In this tutorial, you'll learn three powerful techniques to identify missing dates in your data using Power Query (M Language):
Appending tables – Combine existing data with a complete date list
Merging tables – Detect gaps by joining actual and expected data
Using List.Difference – Compare two lists and directly extract missing entries
These methods are perfect for validating time series, logs, sales data, or any dataset where a continuous date range is expected.
✅ What You'll Learn:
How to generate a complete list of dates in Power Query
How to compare actual vs. expected dates
When to use append vs. merge vs. List.Difference
Best practices for scalable and reusable solutions
🔧 Tools Used: Power BI Desktop / Excel Power Query
📁 Applies To: Excel, Power BI, M Language
Whether you're a data analyst, developer, or report builder, this tutorial will help you catch gaps in your data with confidence.
00:00 Introduction
01:04 Creating a list of all dates
02:50 Solution 1- Merging
04:00 Solution 2- Appending
05:00 Solution 3 - List.Difference
