Have you ever imported a dataset into Tableau, Power BI, Looker Studio, or Qlik Sense—only to find that several identical rows suddenly appear as one?
If so, you’ve likely encountered BI tool data deduplication, a fundamental behavior across nearly all modern Business Intelligence platforms.
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Stacked bar charts are often used to display the breakdown of data within categories, but they have a big drawback: once you go beyond the first layer, comparing the rest becomes visually difficult. That’s where grouped bar charts step in.
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A Pareto chart is a powerful visualization that combines both bar and line charts to identify the most significant factors in a dataset. Named after the Pareto principle (also known as the 80/20 rule), it helps users focus on the causes that generate the majority of results. In this article, we’ll walk through how to build a Pareto chart in Power BI using the Superstore dataset, a common sample dataset used in data visualization training.
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If you’ve ever stared at a blank Tableau dashboard wondering how to move beyond bar and line charts — you’re not alone.
Sure, those basics serve a purpose. But data storytelling is about more than ticking boxes. It’s about helping your audience see the story behind the numbers. That’s why I started building a personal catalog of unique, visually engaging Tableau chart types — and now I’m sharing them with you.
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Data visualization is a powerful tool for conveying insights, but the effectiveness of a visualization largely depends on how well the chosen chart represents the underlying data. As a data analyst, selecting the appropriate chart type is critical to ensuring your message is communicated clearly and effectively. In this guide, we’ll explore the most common chart types, their strengths and weaknesses, and when to use each one.
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Working with dates in Tableau is essential for trend analysis, time-series visualizations, and dynamic dashboards. Tableau provides a rich set of date functions that help you parse, manipulate, and calculate date values with ease.
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Radar charts, also called spider charts, are great for comparing multiple variables across categories. While Tableau doesn’t natively support radar charts, you can still build one using calculated fields and some data reshaping.
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Parallel sets are a visually striking way to represent flows and relationships between categories, offering deeper insights into complex data distributions. In this blog, we’ll guide you step by step on how to create a parallel set visualization in Tableau using the Sample Superstore dataset.
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Table calculations in Tableau are powerful tools that allow you to perform computations directly on the aggregated results in your visualization. Unlike calculated fields (which operate at the data source level), table calculations depend on the structure of your table or pane, making them ideal for dynamic, context-aware metrics. In this guide, we’ll break down compute using options, advanced settings like addressing and partitioning, and demonstrate practical examples using Tableau’s Superstore dataset.
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Polar charts are a unique and visually compelling way to display data in a circular format. In this tutorial, we’ll guide you through creating a polar chart in Tableau using the Sample Superstore dataset. Whether you’re using Tableau Desktop or Tableau Public, follow these steps to build a stunning visualization.
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