Data Analysis Roadmap
A detailed roadmap for data analysis
Basic statistical concepts like mean, median, mode, variance, correlation, etc.
Python with libraries like Pandas, NumPy, Matplotlib or R for data analysis.
Skills for cleaning, transforming, and organizing data using libraries like Pandas.
Git is a version control system for tracking changes in source code. GitHub is a platform for hosting repositories and collaborating on projects.
Creating effective visualizations using libraries like Matplotlib, Seaborn, ggplot2, etc.
Querying and manipulating data stored in relational databases.
Statistical methods for testing hypotheses and making data-driven decisions.
Using Excel for data cleaning, analysis, and basic reporting.
Applying ML techniques for predictive analysis and pattern recognition.
Using tools like Tableau, Power BI for data visualization and reporting.
Using specialized statistical software for complex analysis.
Effectively communicating insights and findings to stakeholders.