Data Integration and Visualization Project This project aims to streamline the process of data integration, analysis, and visualization by merging data from two Excel files, uploading the combined dataset into a SQL database, and creating interactive dashboards in Tableau.

Overview: The project consists of the following steps:

Data Merge: Two separate Excel files containing relevant data are merged into a single dataset using Python or any preferred tool for data manipulation.

Data Upload: The merged dataset is uploaded into a SQL database for storage and further analysis. This step ensures data centralization and facilitates efficient querying and retrieval.

Data Analysis: SQL queries are written to extract meaningful insights and perform data analysis tasks such as aggregations, filtering, and joins. This allows for in-depth exploration of the dataset and extraction of valuable business insights.

Dashboard Creation: Interactive dashboards are created in Tableau to visualize key metrics, trends, and patterns within the data. Various visualization techniques such as charts, graphs, and maps are utilized to present the findings in a clear and intuitive manner.

Key Features: Data Integration: Merge disparate datasets to create a unified view of the data. Data Storage: Store the integrated dataset in a SQL database for efficient data management. Data Analysis: Perform advanced data analysis using SQL queries to extract insights. Dashboard Visualization: Create visually appealing and interactive dashboards in Tableau to present key findings and trends. Benefits: Streamlined Workflow: Automate the process of data integration, analysis, and visualization to save time and resources. Actionable Insights: Gain valuable insights from the data to drive informed decision-making and strategic planning. Enhanced Visualization: Communicate insights effectively through interactive and visually appealing dashboards in Tableau. Future Enhancements: Real-time Data Integration: Implement real-time data integration capabilities to keep the dashboard up-to-date with the latest data. Predictive Analytics: Incorporate predictive analytics models to forecast future trends and outcomes based on historical data. User Collaboration: Enable collaboration and data sharing among users by deploying the dashboard to Tableau Server or Tableau Online.