM, WHERE, GROUP BY
  - JOINs and Subqueries
  - Window Functions
  - Database Management Systems (PostgreSQL, MySQL)
- Python for Data Analysis
  - Pandas DataFrames
  - NumPy Arrays
  - Data Loading and Saving
  - Data Aggregation and Merging
- R for Data Analysis
  - Tidyverse Package
  - Data Frames in R
  - Data Import and Export
  - Data Transformation

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Data Cleaning & Preprocessing

Handling Missing Values
Outlier Detection
Data Type Conversion
Feature Engineering Basics

03Data Visualization & Reporting

Business Intelligence Tools
- Tableau Desktop
- Power BI
- Looker Studio
- Dashboard Design Principles
Python Visualization Libraries
- Matplotlib
- Seaborn
- Plotly / Dash
- Interactive Visualizations
R Visualization Libraries
- ggplot2
- Shiny for Web Apps
- Leaflet for Maps
Storytelling with Data
- Audience Understanding
- Narrative Structure
- Effective Chart Choice
- Presentation Skills

04Advanced Analytics & Machine Learning Basics

Statistical Modeling
- Regression Analysis
- Hypothesis Testing
- ANOVA
- Time Series Models (ARIMA)
Introduction to Machine Learning
- Supervised Learning Concepts
- Unsupervised Learning Concepts
- Model Evaluation Metrics
- Scikit-learn Basics
Time Series Analysis
- Stationarity
- ARIMA Models
- Forecasting Techniques
- Seasonal Decomposition

05Cloud & Big Data Fundamentals

Cloud Platforms Basics
- AWS S3, EC2
- Azure Blob Storage, VMs
- Google Cloud Storage, Compute Engine
- Cloud Data Services Overview
Big Data Concepts
- Hadoop Ecosystem Overview
- Spark Basics
- Distributed Computing
- Data Lakes vs Data Warehouses
Data Warehousing Concepts
- ETL/ELT Processes
- Star Schema, Snowflake Schema
- Dimensional Modeling
- Data Marts

06Projects & Portfolio Building

End-to-End Projects
- Real-world Datasets
- Problem Definition
- Solution Implementation
- Impact Measurement
Version Control
- Git Commands
- GitHub / GitLab
- Branching and Merging
Portfolio Presentation
- Project Documentation
- Interactive Dashboards
- Online Portfolio Website
- Storytelling of Projects

07Job Preparation & Interview Skills

Resume & Cover Letter
- Tailoring to Job Description
- Highlighting Achievements
- ATS Optimization
Behavioral Interview Prep
- STAR Method
- Common Questions Practice
- Company Research
Technical Interview Prep
- SQL Coding Challenges
- Python/R Coding Challenges
- Case Study Analysis
- Statistical Concepts Review
Networking & Job Search
- LinkedIn Optimization
- Informational Interviews
- Job Boards & Referrals
- Continuous Learning