Introduction to LOD Expressions and FIXED

Calculations in Tableau

Maarten Van den Broeck

Content Developer at DataCamp

Granularity of the data

Data granularity is the level of detail in a model or decision making process. It tells you how detailed your data is (1)

e.g. Time-series analysis: per second | minute | hour | day | week | month | (...)

Two tables, the left one with Sleep per day results and the right one with Heart Rate per minute results

1 Ponniah, P. (2004). Data Warehousing Fundamentals: A Comprehensive Guide for IT Professionals. Wiley.
Calculations in Tableau

Granularity of the view

  • Granularity and aggregation
  • Aggregate = decrease the data granularity. e.g. Total SUM(Sales)

  • Add dimensions = increase the data granularity, e.g. SUM(Sales) per region and per year
Calculations in Tableau

Managing granularity in Tableau worksheet

  • Adding dimensions to the Shelves

  • Adding dimensions on the Marks:

    • Detail
    • Color
    • Shape
    • Size
    • Path
    • Label

  • More dimensions = more data points

  • It becomes more difficult to visualize

Screenshot of Tableau's canvas and surrounding shelves and Marks cards

Calculations in Tableau

LOD Expressions in Tableau

LOD Expressions provide a way to easily compute aggregations that are NOT at the level of detail of the visualization

Family of 3 functions:

  • INCLUDE: calculating at a lower level of detail
  • EXCLUDE: calculating at a higher level of detail
  • FIXED: calculating at an exactly specified level of detail
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FIXED LOD Expressions

FIXED level of detail expressions compute a value using the specified dimensions, without reference to the dimensions in the view.

Syntax of FIXED LOD expression with explanation per component of the formula.

  • Works with 0, 1, 2 or more dimensions, in any order
  • Result of the LOD calculation can be either a dimension or a measure
  • Dimensions of interest are contained in the calculation and do not clutter the view
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Practical applications of FIXED LOD expressions

Calculating measures between various time dimensions:

e.g Swapping between daily and weekly calculations { FIXED [Day] : SUM(Sales)}

Calculating (sub) totals per categories:

e.g. % of Total { FIXED [Product] : SUM(Costs) } / { FIXED : SUM(Costs) }

Computing first or last data point per data subject:

e.g. First order date per customer { FIXED [Customer] : MIN([Order Date]) }

Calculations in Tableau

Cohort and survival analysis

Cohort analysis:

  • Analyzing repetitive behavior of a group

Graph presenting cohort analysis

  • e.g. Usage of a product by various client groups (cohorts)

Survival analysis:

  • Analyzing how many subject remain in dataset on a given day

Graph presenting survival analysis

  • e.g. Who still keeps the New Year resolutions in February?
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Cohort and Survival analysis - FIXED

Cohort analysis:

  • Analyzing repetitive behavior of a group.

Graph presenting cohort analysis, with encircled Y-axis date dimension

  • e.g. Usage of a product by various client groups

Survival analysis:

  • Analyzing how many subject remain in dataset on a given day.

Graph presenting survival analysis, with encircled X-xis date dimension

  • e.g. Who still keeps the New Year resolutions in February?
Calculations in Tableau

Let's practice!

Calculations in Tableau

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