Merging queries (joins) in Excel - Deep Dive

Overview - Merging queries (joins)

What is it?

Merging queries, also called joins, means combining data from two or more tables based on a common column. In Excel, this is often done using formulas or Power Query to bring related information together. It helps you see all related data in one place without copying or typing it manually. This makes data analysis easier and more accurate.

Why it matters

Without merging queries, you would have to manually search and copy data from different tables, which is slow and error-prone. Merging lets you quickly combine data sets to answer questions like 'Which customers bought which products?' or 'What are the sales totals by region?' This saves time and helps make better decisions based on complete information.

Where it fits

Before learning merging queries, you should understand basic Excel tables, cell references, and simple formulas like VLOOKUP or INDEX/MATCH. After mastering merges, you can explore advanced data analysis tools like Power Query, PivotTables, and database concepts.

Mental Model

Core Idea

Merging queries is like matching puzzle pieces from different boxes by their shapes to create a complete picture.

Think of it like...

Imagine you have two address books: one with names and phone numbers, another with names and email addresses. Merging queries is like finding the same name in both books and putting their phone and email info together on one page.

Table A: Customers       Table B: Orders
┌─────────────┐       ┌─────────────┐
│ CustomerID  │       │ CustomerID  │
│ Name        │       │ OrderID     │
│ City        │       │ Product    │
└─────────────┘       └─────────────┘

Merge on CustomerID:
┌─────────────┬─────────┬─────────┐
│ CustomerID  │ Name    │ Product │
├─────────────┼─────────┼─────────┤
│ 101         │ Alice   │ Book    │
│ 102         │ Bob     │ Pen     │
└─────────────┴─────────┴─────────┘

Build-Up - 7 Steps

1

Foundation

Understanding tables and keys

Concept: Learn what tables and key columns are in Excel.

A table is a set of rows and columns with related data. A key column is a column that uniquely identifies each row, like CustomerID. Keys let you match rows between tables. For example, CustomerID in both a customer list and an order list helps link orders to customers.

Result

You can identify which columns to use to connect tables.

Knowing keys is essential because merging depends on matching rows by these unique identifiers.

2

Foundation

Basic lookup formulas for merging

Concept: Use simple formulas like VLOOKUP or INDEX/MATCH to merge data.

VLOOKUP searches for a value in the first column of a table and returns a value from another column. For example, =VLOOKUP(A2, Customers!A:C, 2, FALSE) finds the name for a CustomerID in A2. INDEX/MATCH is a more flexible alternative that can look left or right.

Result

You can pull matching data from one table into another.

Lookup formulas are the simplest way to merge data but have limits like only searching rightwards or needing sorted data.

3

Intermediate

Using Power Query to merge tables

🤔Before reading on: do you think merging with Power Query requires formulas or a visual interface? Commit to your answer.

Concept: Power Query offers a visual way to merge tables without formulas.

In Excel, Power Query lets you load tables and merge them by selecting matching columns. You choose the join type (like left join or inner join) and it creates a new combined table. This is easier and more powerful than formulas for big or complex data.

Result

You get a new table combining data from both sources based on your join choice.

Understanding Power Query merges helps handle large data sets and complex joins without formula errors.

4

Intermediate

Different join types explained

🤔Quick: Does an inner join keep unmatched rows or drop them? Commit to yes or no.

Concept: Learn the main join types: inner, left, right, and full outer joins.

Inner join keeps only rows with matches in both tables. Left join keeps all rows from the first table and matches from the second. Right join keeps all from the second and matches from the first. Full outer join keeps all rows from both tables, matching where possible.

Result

You can choose how to combine data depending on what you want to keep or exclude.

Knowing join types prevents losing important data or including unwanted rows in your merged results.

5

Intermediate

Handling duplicates and missing matches

🤔Before reading on: do you think duplicates in key columns cause errors or just extra rows? Commit to your answer.

Concept: Duplicates and missing keys affect merge results and need careful handling.

If keys repeat in one table, merges can create multiple rows for one key, expanding data unexpectedly. Missing keys cause blanks or errors in formulas. You can clean data by removing duplicates or filling missing keys before merging.

Result

Merged data is accurate and predictable without unexpected duplicates or blanks.

Understanding data quality issues helps avoid confusing merge results and errors.

6

Advanced

Combining multiple tables with nested merges

🤔Do you think you can merge more than two tables at once directly? Commit to yes or no.

Concept: You can merge more than two tables by merging pairs step-by-step.

Excel and Power Query merge two tables at a time. To combine three or more, merge two tables first, then merge the result with the next table, and so on. This lets you build complex combined data sets.

Result

You get a final table with data from all sources merged correctly.

Knowing how to chain merges expands your ability to analyze complex data from many sources.

7

Expert

Performance and formula limitations in merges

🤔Quick: Do you think large VLOOKUP formulas slow down Excel significantly? Commit to yes or no.

Concept: Merging with formulas can slow Excel on big data; Power Query is more efficient.

Formulas recalculate every change and can become slow with thousands of rows. Power Query processes data once and loads results, improving speed. Also, formulas have limits like VLOOKUP only searching rightwards and errors if keys are missing. Experts choose the right tool for scale and complexity.

Result

You understand when to switch from formulas to Power Query for merges.

Knowing tool limits helps maintain fast, reliable spreadsheets in real-world projects.

Under the Hood

Merging queries works by matching rows from different tables using a common key column. Formulas like VLOOKUP scan the lookup column to find the matching key and return related data. Power Query loads tables into memory, performs join operations based on the selected join type, and outputs a new combined table. Internally, joins compare keys row-by-row and decide which rows to keep or discard depending on the join type.

Why designed this way?

Merging was designed to solve the problem of scattered data across tables. Early Excel formulas like VLOOKUP were simple but limited, so Power Query was introduced to handle complex merges visually and efficiently. The design balances ease of use for beginners with power for advanced users, allowing both formula-based and GUI-based merges.

┌─────────────┐     match keys     ┌─────────────┐
│ Table A     │───────────────────▶│ Table B     │
│ CustomerID  │                   │ CustomerID  │
│ Name        │                   │ OrderID     │
└─────────────┘                   └─────────────┘
        │                               │
        │          join operation       │
        └─────────────┬─────────────────┘
                      ▼
             ┌─────────────────────┐
             │ Merged Table        │
             │ CustomerID          │
             │ Name                │
             │ OrderID             │
             └─────────────────────┘

Myth Busters - 4 Common Misconceptions

Quick: Does VLOOKUP work if the lookup column is not the first column? Commit to yes or no.

Common Belief: VLOOKUP can find data even if the lookup column is not the first column in the table.

Reality: VLOOKUP only searches the first column of the table array for the lookup value. If the key is not in the first column, VLOOKUP will not work correctly.

Why it matters: Using VLOOKUP with the wrong column causes incorrect or missing data, leading to wrong analysis.

Quick: Does a left join keep all rows from the second table? Commit to yes or no.

Common Belief: A left join keeps all rows from both tables regardless of matches.

Reality: A left join keeps all rows from the first (left) table only, adding matching rows from the second (right) table. Unmatched rows from the right table are excluded.

Why it matters: Misunderstanding join types leads to missing data or unexpected rows in merged results.

Quick: Can Power Query merges update automatically when source data changes? Commit to yes or no.

Common Belief: Once merged, Power Query tables update automatically without any user action.

Reality: Power Query merges require manual refresh to update merged data after source changes.

Why it matters: Assuming automatic updates can cause users to work with outdated data unknowingly.

Quick: Does merging with formulas always produce a single combined table? Commit to yes or no.

Common Belief: Using formulas like VLOOKUP merges tables into one combined table automatically.

Reality: Formulas pull data into existing tables but do not create a new combined table automatically; you must set up the layout manually.

Why it matters: Expecting automatic table creation can cause confusion and extra manual work.

Expert Zone

1

Power Query merges can handle complex data types and transformations during the merge, not just simple key matching.

2

Using INDEX/MATCH with multiple criteria allows more flexible merges than VLOOKUP, especially when keys are composite.

3

Performance of merges depends heavily on data size and formula complexity; caching and query folding in Power Query optimize this.

When NOT to use

Avoid formula-based merges for very large data sets or complex joins; use Power Query or database tools instead. For real-time dynamic merges, consider Excel's Data Model with relationships or external databases.

Production Patterns

Professionals use Power Query merges to prepare clean, combined data sets before analysis or reporting. They often chain multiple merges and apply filters or transformations in one query. Formula merges are common for small, quick lookups or dashboards.

Connections

Relational Databases

Merging queries in Excel is similar to SQL JOIN operations in databases.

Understanding Excel merges helps grasp how databases combine tables, enabling smoother transition to database querying.

Data Cleaning

Merging requires clean, consistent keys, linking it closely to data cleaning practices.

Knowing merging depends on data quality highlights the importance of cleaning data before analysis.

Supply Chain Management

Merging data from suppliers, orders, and inventory mirrors how supply chains integrate information.

Seeing merges as data integration helps understand complex real-world systems like supply chains.

Common Pitfalls

#1 Using VLOOKUP with unsorted data and approximate match.

Wrong approach:

=VLOOKUP(A2, Customers!A:C, 2, TRUE)

Correct approach:

=VLOOKUP(A2, Customers!A:C, 2, FALSE)

Root cause:

Confusing the last argument TRUE (approximate match) with FALSE (exact match) causes wrong matches.

#2 Merging tables with duplicate keys without handling duplicates.

Wrong approach:

Merging tables directly in Power Query without removing duplicates.

Correct approach:

Remove duplicates in key columns before merging or use grouping to handle duplicates.

Root cause:

Not recognizing that duplicate keys cause multiple rows and unexpected data expansion.

#3 Not refreshing Power Query after source data changes.

Wrong approach:

Assuming merged table updates automatically after editing source tables.

Correct approach:

Manually refresh Power Query queries or set automatic refresh options.

Root cause:

Misunderstanding that Power Query loads data snapshots, not live links.

Key Takeaways

Merging queries combines data from different tables by matching key columns to create a unified view.

Simple merges can be done with formulas like VLOOKUP, but Power Query offers more power and flexibility for complex or large data.

Choosing the right join type (inner, left, right, full) controls which rows appear in the merged result.

Data quality, especially unique and consistent keys, is critical for accurate merges.

Understanding tool limits and performance helps choose the best method for merging in real-world Excel projects.