This repository contains a series of Tableau projects designed to enhance data visualization and analysis skills using various datasets. The projects cover different aspects of Tableau, including table creation, data combining, filtering, creating visualizations, and developing dashboards.
Develop a Tableau dashboard using the Sample Superstore dataset with the following features:
- Two Planes: Left plane for company logo, interaction controls, filters; Right plane for dynamic visualizations, KPI cards.
- Metrics: Sales, Profit, Number of Orders (# Orders).
- Dynamic Visuals: Adjust based on selected metric with changing titles and tooltips.
- Interactive Filters: Options for year and region with a hide/display button.
- Consistent Top Products Display: Top 5 products based on the selected metric.
- Filter Actions: Category chart dynamically filters other visualizations.
- Clickable Logo: Redirects to the dashboard on Tableau Public.
- Trend Lines: Include average and trend lines where necessary.
###Dashboard Highlights
- Interactive Filters: Easily refine analysis by year and region.
- Dynamic Visualizations: Visuals adjust based on selected metrics (Sales, Profit, # Orders).
- Top Products Display: Consistent display of top 5 products regardless of filters.
- Filter Actions: Interactive category chart filters other visualizations dynamically.
- Trend Analysis: Inclusion of average and trend lines for deeper insights.
- The dashboard provides a comprehensive overview of the business performance with key metrics like profit margin and return rate.
- Dynamic visualizations and KPI cards facilitate quick and effective decision-making by highlighting critical business areas.
- Interactive filters and top product displays ensure focused and relevant analysis, enhancing data-driven strategies.
Topic: Table Creation Creating tables in Tableau is fundamental for organizing and summarizing data, making it easier to understand and analyze.
Metrics Used Total Sales Total Profit Importance Tables help in breaking down data into digestible parts, allowing for detailed analysis and comparisons across different categories and regions.
Inference This visualization allows us to compare the performance of different categories and sub-categories across various regions, highlighting areas with high sales and profit margins.
Topic: Data Combining Techniques & Filtering Merging tables using joins in Tableau is crucial for integrating different datasets, enabling comprehensive analysis.
Metrics Used: Number of Appearances & Movie Titles
Importance: Combining data from multiple sources provides a complete picture and deeper insights, essential for complex analyses.
Inference: Identifying the actor/actress with the most appearances in sports movies helps in understanding casting trends and the popularity of certain actors in specific genres.
Topic: LODs & Histogram Histograms display the distribution of data points across a specified range, which is useful for understanding patterns and frequencies.
Metrics Used: Number of Orders & Customer Count
Importance: Histograms are significant for identifying trends and anomalies in data, providing a visual representation of distribution.
Inference: This histogram reveals the frequency of customer orders, helping in identifying customer behavior patterns and potential areas for improving order frequency.
Topic: Sets Pie charts are effective for displaying proportions and comparing parts of a whole, particularly in sales analysis.
Metrics Used: Sum of Sales
Importance: Pie charts simplify the understanding of data proportions, highlighting significant contributors to total sales.
Inference: This pie chart showcases the contribution of the top 50 customers to total sales, emphasizing the importance of key customers in driving revenue.
Topic: Custom Visuals KPI cards and trend lines are crucial for tracking key performance indicators and visualizing changes over time.
Metrics Used: Total Profit & Percentage Growth
Importance: KPI cards provide at-a-glance information on critical metrics, while trend lines illustrate performance over time.
Inference: These visuals highlight the profit trends and growth rates, enabling quick assessment of financial performance and identification of growth patterns.
Topic: Parameters & Groups Parameters and groups in Tableau allow for dynamic analysis and customized data views based on user selection.
Metrics Used: Sum of Sales
Importance: Dynamic parameters enable users to interact with data, providing flexible and tailored insights.
Inference: This visualization allows for detailed sales analysis based on selected parameters (Region, Category, Sub-category), facilitating targeted decision-making.
- Download the Tableau .twbx file from this repository.
- Open the file in Tableau.
- Explore the various sheets and dashboard to analyze the data.
- Utilize the interactive filters and parameters to customize the visualizations based on your needs.