Converting Sold Quantity to Standardized Units in SQL

Learn how to convert sold quantities in SQL into `standardized units` using conditional aggregation and joins. This guide simplifies the complex process for better understanding.
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Converting Sold Quantity to Standardized Units in SQL

As businesses grow and expand their operations, they often face challenges in reconciling different units of measurement. For example, if a company sells products measured in both kilograms (KG) and gallons (GAL), it can be tricky to analyze overall sales if quantities aren't in a standardized unit. In this guide, we will demonstrate how to convert sold quantities into standardized units using SQL.

The Problem

Imagine you have sales data containing total quantities sold measured in different units. Our goal is to convert these units into a common measure, such as pounds (LBS), kilograms (KG), or gallons (GAL), according to a reference table that specifies conversion multipliers.

Example Data

Quantity Sold:

MaterialUnitOfMeasureQuantitySold1910KG4467801910GAL50001911GAL2000Reference Table:

MaterialFromUnitsToUnitsMultiplier1910GALLbs7.1071910LbsKgs0.51910KGLbs2.31911GALLbs9.31911LbsKg0.91911KGLbs4.2Desired Output

We want to produce a new table that summarizes sales data into standardized units:

MaterialUnitOfMeasureQuantitySoldStandardised_LbsStandardised_KGStandardised_GAL1910KG446780(446780*2.3)1910GAL5000(5000*7.1)1911GAL2000(2000 * 9.3)

The Solution

To convert sold quantity to standardized units in SQL, we can employ the power of Conditional Aggregation in conjunction with a JOIN statement. Let’s break down the SQL code that accomplishes this.

SQL Query Breakdown

[[See Video to Reveal this Text or Code Snippet]]

Explanation of the Query

SELECT Statement: We choose the columns we need from our datasets, which includes the material, the unit of measurement, and the quantity sold.

Conditional Aggregation:

We use the SUM() function alongside CASE statements to create new columns for each standardized unit (Lbs, KG, and GAL).

For each ToUnits, we check if it matches 'Lbs', 'KG', or 'GAL' and if it does, we multiply the QuantitySold by the corresponding Multiplier from our reference table.

JOIN Clause: This joins the sales data with the reference table based on matching Material and the original unit of measurement. This allows us to apply the correct conversion multiplier for each sold quantity.

GROUP BY Clause: Since we are aggregating data (using SUM), we group our results by Material, UnitOfMeasure, and QuantitySold to maintain organized results.
Conclusion

Transforming quantities from various units into a single standardized unit in SQL may seem daunting, but breaking it down into smaller parts makes it manageable. By employing Conditional Aggregation and JOIN operations, we can effectively convert and analyze sales data. This not only simplifies reporting but also provides clearer insights into product performance across different measurement units.

Feel free to experiment with the provided SQL query on your datasets to see how it can enhance your analytics capabilities!

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