Mastering Excel Data Matching: A Comprehensive Guide with Step-by-Step Instructions

Data matching is a fundamental skill for anyone working with spreadsheets, especially in Excel. Whether you’re merging customer lists, reconciling financial records, or analyzing survey results, the ability to accurately match data points across different datasets is crucial for informed decision-making. This comprehensive guide will walk you through various techniques for matching data in Excel, providing detailed steps and instructions to help you become proficient in this essential skill.

Why is Data Matching Important?

Data matching, often referred to as data lookup, data reconciliation, or data merging, is the process of identifying corresponding records across two or more datasets. It’s not just about finding identical entries; often, you need to match data based on partial matches, approximate matches, or matches using multiple criteria. Here are some reasons why it’s a critical skill:

• Data Integration: Combining data from different sources into a single, cohesive view.
• Data Cleansing: Identifying duplicates and inconsistencies within your data.
• Data Validation: Ensuring the accuracy and completeness of your data.
• Analysis: Connecting related data points for more comprehensive analysis and reporting.
• Efficiency: Automating tasks that would otherwise be tedious and time-consuming.

Basic Data Matching Techniques

Let’s start with some of the foundational techniques for data matching in Excel. These methods are suitable for straightforward scenarios where a direct match is expected.

1. VLOOKUP (Vertical Lookup)

The `VLOOKUP` function is one of the most widely used functions for matching data based on a common column. It searches for a value in the first column of a table array and returns a value in the same row from another column.

Syntax:

=VLOOKUP(lookup_value, table_array, col_index_num, [range_lookup])

Arguments:

• lookup_value: The value you want to find in the first column of the table_array.
• table_array: The range of cells containing the table you want to search in. The first column of this range is where the lookup_value will be searched.
• col_index_num: The column number in the table_array from which you want to return the matching value. The first column is number 1.
• range_lookup: An optional argument specifying whether you want an exact match (`FALSE`) or an approximate match (`TRUE`). It’s generally recommended to use `FALSE` for most data-matching scenarios.

Step-by-Step Instructions:

1. Prepare your data: Ensure your two datasets are in separate sheets or separate areas of your same sheet. Have one common column which will be the `lookup_value`.
2. Select the cell: In the sheet where you need the matching data, select the cell where you want the matched value to appear.
3. Enter the `VLOOKUP` function: Type `=VLOOKUP(` into the formula bar.
4. Specify the `lookup_value`: Click on the cell containing the value you want to match (this is usually the key field in your data). For example, if the key is in cell A2, type A2. Add a comma.
5. Specify the `table_array`: Go to the sheet or range containing the data you are matching from, then select the entire table including the column with the `lookup_value` in the leftmost position. Be sure to use absolute references by pressing F4 to lock down the range (e.g. $A$1:$C$10). Add a comma.
6. Specify the `col_index_num`: Enter the column number (starting from 1) of the column in the table_array from which you want to return a match. Add a comma.
7. Specify the `range_lookup`: Type `FALSE` for an exact match.
8. Close the parenthesis and press Enter: Your formula should look something like this `=VLOOKUP(A2,Sheet2!$A$1:$C$10,3,FALSE)`.
9. Drag the formula down: To apply the same formula to the other cells, click on the small square at the bottom right of your cell and drag it down through the relevant rows.

Example:

Suppose you have two sheets, one with customer IDs and names (Sheet1), and another with customer IDs and purchase amounts (Sheet2). You want to match the purchase amount to each customer name based on the ID:

Sheet1:

Sheet2:

In Sheet1, in cell C2, you would enter the formula: `=VLOOKUP(A2,Sheet2!$A$2:$B$4,2,FALSE)`. This will return the purchase amount for customer ID 101. Then, drag this formula down to C3 and C4 to get all the matching values. The result will give you customer name and their amount. If any of the customer ids from sheet1 does not exist in sheet 2, the formula will return #N/A, which you can remove or change with additional `IFERROR` conditions.

2. HLOOKUP (Horizontal Lookup)

The `HLOOKUP` function is similar to `VLOOKUP`, but it searches for a value in the first *row* of a table array and returns a value in the same column from another row.

Syntax:

=HLOOKUP(lookup_value, table_array, row_index_num, [range_lookup])

The arguments are similar to `VLOOKUP`, but note that:

• The table_array is structured horizontally.
• The row_index_num is the number of the row from which to return a match.

The usage is very similar to `VLOOKUP`, with the key difference being the orientation of the data. If your data is organized with the lookup keys in the first row, `HLOOKUP` is the method to go.

3. INDEX and MATCH

The combination of `INDEX` and `MATCH` functions is more flexible than `VLOOKUP` and `HLOOKUP`. The `MATCH` function returns the position of a value in a range, and the `INDEX` function returns a value from a range based on its position.

Syntax:

=INDEX(array, row_num, [column_num])

=MATCH(lookup_value, lookup_array, [match_type])

Arguments:

• For INDEX, the array is the range of cells from which to return the value, the row_num is the row number (or column_num) where the value is, and the column_num is optional (if working with a one-dimensional array you may omit it)
• For MATCH, the lookup_value is the value to look for, the lookup_array is the range to search, and the match_type indicates whether an exact (`0`), approximate (`1`), or an approximate match below or equal to (`-1`). For most data matching scenarios, we’ll use `0` for an exact match.

Step-by-Step Instructions:

1. Select the cell: In the sheet where you need the matching data, select the cell where you want the matched value to appear.
2. Enter the `INDEX` function: Type `=INDEX(` into the formula bar.
3. Specify the array: Click on the column from where you want to return value. Be sure to lock the column with F4 for absolute reference (e.g. $B:$B). Add a comma.
4. Enter the `MATCH` function: Type `MATCH(` into the formula bar after the comma of `INDEX` function.
5. Specify the `lookup_value`: Click on the cell containing the value you want to match (this is usually the key field in your data). Add a comma.
6. Specify the `lookup_array`: Go to the sheet or range containing the data you are matching from, then select the column containing the `lookup_value`. Be sure to lock the column with F4 for absolute reference. Add a comma.
7. Specify the `match_type`: Type `0` for an exact match.
8. Close the parenthesis for both `MATCH` and `INDEX` and press Enter: Your formula should look something like this: `=INDEX(Sheet2!$B:$B,MATCH(A2,Sheet2!$A:$A,0))`.
9. Drag the formula down: Apply this formula to the other cells.

Example:

Using the same customer data as above, the formula in cell C2 of Sheet1 would be: `=INDEX(Sheet2!$B:$B,MATCH(A2,Sheet2!$A:$A,0))`.

Why `INDEX` and `MATCH` is Preferred over `VLOOKUP`:

• Flexibility: `INDEX` and `MATCH` do not require the lookup value to be in the leftmost column. You can match data based on any column in your table.
• Performance: In some large datasets, `INDEX` and `MATCH` can perform better than `VLOOKUP` as they are optimized and does not look at the entire range

Advanced Data Matching Techniques

Now, let’s dive into some more advanced techniques for handling complex data-matching scenarios.

1. Matching with Multiple Criteria using `INDEX` and `MATCH`

Sometimes, you need to match data based on multiple criteria. For example, you might need to match customer data based on both their name and location. This can be accomplished using an array formula with `INDEX` and `MATCH`.

Step-by-Step Instructions:

1. Create a helper column: In both datasets, add a helper column that concatenates the multiple criteria you want to match on. This involves combining the values from multiple columns into a single string. For instance, if you want to match on Customer Name and Location, your helper column could contain strings like “John Doe-New York.” The formula for concatenating would look like this in the first helper column of sheet 1: `=A2&”-“&B2` (assuming name is in column A and location is in column B)
2. Use the `INDEX` and `MATCH` formula: In the sheet where you want to match data, use the same INDEX and MATCH structure but match using helper columns. The formula will look like `=INDEX(Sheet2!$C:$C,MATCH(Sheet1!$D2,Sheet2!$D:$D,0))`, given that in sheet1 the helper column is located in column D and sheet2 helper column also in column D and want to return the value in C column.
3. Press Ctrl+Shift+Enter: If it is an array formula press Ctrl+Shift+Enter instead of just Enter. This will encapsulate the formula in curly braces and tell excel it is an array. This might not be necessary in later version of excel or if the version already handles it as a dynamic array.
4. Drag the formula down: Copy the formula through all your required cells.

Example:

Suppose you have two datasets, both with customer names and locations, but the purchase amount is in the second dataset, and you wish to match it based on both.

Sheet1:

Sheet2:

In both tables you would first create the helper column by concatenating customer name and location. This column will now be the matching key. Then use the formula above to get the match.

2. Matching with Approximate Matches using `VLOOKUP` and `XLOOKUP`

In some scenarios, you need to match data based on approximate matches. For instance, you might have a set of sales numbers and want to assign a commission tier based on predefined intervals. For the classic VLOOKUP, if there is no exact match for a value, the data needs to be sorted in ascending order for VLOOKUP to return a lower value for the `lookup_value` argument. In the more modern XLOOKUP however, an approximate match can be chosen even if the table is not sorted.

Syntax (VLOOKUP with Approximate Match):

=VLOOKUP(lookup_value, table_array, col_index_num, TRUE)

The table must be sorted in ascending order for approximate match to work correctly.

Syntax (XLOOKUP with Approximate Match):

=XLOOKUP(lookup_value, lookup_array, return_array, [if_not_found], [match_mode], [search_mode])

Arguments:

• lookup_value: The value you want to find in the lookup_array
• lookup_array: The range of cells that needs to be searched for lookup_value
• return_array: The range of cells that contains the values that will be returned
• if_not_found: (optional) The value to return if no match is found.
• match_mode: (optional) The type of match to perform, by default it is 0 for an exact match. Other values are: -1 for exact match or next smallest item, 1 for exact match or next larger item, 2 for wildcard match.
• search_mode: (optional) How the lookup is performed, by default the lookup starts from first to last. Other values are: -1 for lookup from last to first, 2 for binary search ascending order, -2 for binary search descending order.

Step-by-Step Instructions (VLOOKUP with Approximate Match):

1. Create a lookup table: Prepare a table with the lower bound of your intervals in ascending order in the first column, and the corresponding matching values in the second column.
2. Use the `VLOOKUP` function: Employ the `VLOOKUP` function with `TRUE` as the `range_lookup` argument. The syntax is the same as described above, the difference here is the argument `TRUE`. If not match, the function will return the closest value that is smaller.

Step-by-Step Instructions (XLOOKUP with Approximate Match):

1. Create a lookup table: Prepare a table with the lower bound of your intervals in one column, and the corresponding matching values in the adjacent column.
2. Use the `XLOOKUP` function: Employ the `XLOOKUP` function with -1 or 1 as the `match_mode` argument to get the next smaller or next bigger item. For a exact match with value 0, you do not need to specify match_mode, or can explicitly indicate 0.

Example (VLOOKUP):

Suppose you have the following commission tiers:

To find the commission tier for a sales amount of 1500, the formula would be `=VLOOKUP(1500,A1:B3,2,TRUE)` and the result would be Tier 2.

Example (XLOOKUP):

Using the same commission tier, the formula to find the commission tier using XLOOKUP would be: `=XLOOKUP(1500,A1:A3,B1:B3,,1)` or `=XLOOKUP(1500,A1:A3,B1:B3,-1)` which returns Tier 2 if using 1 and returns Tier 1 if using -1.

3. Using Power Query for Data Matching

Power Query (Get & Transform Data) is a powerful tool built into Excel that allows you to import and transform data from various sources. It’s an ideal option when you have complex matching tasks that require multiple steps.

Step-by-Step Instructions:

1. Import your data: Go to the “Data” tab, and use “From Table/Range” or other import options to import your datasets into Power Query.
2. Merge queries: In the Power Query Editor, select your primary query (sheet) and click “Merge Queries” from the “Home” tab.
3. Select the merge table: Choose the other query you want to match data from in the dialog box, specify the matching column(s), and choose a join kind (e.g., Left Outer, Inner). Left Outer will return all records from first table and matched values from the other table, inner will only return matches on both tables.
4. Expand columns: After merging, you can expand the columns from the second table to bring in the matching data.
5. Load data: Close and Load the transformed data back to a new worksheet in Excel.

Power Query is highly effective in handling large data sets and can handle more complex merge scenarios. It provides a GUI for merging data and allows you to perform other data transformation during the process.

Tips for Efficient Data Matching

• Data Cleaning: Before starting the matching process, clean your data, removing leading or trailing spaces, and addressing any inconsistencies. Data consistency is key to reliable matches.
• Data Validation: Double-check your matching results and ensure the returned values are accurate.
• Use Absolute References: For the table_array or range, use absolute references in your formulas (e.g. $A$1:$C$10), it will help when copying the formula to other cells.
• Error Handling: Utilize `IFERROR` function or other error handling techniques to deal with cases where no match can be found, it will return custom messages instead of error codes.
• Start with smaller sample: If you have massive sets of data, start with a small sample to make sure the formula works as expected.
• Use the Right Function: Choose the right function for the job. Use `VLOOKUP` or `HLOOKUP` for simple cases, `INDEX` and `MATCH` for more flexible and powerful lookups, `XLOOKUP` for enhanced features and flexibility, and Power Query for more complex merging scenarios.
• Performance Considerations: Large datasets can impact the performance of data-matching formulas. Consider using helper columns or Power Query if you are working with massive dataset.

Conclusion

Data matching in Excel is a vital skill that every data professional should master. By understanding and applying the techniques outlined in this guide, you can significantly improve your efficiency and accuracy in data analysis. Remember to start with the basics, progress to the advanced techniques, and always strive to improve your workflow by cleaning your data, validating the results, and using the right tools for the job. With practice, you’ll become proficient at seamlessly matching data across multiple datasets and unlocking the true power of your spreadsheets.