Advance Tableau Calculations

Explore quick table calculations in Tableau with predefined functions like running total, difference, percent difference, percent of total, rank, percentile, and moving average.

Learn how to create a running total in Tableau using quick table calculation, dimensions, measures, and grand totals.

Apply a difference table calculation in Tableau by arranging subcategory on rows, placing unit price on the marks shelf as label and text, and interpreting the resulting differences.

Learn how to compute percent difference in Tableau by comparing consecutive values of a discount, using the current over previous formula and examples like jumbo drum and jumbo box.

Explore how to compute percent of total in Tableau, using the grand total as the denominator and the mark shelf to create a percent of total calculation with practical examples.

apply the rank function as a quick table calculation to rank products by unit price in descending order. rank-dense helps avoid skipped numbers when duplicates occur, with shipping price demonstrated.

Learn how to use rank dense instead of rank in Tableau calculations, applying a dense rank on sum of sales to handle duplicates and avoid demerits.

Learn to create a moving average in Tableau using order date by month, apply filters, and synchronize dual axes to reveal smoother sales trends.

Compute moving averages from monthly sales by combining the current value with previous months, handling nulls, and dividing by the actual count to produce the smoothed output.

Master moving average calculations in Tableau by applying past and future data points to smooth sales trends, adjust granularity, and interpret output for better forecasting.

Explore the rank unique function in Tableau, learn to create a calculated field for sum of sales, compare rank and dense rank, and master ascending vs descending ranking with duplicates.

Explore rank, rank dense, and rank unique in Tableau calculations, highlighting how duplicates affect ranking and why rank dense yields accurate results for sales.

Apply the rank function to assign a unique priority in tableau, using the example where S3 gets the top rank nine and S1 gets rank ten as the next.

Explore Tableau level of detail syntax, selecting type (fixed, include, exclude), dimensions, and aggregations (min, max, average, median) for measures like profit and sales.

Identify three level of detail expressions in Tableau calculations: fixed, include, and exclude. Fixed is independent; include and exclude are dependent on the visualization and context filters.

Apply the Elodie syntax in Tableau calculations by combining type, dimension, and measure aggregation. Compare fixed, include, and exclude to see how results stay constant or vary with filters.

Learn how to use fixed level-of-detail expressions in Tableau to fix a category and sum sales, illustrating independence from subcategory and visualization while exploring granularity and level of detail.

Learn how fixed load remains independent of dimensions in Tableau, how context and dimension filters can alter values, and how granularity shapes sales by region and category.

Explore include expressions in Tableau and compare them with fixed calculations, applying them to product category and category levels, and examine how dimensions like subcategory influence results in visualizations.

Learn to create an exclude calculation in Tableau to omit product category and see how it contrasts with fixed and include across product subcategory and sales.

Master include and fixed level of detail expressions in Tableau, and see how dimension filters and visualization context influence them. Analyze granularity through product category, subcategory, and related dimensions.

Learn to build and interpret customer and order counts in Tableau, using distinct versus non-distinct counts on orders data to reveal unique customers and total orders.

Apply advanced tableau calculations to derive the order count list and customer count by removing duplicates and counting distinct order IDs, then explore running totals and discrete measures.

Explore how to compute each customer's first and last purchase in Tableau using order dates and min/max dates, building fp1 by customer ID and validating exact purchase dates.

Use fixed level of detail calculations to identify each customer's first purchase by year (minimum order date), then count distinct customers per year, presenting results in discrete year blocks.

Explore cohort analysis and retention concepts in Tableau, calculating retention rate from customer count over time spans, using calculated fields and distinct counts to visualize trends.

Learn to measure retention and perform cohort analysis in Tableau, calculating retention rate across years and months using distinct customer counts and time spans.

Explore segment basis item comparison in Tableau by building a parameter to select a customer segment and a calculated field with exclude for sales differences.

Clarify dataset requirements and reinforce foundational skills by directing beginners to the A to Z w codes for beginners and intermediates before enrolling in the blue visualization course.

Explore building a pie chart in Tableau using marks card, color by product category, and applying percent of total, angle, and size to compare sales across categories and years.

Explore how year and product category filters let you compare sales by category in a pie chart and color by the sum of sales as a percentage of total.

Enhance a pie chart with greater granularity and multi-year views. Drag order date to columns to create yearly pies, color by product category, and tailor labels per the requirement.

Explore coloring and layout techniques in viz4, using product category and subcategory to build pie charts and tree maps, adjust marks, and compare dimensions in Tableau.

Create treemaps in Tableau from scratch, using sales as size and category/subcategory as color, with city and year filters to analyze regional performance.

Visualize customers on a world map by region, using distinct count for customer names as bubble size, with region filters, color by region, and in-bubble labels.

Learn to create dynamic top-N sales by product subcategory in Tableau using sets and parameters, with in and out of the set, filters, and labeled visuals.

Demonstrate how to show the top five customers by sales in Tableau using filters, sets, and a dynamic parameter to display each customer's total sales.