www.tableaulearners.com is a website that has been created keeping in mind, both Tableau developers and Tableau beginners. This website aims at helping Tableau developers excel in their work and to learn more about Tableau. For beginners, this website will help lay a strong foundation in Tableau. The website contains numerous articles that explain several Tableau topics, in detail. The website will act as a platform wherein new articles, tips and tricks are posted regularly.
Let’s break the dashboard design and think how we should use layout containers. A “Layout container” is a type of object. It helps to organize worksheets and other objects on the dashboard. Layout containers usually create an area in the dashboard sheet where views or objects automatically adjust their size and position based on other views or objects in the dashboard. In simple words, it allows you to group objects horizontally or vertically within the dashboard workspace.
Edward Tufte, a pioneer in the field of data visualization and data design, maintains that pie charts “should never be used,” and Stephen Few calls it “by far the least effective” graph intended to facilitate quantitative communication and no one denies this theory but yet, we support pie charts. Why?
Pie charts are useful for representing a simple proportion of a whole, and can easily be interpreted by expert and novice alike. Even Viz Guru Mr.Few admits that there’s one thing the pie chart does better than any other visualization, and that is convey the part-to-whole relationship.
Waterfall charts are ideal for showing how you have arrived at a net value, by breaking down the cumulative effect of positive and negative contributions.The initial value and the resulting total value are represented by bars in the visualization, and the value changes in-between are shown as floating blocks that indicate the ups and downs. As a means to follow the development of the value from start to end, transition lines can be added between the blocks. This is very helpful for many different scenarios, from visualizing financial statements to navigating data about population, births and deaths.
Crosstab or Cross Tabulation is used to aggregate and jointly display the distribution of two or more variables by tabulating their results one against the other in 2-dimensional grids. Cross-tabulation is usually performed on categorical data — data that can be divided into mutually exclusive groups. Cross-tabulations are used to examine relationships within data that may not be readily apparent and if you can highlight a specific column or row in your crosstab it will help you to understand the quantitative relationship between multiple variables.
This week Rody back with a fairly simple challenge, but one that has a few useful tricks that could help spice up your next viz. The tricks used in this challenge are geared toward design, but have additional benefits. This Workoutwednesday Challenge can teach you some advance usage of Tableau function like use of Regex function, MID function and how you can utilize ASCII characters on your calculation.
A Pareto diagram is a simple bar chart that ranks related measures in decreasing order of occurrence. The principle was developed by Vilfredo Pareto, an Italian economist and sociologist who conducted a study in Europe in the early 1900s on wealth and poverty. He found that wealth was concentrated in the hands of the few and poverty in the hands of the many. The principle is based on the unequal distribution of things in the universe. It is the law of the “significant few versus the trivial many.” The significant few things will generally make up 80% of the whole, while the trivial many will make up about 20%.
Data preparation is an iterative and very important process for exploring, combining, cleaning and transforming raw data into curated datasets for data integration, data science, data discovery and business intelligence analytics. Data preparation plays key role in businesses and any decision to make using data. Data preparation is made easy by using data preparation tools for analysts and so many businesses.In real life people spend upto 80% of time preparing data and 20% analyzing it