What is Data Validation: Types, Importance and Benefits of Data Validation

Isaac Adeyemi

2 years ago

What is data Validation?

Data Validation is the concept of using data integrity principles to ensure measures conform to defined business rules or constraints. Data validation is an essential tool for spreadsheet management that ensures the accuracy, consistency, and integrity of data. Data validation allows users to define rules and constraints that data must meet before it can be entered into a spreadsheet.

This article will provide an overview of data validation, its benefits, and how to set it up in a spreadsheet.

Importance of data validation in spreadsheet management

Data validation is an essential tool for managing spreadsheets because it helps to ensure the accuracy, consistency, and integrity of data. Without data validation, it’s easy to make mistakes, enter incorrect data, or overlook inconsistencies in data.

By implementing data validation, users can establish rules and constraints that data must meet before it can be entered into a spreadsheet. This helps to avoid data entry errors, reduce mistakes, and ensure consistency in data entry. For example, data validation can be used to limit the range of values that can be entered in a cell or to require data to be entered in a specific format.

Data validation also improves data accuracy by preventing incorrect data from being entered into a spreadsheet. For example, if a user attempts to enter a date outside of a specified range, an error message will be triggered, and the data will not be accepted until it meets the validation criteria.

In addition to improving data accuracy and consistency, data validation can enhance data analysis. By ensuring that data is entered consistently and accurately, users can rely on their data for more accurate analysis and decision-making.

Types of Data Validation

In this section, we will discuss the six different types of data validation, which include data type, data range, data constraint, data consistency, data structure, and code validation. While it may not be necessary to perform all of these validations, it is essential to verify that the data has been validated before beginning work on a dataset. Doing so helps to ensure data integrity and gives confidence that the data being used is accurate and error-free.

Data Type

Purpose: To verify that the data matches the data type specified for a field.

Example: Numeric data type for school grades 1-12.

Limitations: The data value 13 would pass the data type validation, but it would not be acceptable for school grades. In this case, data range validation should also be performed.

Data Range

Purpose: To verify that the data falls within an acceptable range of values specified for a field.

Example: School grades should be between 1 and 12.

Limitations: The data value 11.5 would be within the data range and would pass the data type validation, but it would not be acceptable for school grades. In this case, data constraint validation should also be performed.

Data Constraint

Purpose: To verify that the data meets certain conditions or criteria for a field, including the type of data entered and other field attributes, such as the number of characters.

Example: Content constraint for school grades 1-12 to only allow whole numbers.

Limitations: The data value 13 is a whole number and would pass the content constraint validation, but it would not be acceptable for school grades. In this case, data range validation should also be performed.

Data Consistency

Purpose: To verify that the data makes sense in the context of related data.

Example: Shipping dates for products cannot be earlier than the production dates.

Limitations: Data consistency alone does not ensure that the data is correct or accurate.

Data Structure

Purpose: To verify that the data conforms to a prescribed structure.

Example: Web pages must follow a specific structure to be displayed correctly.

Limitations: A data structure alone does not ensure that the data is correct or accurate.

Code Validation

Purpose: To verify that the application code systematically performs any of the previously mentioned validations during user data input.

Example: Validating that only one data type is allowed or checking for data range.

Limitations: Code validation may not cover all possible variations of data input.

There are also four types of data validation options available in spreadsheet software like Google sheet and Excel:

Input messages: Input messages provide helpful tips to users on what data should be entered into a specific cell. Input messages can be used to provide guidance on data entry, explain the purpose of a cell or alert users to specific requirements.
Error alerts: Error alerts are triggered when data entered into a cell violates data validation criteria. When an error alert is triggered, users are alerted with an error message that informs them of the mistake and provides guidance on how to correct it.
Data validation criteria: Data validation criteria define the rules and restrictions that data must meet before it can be entered into a cell. For example, data validation criteria can be used to limit the range of values that can be entered in a cell, restrict data to specific formats or data types, or prevent duplicates from being entered.
Custom data validation rules: Custom data validation rules allow users to create their own unique data validation rules that fit their specific needs. This option is useful when pre-defined data validation rules do not meet the user’s requirements. With custom data validation rules, users can create rules that check for specific data patterns, combinations of data, or other unique criteria.

In conclusion, data validation is essential to ensure data accuracy and consistency. By understanding the different types of data validation available, you can choose the appropriate validation method for your dataset. Remember to perform data validation regularly to avoid errors and maintain data integrity.

Step-by-step guide on how to set up data validation in Excel

Setting up data validation in Excel is a straightforward process that involves a few simple steps. Here is a step-by-step guide on how to set up data validation in Excel:

Step 1: Select the cell or range of cells that you want to apply data validation to.

Step 2: Click on the “Data” tab in the ribbon menu.

Step 3: Click on “Data Validation” in the “Data Tools” group.

Step 4: In the “Data Validation” dialog box, choose the type of validation that you want to apply from the “Allow” drop-down list. For example, you can choose to allow only whole numbers, dates within a specific range, or data from a list.

Step 5: Depending on the type of validation you choose, you will need to specify additional criteria. For example, if you choose to allow only whole numbers, you will need to specify the range of values that are allowed.

Step 6: If you want to provide an input message to users when they select a cell that has data validation applied to it, go to the “Input Message” tab, and enter the text that you want to display.

Step 7: If you want to display an error message when users enter invalid data, go to the “Error Alert” tab, and enter the text that you want to display.

Step 8: Click “OK” to apply the data validation to the selected cell or range of cells.

Step-by-step guide on how to set up data validation in Google Sheets

Data validation is a useful feature in Google Sheets that allows users to control and restrict the type of data that can be entered in a cell or a range of cells.

Here is a step-by-step guide on how to set up data validation in Google Sheets:

Select the cell or range of cells where you want to apply data validation.
Click on the “Data” menu at the top of the screen.
Select “Data validation” from the dropdown menu. This will open the data validation dialog box.
In the “Criteria” section, select the type of data validation you want to apply. The available options include:
- List from a range: This option allows you to create a dropdown list of options based on a range of cells in your sheet.
- List of items: This option allows you to create a dropdown list of fixed values.
- Number: This option allows you to set criteria for numeric data, such as a minimum and maximum value.
- Text: This option allows you to set criteria for text data, such as a specific length or pattern.
- Date: This option allows you to set criteria for date data, such as a specific date or range of dates.
- Custom formula: This option allows you to use a custom formula to validate the data.
Depending on the type of data validation you selected, you will need to provide additional information. For example, if you selected “List from a range,” you will need to specify the range of cells containing the list of options.
In the “On invalid data” section, you can choose how Google Sheets should handle invalid data. The available options include:
- Reject input: This option prevents the user from entering invalid data.
- Show warning: This option displays a warning message when the user enters invalid data, but allows them to override it.
- Do not show warning: This option allows the user to enter invalid data without any warning message.
Click “Save” to apply the data validation to the selected cell or range of cells.

That’s it! You have successfully set up data validation in Google Sheets. You can now test the data validation by trying to enter data that does not meet the specified criteria.

Overall, setting up data validation in Google sheets and Excel is a quick and simple process that can help to improve the accuracy, consistency, and integrity of data entered into a spreadsheet. By using data validation, users can ensure that data is entered correctly and consistently, and avoid common data entry errors.

Walkthrough of the different options available for setting up data validation

When setting up data validation in Excel, there are several options available to customize the validation rules and messages. Here is a walkthrough of the different options available for setting up data validation:

Allow: This dropdown menu provides a list of different types of data validation that can be applied, such as whole numbers, decimals, dates, times, and text length.
Data: This field allows you to enter a range of valid data, such as a list of allowed values or a range of numbers.
Criteria: This field allows you to specify additional criteria for the validation rule. For example, if you choose “between” in the Allow dropdown menu, you will need to specify the range of values that are allowed.
Input Message: This tab allows you to provide a message to users when they select a cell that has data validation applied to it. This message can provide helpful tips or instructions on how to enter data correctly.
Error Alert: This tab allows you to provide an error message to users when they enter invalid data. There are three types of error messages: Stop (prevents the user from entering invalid data), Warning (displays a warning message but allows the user to continue), and Information (displays an information message but allows the user to continue).
Show error alert after invalid data is entered: This checkbox allows you to choose whether to display the error alert message immediately when invalid data is entered, or only when the user tries to leave the cell.
Error message: This field allows you to enter the text of the error message that will be displayed when invalid data is entered.

By customizing these options, you can create powerful data validation rules that ensure data integrity and accuracy. Additionally, by providing input messages and error messages, you can help users to enter data correctly and avoid common data entry errors.

Examples of Data Validation in Action

Here are some examples of data validation in action:

Restricting data entry to a specific list: Suppose you have a spreadsheet that tracks employee information, and you want to ensure that users only enter valid departments. To accomplish this, you can use data validation to restrict data entry to a list of valid department names. This will prevent users from entering typos or other errors that could cause problems later on.
Limiting data entry to a range of values: Imagine you have a spreadsheet that tracks sales data, and you want to ensure that users only enter valid sales amounts. To accomplish this, you can use data validation to limit data entry to a specific range of values. For example, you could set up a validation rule that only allows values between $0 and $10,000. This will prevent users from entering values that are outside of the expected range.
Preventing duplicates: Let’s say you have a spreadsheet that tracks customer orders, and you want to ensure that each order number is unique. To accomplish this, you can use data validation to prevent users from entering duplicate order numbers. This will help to avoid confusion and ensure that orders are processed correctly.
Ensuring data consistency: Suppose you have a spreadsheet that tracks customer information, and you want to ensure that the state entered for each customer matches the zip code. To accomplish this, you can use data validation to ensure that the zip code entered in one field matches the state entered in another field. This will help to ensure data consistency and accuracy.
Providing data entry guidance: Finally, data validation can be used to provide helpful tips or instructions to users when entering data. For example, if you have a spreadsheet that tracks employee hours worked, you can use data validation to provide a message that reminds users to enter hours in decimal format (e.g. 7.5 for 7 and a half hours). This can help to prevent common data entry errors and improve data accuracy.

Benefits of Data Validation

Data validation is a powerful tool that can help to improve the accuracy, consistency, and reliability of data entered into a spreadsheet. Here are some of the key benefits of using data validation:

Improved data accuracy: By using data validation, users are prevented from entering incorrect or invalid data. This can help to ensure that data is accurate and reliable, which is critical for making informed decisions.
Reduced data entry errors: Data validation can help to reduce common data entry errors, such as typos, spelling mistakes, or incorrect formatting. This can help to save time and improve the quality of data entered into a spreadsheet.
Increased data consistency: By enforcing consistent data entry practices, data validation can help to ensure that data is consistent and reliable. This can make it easier to analyze and compare data across different spreadsheets or databases.
Better data analysis: By ensuring that data is accurate and consistent, data validation can help to improve the quality of data analysis. This can help to identify trends, patterns, and insights that might otherwise be missed.
Reduced data processing time: By preventing incorrect or invalid data from being entered into a spreadsheet, data validation can help to reduce the time and effort required to process and analyze data. This can help to improve productivity and save time.

Best Practices for Data Validation

Here are some best practices to follow when using data validation in a spreadsheet:

Determine the data validation rules: Before applying data validation, determine the specific data validation rules that are needed to ensure data accuracy and consistency. This may involve limiting data entry to a specific range of values, or setting up rules to prevent duplicates or incorrect formatting.
Keep it simple: It’s important to keep data validation rules simple and straightforward. Avoid creating overly complex rules that can be confusing or difficult to follow. Clear and concise data validation rules are easier to understand and can be more effective in improving data accuracy.
Test data validation rules: Once data validation rules have been applied, it’s important to test them to ensure that they are working as expected. This can help to identify any issues or errors that need to be corrected before the spreadsheet is used for data analysis or reporting.
Provide helpful error messages: If data validation rules are violated, provide clear and helpful error messages that explain why the data is invalid and how to correct it. This can help to avoid frustration and confusion among users.
Document data validation rules: It’s important to document data validation rules to ensure consistency and transparency. This can be done by creating a data validation policy or by including a description of the rules in the spreadsheet itself. Documentation can also help to ensure that data validation rules are followed consistently over time.
Update data validation rules as needed: As data changes or new data sources are added to a spreadsheet, it may be necessary to update data validation rules to ensure that they remain accurate and effective. Regularly reviewing and updating data validation rules can help to maintain data accuracy and consistency over time.

Overall, following these best practices can help to ensure that data validation is effective in improving data accuracy, consistency, and reliability in a spreadsheet.