Advanced Tableau - Level of Detail Expressions / LOD

Name: Advanced Tableau - Level of Detail Expressions / LOD
Rating: 4.6 (998 reviews)

Take Your Tableau Data Visualization and Data Analytics Skills to the Next Level and Design Custom Solutions with Ease

Created byR-Tutorials Training

Last updated 9/2019

English

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What you'll learn

Understanding LOD expressions and using them confidently
Performing calculations in Tableau that are at a different level of detail than the view
Analyzing and solving complex analytical challenges
Understanding the different levels of details of multivariate datasets
Cohort analysis
Market basket analysis
User retention analysis
Binning aggregates by dimensions
Proportional brushing
Relative comparison of values/ categories
Nesting LOD expressions

Course content

4 sections • 45 lectures • 6h 13m total length

Introduction3:25
Master level of detail expressions in Tableau to solve cohort analysis, retention, binning, and aggregate comparisons beyond the view level of detail, enabling practical, scalable insights.
Prerequisites - Things to Consider to Benefit from this Course3:01
Prerequisites include a basic understanding of Tableau and prior calculations; no Lod expressions knowledge is required, and you need Tableau Desktop or Public plus Excel or Calc.
Datasets Used2:27
Discover how varying dataset structures and granularity frame Tableau analysis, reveal possible calculations, and guide access to xlsx datasets and packaged twb workbooks used in lectures.
Course Inventory1:12
Calculation Types in Tableau8:11
Explore the main calculation types in Tableau, including row-level calculations, aggregated expressions, table calculations, and level of detail (LOD) expressions, and see how they relate to granularity and aggregation.
What Is the Level of Detail?10:10
Discover how level of detail expressions in Tableau enable aggregations at different granularities, explain the view level of detail, and handle row-level data and profit ratio differences.
How Do LOD Expressions Help?5:33
Explore how level of detail expressions manage data granularity and aggregation in Tableau, using fixed, include, and exclude to compute across dimensions beyond the current view.

Syntax2:56
Explain the syntax of level of detail (LOD) expressions in Tableau, including fixed, include, and exclude, with dimension declarations and aggregation. Show how city affects totals.
The INCLUDE Expression11:52
The EXCLUDE Expression9:53
Explore the exclude expression in Tableau LODs, which omits a dimension to compute at a coarser scope and duplicates results across the view, unlike include.
The FIXED Expression10:22
Learn how the fixed level of detail expression computes aggregations independently of the view, by specifying dimensions and maintaining consistent results across changing visualizations.
Exercise with the Lures Dataset - Getting the Difference of a Value and its AVG6:31
Use fixed level of detail (LOD) expressions to compute the difference in profit ratio between each product and its category, revealing product performance relative to category.
Calculation Results and the View LOD - Comparison of Expressions10:00
Compare fixed, include, and exclude LOD expressions in Tableau and their relation to the view and filters. See how context and dimension choices shape sales aggregation.
Filters and Outcomes - Comparison of Expressions7:27
Compare fixed, include, and exclude level of detail expressions as they interact with filters, showing how fixed stays set against dimension filters while include and exclude adapt.
Finding Dates with LOD Calculations8:48
Master table-scoped LOD expressions to find the earliest and latest order dates with fixed min and max. Compare latest versus prior year sales using year and date trunk functions.
Table Scoped LOD Expressions8:06
Apply table-scoped and fixed LOD expressions to control scope in Tableau, using customer name and latest order as examples, and compare profit against the table average.
Declaring Date Parts in an LOD Expression6:27
Declare date parts in lod expressions to compute average orders per category per month, using fixed calculations and date trunc to roll dates to month, with year added when needed.
Adjusting the Timeline with LOD Expressions6:58
Exercise Assignment - German Gas Stations3:04
Explore advanced Tableau level of detail (LOD) expressions to calculate average customer spending by city while avoiding double counting in a German gas stations dataset, and build a supporting visualization.
Exercise Solution - German Gas Stations12:05
Testing and Debugging11:39
Test and debug level of detail calculations in Tableau using Excel for validation, while sampling data to confirm per-customer versus per-state averages and the impact of city–state relationships.

Introduction1:48
Master advanced level of detail expressions by applying thematic, standalone lectures on cohort analysis, nested lod expressions, and practical load calculations to deepen analytical skills in Tableau.
Binning Measures with LOD Calculations - Binning Aggregates I9:59
Explore binning aggregates with fixed LOD expressions in Tableau to count orders, items, and customers. Learn step-by-step how to build histograms, bin data by order ID, and verify results.
Conditional Binning - Binning Aggregates II.13:48
Explore advanced binning of aggregates in Tableau using fixed level of detail expressions. Compute age-group averages of distinct treatment counts with reference lines and careful aggregation.
Creating Custom Cohorts - Cohort Analysis I.11:00
Understand cohort analysis in Tableau using LOD expressions and fixed calculations to define first order dates, visualize customer cohorts, and analyze user lifetime and revenue by cohort.
Tracking User Retention - Cohort Analysis II.14:44
Explore cohort analysis in Tableau to visualize user retention across many cohorts using calculated fields and table calculations, including color cohorts, dual-axis lines, and cross-tab views.
User Retention and Non-Consecutive Behavior - Cohort Analysis III.8:32
Explore cohort analysis with level of detail expressions to measure non-consecutive user retention, computing months between first and second orders and visualizing trends with a heatmap.
Comparing Data at Different LODs - Proportional Brushing I.8:35
Learn to compare fertility rate of a country against its region across segments using level of detail expressions and fixed expressions, then build interactive dashboards with map filters and actions.
Data Density Issues - Proportional Brushing II.5:53
Explore how fixed level-of-detail calculations behave under filters, compare monthly sums to density-driven line changes, and learn data padding to maintain consistent proportional brushing in Tableau.
Relative Comparison - Proportional Brushing III.8:52
Explore proportional brushing through a relative comparison that lets you pick a base product and see other products' profits relative to that selection using parameter-driven lod calculations.
Market Basket Analysis - Proportional Brushing IV.15:39
Learn market basket analysis in Tableau using proportional brushing and level of detail expressions to reveal items bought together across orders.
Exercise: Vehicles11:42
Apply fixed and table-scoped lod expressions to build three Tableau charts for a car fleet: total, lent out vs stationed, and a type-based percentage ratio.
Benchmark Performance Alerts13:53
Leverage level of detail expressions in Tableau to create benchmark performance alerts, computing production ratio and flagging underperforming manufacturers below a threshold with a reference line.
Switching Between High and Low LODs - Benchmark Performance Alerts II.6:30
Switch between high and low levels of detail in Tableau by using parameter-driven dashboards and filter actions to drill from group to manufacturer with a back navigation button.
Changing the LOD of Maps - Changing the View LOD II.7:20
Learn to switch map detail from country to city using level of detail (LOD) expressions, parameters, and contextual filters, building a dual-axis map with fixed expressions and geographic roles.
Leveraging on Parameters - Changing the View LOD III.4:34
Use parameters to dynamically change the view level of detail in Tableau by switching between dimensions like category and country and metrics like profit and sales.
Exercise: Proportional Brushing8:01
Combine lod expressions for proportional brushing and a drill down to create an interactive dashboard with a map of profit by country and a line chart showing profit over time.

The Rules of Nesting LOD Expressions7:40
Master nested lod expressions in Tableau to answer complex questions across multiple levels of detail, such as comparing February sales across years, while applying rules of aggregation, replication, and filters.
Comparison of Results14:54
Explore how fixed, include, and nested LOD expressions affect the sum of sales by state and customer, revealing context inheritance and when different approaches yield the same results.
Combining the EXCLUDE and INCLUDE Expressions8:36
Learn how to use include and exclude level of detail expressions in nested calculations to find the maximum sum of sales by city and customer within each state.
Combining the FIXED and INCLUDE Expressions11:06
Explore how to combine fixed and include LOD expressions in Tableau, demonstrating nesting effects, dimensionality inheritance, and how to achieve correct aggregation across city, state, and customer name.
Revisiting the Data Structure8:27
Explore how level of detail expressions handle fixed and nested calculations, reveal many-to-many state and city relationships, and emphasize data structure understanding through sampling and testing.
Exercise: Nested LOD Expressions10:39
Explore nested level-of-detail calculations to compare each month against its historical monthly average, using fixed and exclude scopes, and calculate percent differences with date parts for month-level aggregation.
Limitations4:57
Explore the limitations of LOD expressions in Tableau, including data source constraints, that results are meaningful only within specific LOD contexts, and that Tableau data extracts support LOD expressions.
Typical Scenarios of LOD Expressions - Summary5:59
Explore typical scenarios for level of detail expressions in Tableau, including fixed, include, and exclude, to aggregate at different levels, bin data, and bypass filters.

Requirements

Basic understanding of Tableau
No prior knowledge of level of detail expressions is required
Tableau Desktop Professional or Tableau Public Desktop
Tableau Reader (if you are a Tableau Public user)
MS Excel or other table management tool (e.g. OpenOffice Calc)
Pen and paper to take notes

Description

Have you ever had analytical questions that are easy to ask, but surprisingly hard to answer with regular analytical tools? Do you often find yourself asking questions involving different data layers? Like comparing a single category to a whole table; or applying filters on particular fields; or tracking the behaviour of custom cohorts over time - just to mention a few classic examples.

Do you want to know how to compare data aggregated at different levels of granularity?

Do you often bump into the error message: 'Cannot mix aggregate and non-aggregate values'?

Do Tableau terms FIXED, INCLUDE or EXCLUDE confuse you? Are you struggling choosing the right one for particular tasks?

Do you want to step up your daily analytical game and gain new, useful skills?

If you are a passionate Tableau user and you can associate yourself with one or more of the questions above, then this course is for you. Scenarios like the ones mentioned above occur on a daily basis, and they can cause quite a bit of headache for the analyst. Tableau has many great tools and functions including table calculations that make everyday life easier for the data scientist.

One strong point of the software is its responsiveness. Plotting measures against variables has never been easier: each change to the shelves is instantly and automatically applied on the view - a great environment to interact with the data. This strong point, however, can easily be turned into a weakness, if you want your analysis to step out of the borders of the view level of detail.

In Tableau, to solve classic analytical problems (such as cohort analysis, retention analysis or binning aggregates by dimensions), or to proceed with special filtering scenarios (like proportional brushing or relative comparisons) you need to be familiar with a special tool set called the level of detail (LOD) expressions.

In this course, you will learn about the general mechanics of LOD expressions both in theory and practice. We start from the very basics and then we proceed to more advanced techniques in a stepwise manner. If you are not familiar with the concept of LOD expressions yet, but you are already a Tableau user, then taking this course will most probably improve your analytical skills and broaden your tool set.

After completing this course, you will be able to solve all above mentioned analytical challenges and even more, because LOD expressions let the analyst come up with creative solutions for custom scenarios. Instead of asking the questions you can be the one in the office who always has a practical answer or a constructive idea. Take a look at the content of this course, and I bet you won’t regret it.

Who this course is for:

Tableau users who want to unlock new analytical skills
Tableau users who want to better understand the usage of level of detail expressions
This course is not for absolute Tableau beginners

Advanced Tableau - Level of Detail Expressions / LOD

What you'll learn

Explore related topics

Course content

Introduction to the Course7 lectures • 34min

The Basics of Level of Detail Expressions14 lectures • 1hr 56min

Intermediate and Advanced LOD Projects16 lectures • 2hr 31min

Nested LOD Expressions8 lectures • 1hr 12min

Requirements

Description

Who this course is for: