Tableau has been the most promising tool when it comes to data visualization. Visualization is all about presenting data in different forms which makes aggregation an important feature to get along. Let’s grasp some insights on data aggregation in Tableau in the following paragraphs.
What is Data Aggregation?
Data Aggregation refers to numerical or non-numerical information collected from multiple sources and compiled into data summaries or summary reports. Its major efficacy lies in the field of public reporting or statistical analysis. In Tableau, we can aggregate measures and dimensions. Whenever you add a measure to your view, an aggregation applies to that measure by default. The type of aggregation applied varies depending on the context of the view.
Well, there are some rules to be considered while applying data aggregation in Tableau. Ensure you follow them to the desired output.
Types of Aggregate Functions in Tableau
When you add a measure to the view, Tableau automatically aggregates its values. Sum, average, and median are the common aggregations. Below are some of the Tableau Aggregate Functions list:
- Number Functions
- String Functions
- Date Functions
- Type Conversion Functions
- Aggregate Functions
- Logical Functions
What are Aggregate Functions?
Aggregate functions are the built-in functions that allow you to summarize your data. It helps you change the granularity of your data. Following are the various Aggregate functions in Tableau:
Average functions return the mean of all values in an expression. It can be used with numeric fields only and it will ignore the null values.
The function would only return the single value for the calculated row. The null values will be ignored.
This function can be used for spatial fields. It will combine the values in the argument fields.
CORR stands for correlation between the two give expressions. When we want to correlate between the two variables, it can return three values 1, 0 and -1. The values 1 represents the positive changes, 0 represents no relationship and -1 represents the negative change.
It returns the number of values present in the selected column and NULL values can’t be counted.
This function will return the distinct count for the given column or a group and it will not return a NULL value.
COVAR stands for covariance for the given two expressions. The positive covariance indicates the variable is moving towards in the right direction and we can be noticed in the trend.
This function is similar to covariance but it is only biased with the population.
This function returns the maximum values for the given expression.
It will return the numeric values with the median of a single expression.
The MIN functions return the minimum values for the given expression.
This function will return the percentile for the corresponding given expression. It only returns values between 0 and 1.
This function returns if there are any high or low standard deviation values for the average value constrain.
It is similar to the standard deviation but the difference is, it will be based on a population.
It is a function that calculates the total numbers for the given range of numeric values.
The VAR function calculates the variance in the given expression.
It is similar to the Variance but the difference is, it will be based on a population.
You can aggregate measures using Tableau only for relational data sources. Multidimensional data sources contain data that is already aggregated. Learn more about aggregation and other Tableau features from the experts. Please follow the link https://irizpro.in/courses/certificate-training-in-tableau for certification and further details.
PS: In Tableau, Multidimensional data sources are supported only in Windows.