Data Analyst Roadmap
Roadmap to become a data analyst
These are the roadmap to become a data analyst:
Foundation Skills:
Strengthen Mathematics: Focus on statistics relevant to data analysis
Descriptive Statistics
Inferential Statistics: Hypothesis Testing,..
💡 Book Reference: https://drive.google.com/file/d/142tPq9LRyu3cU9D2rNz301gdOQPotHVJ/view?usp=sharing
Excel Basics: Master fundamental Excel function and formulas.
SQL Proficiency:
Learn SQL Basics: Understand SELECT statements, Joins, and Filtering
Practice Database Queries: Work with database to retrieve and manipulate data
Excel Advanced Techniques:
Data Cleaning in Excel: Learn to handle missing data and outliers, duplicated data.
PivotTables and Pivot Charts: Master these powerful tools for data summarization.
Data Visualization with Excel:
Create Visualizations: Learn to build charts and graphs in Excel
Dashboard creation: Understand how to design effective dashboards.
Power BI Introduction:
Install and Explore Power BI: Familiarize yourself with the interface.
Import Data: Learn to import and transform data using Power Bl.
Power Bl Data Modeling:
*Relationships: Understand and establish relationships between tables.
DAX (Data Analysis Expressions): Learn the basics of DAX for calculations.
Advanced Power Bl Features:
Advanced Visualizations: Explore complex visualizations in Power BI.
A Custom Measures and Columns: Utilize DAX for customized data calculations.
Integration of Excel, SQL, and Power BI:
Importing Data from SQL to Power BI: Practice connecting and importing data.
Excel and Power Bl Integration: Learn how to use Excel data in Power BI.
Python for Data Analyst:
Basic Syntax of Python
Exploratory Data Analysis: Understand how important of EDA and how to do EDA:
💡 Reference: https://www.kaggle.com/discussions/general/329404
💡Reference of EDA: https://www.kaggle.com/code/chemistahmedkamel/eda-diabetes-prediction-with-lowest-error/notebook
NumPy Array
Jupyter Notebook
Data Loading, Storage, File Format
Data Cleansing and Preparation with Pandas
Data Wrangling: Join, Combine, and Reshape
Plotting and Visualization,
Time Series
Machine Learning
💡Book References: https://drive.google.com/file/d/1oY5GWO8YxWt1cPJdXWn-aIHQxvhMn7j-/view?usp=sharing
Case Study: Try real world case studies project with examples
Walmart:
dataset: https://www.kaggle.com/datasets/yasserh/walmart-dataset
Apply Prediction: https://www.kaggle.com/code/yasserh/walmart-sales-prediction-best-ml-algorithms
Netflix:
dataset: https://www.kaggle.com/datasets/shivamb/netflix-shows
Visualization, Recommendation, EDA: https://www.kaggle.com/code/niharika41298/netflix-visualizations-recommendation-eda
YouTube channel for machine learning project with deployment: https://www.youtube.com/playlist?list=PLeo1K3hjS3uu7clOTtwsp94PcHbzqpAdg
Project Cover:
Data cleaning
Feature engineering
Model Building
Building Website for price prediction
Deployment to AWS
Business Intelligence Best Practices:
Data Storytelling: Develop skills in presenting insights effectively.
Performance Optimization: Optimize reports and dashboards for efficiency.
Build Portfolio
Showcase Excel Projects: Highlight your data analysis skills using Excel.
Power BI Projects: Feature Power BI dashboards and reports in your portfolio.
Showcase Data Analysis Project with Python
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