Dealing with different data sets, cleaning, manipulation, pre processing, then make data reporting and visualization.
Data Cleaning and Preprocessing: Cleaning and organizing the collected data to ensure its accuracy, completeness, and relevance. This may involve dealing with missing values, outliers, and formatting issues.
Data Analysis: Using statistical methods and tools to analyze the data and extract meaningful insights. This could involve running queries, creating visualizations, and applying various analytical techniques.
Data Visualization: Creating visual representations of the analyzed data, such as charts and graphs, to communicate findings to non-technical stakeholders and make complex information more understandable.
Reporting: Generating regular reports and dashboards to communicate key metrics, trends, and insights to relevant teams or management.
Identifying Patterns and Trends: Detecting patterns, trends, and correlations in the data that can be used to inform business decisions or strategies.
Data Interpretation: Interpreting the results of analyses and providing actionable recommendations based on the data.
Skills:
Excel
Power Bi
Tableau
SQL
Python