Fixed LOD Tableau Functions: The Ultimate Guide 101
The purpose of this blog is to discuss the Fixed LOD Tableau Function and Expression. It also includes an example to show how to develop a basic LOD Expression.
Table of Contents
Level of Detail expressions (also known as LOD expressions) enables you to compute values at both the data source and visualization levels. LOD expressions, on the other hand, provide you with even more control over the level of granularity you want to compute. They can be carried out at a more granular (INCLUDE) or a less granular (EXCLUDE) level, or at a totally separate level (FIXED).
Simply put, FIXED expressions aggregate the value ONLY at the specified dimensions in the calculation. Unlike the INCLUDE/EXCLUDE expression, the FIXED expression does not take the dimensions of the view into account.
The plot twist, however, is as follows. FIXED LOD Tableau expressions, like LOD shapeshifters, can have finer, coarser, or even the same level of detail as the view. As a result, how you use it is determined by the dimensions that are already present in the view.
Table of Contents
- What is Tableau?
- What is FIXED LOD Tableau Function?
- How to Use FIXED LOD Tableau Function?
- Fixed LOD Tableau Function Limitations
- Conclusion
What is Tableau?
Tableau is a strong and rapidly developing Data Visualization solution in the Business Intelligence Industry. It makes it easier to convert raw data into an Intelligible format. Tableau aids in the generation of data that experts at all levels of a company can understand.
Tableau, a Data Visualization and Business Intelligence Platform, was developed in 2003 by Christian Chabot, Pat Hanrahan, and Chris Stolte. It grew in popularity as businesses sought meaningful insights from various data sources while also working with their employees.
Tableau, A good tool for evaluating large volumes of data since it excels at Data visualization. Tableau has assisted leading organizations in a range of industries in reducing processing time and becoming more data-driven, all while ensuring Flexibility, Security, and Reliability.
Key Features of Tableau
Tableau is a better alternative to other BI solutions because it has more features. Here are a couple of examples of this:
- It provides a wide range of integrations to choose from.
- A one-of-a-kind drag-and-drop functionality.
- Your inquiries or questions are transformed into Visual Representations.
Tableau can be accessed via mobile, online, and desktop platforms. - It allows you to create a range of Visualizations to aid with data analysis.
- Tableau has over 200 connectors that enable users to securely connect to external data sources such as RDBMS, the cloud, and spreadsheets.
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What is FIXED LOD Tableau Function?
Determine the number of sales for each state and region. First, use the formula to construct the Regional Sales formula field, as seen in the screenshot below.
Then, under the Marks card, drag the Region and State fields to the Rows shelf and the computed field to the Text shelf. Drag the Region field to the Color shelf as well. This results in the following view, which displays a fixed value for each state. This is due to the fact that we have set the dimension as a region for the computation of Sales value.
How to Use FIXED LOD Tableau Function?
The FIXED LOD Tableau Function allows you to determine the granularity of the computation regardless of what is in the view. This is how the syntax looks:
FIXED LOD Tableau DETAIL LEVEL Expressions can have finer detail than the view, coarser detail than the view, or the same amount of detail as the view. The requirement to aggregate the outcomes of a FIXED LOD Tableau Function of detail is determined by the dimensions in the given view.
The Sample – Superstore data source can be used to recreate the following examples.
The period between a customer’s first purchase date and any subsequent purchases is depicted in the following view:
- Make two computed fields: one with a FIXED degree of detail expression and one with a date subtraction.
- FIXED [Customer Name]: MIN([Order Date]) FIRST PURCHASE DATE
Days since the initial purchase
DATETRUNC(“day,” [Order Date])-DATETRUNC(“day,” [First Purchase Date])
Drag Days Since First Purchase from the Data pane’s Measures field to the Dimensions area.
- Drag the days since the first purchase to the columns.
- Columns, click Days Since First Purchase, and then select Continuously.
- Sales should be dragged to Rows.
- Change the Sales on Rows aggregate from SUM to AVG.
- Sales on Rows: Running Total now has a simple table computation.
- Drag the First Purchase Date to the Color palette.
To add the next level down in the date hierarchy, click the + in the YEAR(First Purchase Date) column on Color: QUARTER (First Purchase Date).
Tableau will not place two fields on Color by default, but you can force it by clicking the icon to the left of the QUARTER(First Purchase Date) field and selecting a Color:
Drag the Color legend to the left side of the screen, beneath the Marks card. Your perspective should now look like this:
As you engage with Visualization, you will gain insights. Select a quarter from the color legend on the left to see how consumers acquired in that quarter continued to spend in later quarters. Customers recruited in the early beginning (2013) tend to spend at a higher pace, even when considering that they had more time to do so—hence, the blue lines (for 2013) are higher up on the x-axis than other lines.
The view would have been easier to design if you had used a standard date value on the y-axis, but the lines would not have all started at the same locations, making a comparison of acquisition speeds more challenging.
When we include City in the Row shelf, the view becomes finer-grained than the FIXED computation we used. As you can see, the view has two dimensions (State and City), whereas our FIXED LOD Tableau Calculation just has one. Because our FIXED LOD Tableau calculation is coarser than the view, our data have now been replicated down the pane.
Fixed LOD Tableau Function Limitations
The following limits and constraints apply to all Fixed LOD Tableau expressions:
- When used in a view that requires a comparison of the values in the expression, FIXED LOD Tableau expressions that reference floating-point measures can exhibit unpredictable behavior.
- When referencing a parameter in a dimensionality declaration for FIXED LOD Tableau expressions, you must always use the parameter name rather than the parameter value.
- Before you can use a level of detail expression from the secondary data source, you must first confirm that the linking field from the original data source is in the view with the FIXED LOD Tableau.
Conclusion
We’ve just scratched the surface of what is perhaps Tableau’s most powerful feature Fixed LOD Tableau expression, but this example should have provided a decent foundation for understanding what degree of detail is and how it can be changed to enhance your study.
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