Identifying trends in our data is an important step in extracting valuable information about our organization’s work. Trends, patterns, or the frequency of certain behaviors can tell a lot about future strategies that should be implemented. Additionally, they also contribute to a better process organization to deliver to consumers what they expect, in the moments that matter. In today’s post we will discuss how to use a detailed histogram in Tableau Software and the advantages it offers when added to an analysis.
We discussed in a previous post about histograms with normal distribution in Tableau. You can access the article here. We explained there what it is, how it can be used and built. Today, however, we will focus on a new way to build histograms, namely, to add more details and values for a better understanding of our data.
Histograms represent a bar chart that displays the distribution of values in a data set on an axis. Each bar of the graph represents the range of a value. The bars that form the chart are also called bins or buckets, and their height is given by the frequency of the analyzed values. The higher a bar, the higher the value in that range and vice versa.
Although most of the time histograms are used only to highlight the frequency of certain values in certain intervals, Tableau Software allows us to add other additional information. Thus, in the final visualization we will be able to explore in more detail valuable information for our activity. The final result will be in fact a detailed histogram through which we will highlight the distribution of values, their frequency in certain intervals and other additional information that interests us.
A detailed histogram can be used in different situations, depending on what information we have in our data set. For example, we can visualize which are the days with the most registered orders and the profit of each order. We can analyze which are the times of the year with the most sales, adding the best-selling product categories from those periods. We can identify, for example, the frequency of people in a restaurant and which are the most consumed products depending on the hours they choose to spend their time there. A detailed histogram allows us to identify several levels of detail that can often be useful to make the right decisions for our business.
To create a detailed histogram, please follow the steps below and watch the video:
→ In Tableau Desktop, connect to Tableau: Sample-Superstore
→ Select Analysis > Create Calculated Field: Count distinct of customer orders
{FIXED [Customer Name]:COUNTD([Order ID])}
→ Select Analysis > Create Calculated Field: Index
INDEX()
→ Convert to Dimension : Count distinct of customer orders
→ Drag Count distinct of customer orders to Columns
→ Drag Index on Rands
→ Right-click on Distinct Count of Customer Orders and select Continuous
→ Drag Customer Name on Rows
→ Edit Calculated Table(Index):
1. Select Customer Name only
2. Sort order: select Custom and choose Profit
→ Drag Profit on Color
By Eduard Arhire
What is metadata? Metadata is structured information that describes various data sources and files, which can be managed and reused within jobs. Why is metadata used? Creating metadata is a Best Practice because it simplifies setting up connections and accessing […]
On April 18 we organized a private event btProvider & Vertica by OpenText titled “AI and Analytics”.
It was a private event dedicated to Data enthusiasts eager to explore the innovations of Analytics and Artificial Intelligence.
Pace charts are an alternative to bullet graphs that normalize progress-to-goal visualizations across KPIs, even when these KPIs have different data formats, scales, and/or seasonal trends. They are useful for providing an apples-to-apples, pace-to-goal comparison in businesses with KPIs spanning […]