![]() What values are allowed in a given field are determined by the domain of the field (see the note below). The items themselves are called values or members (only discrete dimensions contain members). (We save the term column in Tableau Desktop for use in the columns and rows shelf and to describe certain visualizations.) A field of data should contain items that can be grouped into a larger relationship. What is a field or column?Ī column of data in a table comes into Tableau Desktop as a field in the data pane, but they are essentially interchangeable terms. Tip: For more information, see Data Aggregation in Tableau. Understanding aggregation and granularity is a critical concept for many reasons it impacts things like finding useful data sets, building the visualization you want, relating or joining data correctly, and using LOD expressions. Knowing the granularity of the data is crucial to working with level of detail (LOD) expressions. What does a row or record in the data set represent? A person with malaria? A provinces' total cases of malaria for the month? That's the granularity. You can change the aggregation to options like Average, Median, Count Distinct, Minimum, etc. Refers to how multiple data values are brought together into a single value, such as counting all the Google searches for Pumpkin Spice or taking the average of all the temperature readings around Seattle on a given day.īy default, measures in Tableau are always aggregated. If you can't articulate that, the data might be structured poorly for analysis.Ī concept related to what makes up a row is the idea of aggregation and granularity, which are opposite ends of a spectrum. This is the same as answering "What does the TableName(Count) field represent?". Try to make sure you can answer the question "What does a row in the data set represent?". Note that not all data sets have a UID but it can't hurt to have one. Think of it like the social security number or URL of each record. Tip:A best practice is to have a unique identifier (UID), a value that identifies each row as a unique piece of data. It's important to know what a record (row) in the data represents. So what should be a row or column? What is a row?Ī row, or record, can be anything from information around a transaction at a retail store, to weather measurements at a specific location, or stats about a social media post. That is, data stored in rows and columns, with column headers in the first row. Tableau Desktop works best with data that is in tables formatted like a spreadsheet. But if you can optimize the data structure it will likely make your analysis much easier. For an example of how to perform the same analysis with different data structures, see Tableau Prep Day in the Life Scenarios: Analysis with the Second Date in Tableau Desktop (Link opens in a new window). It is often still possible to perform the analysis but you may need to change your calculations or how you approach the data. ![]() ![]() However, there may be situations when you can't pivot or aggregate your data as desired. The rest of this topic assumes you have access to the raw data and the tools needed to shape it, such as Tableau Prep Builder. The structure of your data may not be something you can control. If you do not already have a data set you can use, see our tips for finding good data sets (Link opens in a new window). Tip: It may help to go through the following topic with a data set of your own. rows and columns, as well as aspects of data cleanliness, such correct data types and correct data values. Data can be generated, captured, and stored in a dizzying variety of formats, but when it comes to analysis, not all data formats are created equal.ĭata preparation is the process of getting well formatted data into a single table or multiple related tables so it can be analyzed in Tableau. There are certain concepts that are fundamental to understanding data prep and how to structure data for analysis. ![]()
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