What's included

• Data Collection

  Gathering data from various sources relevant to the project or study.

• Data Cleaning

  Removing inaccuracies, duplicates, and irrelevant data to ensure quality.

• Data Exploration

  Examining the data to find patterns, outliers, and initial insights.

• Data Analysis

  Applying statistical or machine learning techniques to understand trends, relationships, and patterns.

• Data Interpretation

  Making sense of the analysis results to draw conclusions.

• Data Visualization

  Using graphical representations to communicate findings clearly.

• Reporting:

  Compiling insights, methodologies, and conclusions into a comprehensive report for stakeholders.