Performing data validation and error handling in Power Query involves several steps to ensure data integrity and manage errors effectively. Here's how you can do it:

Data Validation

1. Check for Null Values:
- Use the `Replace Values` feature to replace null values with a default value or remove them if necessary.
- Use the `Remove Rows` feature to remove rows with null values: `Home` tab > `Remove Rows` > `Remove Rows with Errors` or `Remove Blank Rows`.

2. Data Type Validation:
- Ensure each column has the correct data type.
- Select a column and go to the `Transform` tab > `Data Type` and choose the appropriate type (e.g., Text, Number, Date).

3. Conditional Column for Validation:
- Create a new conditional column that flags rows with invalid data.
- Go to the `Add Column` tab > `Conditional Column`.
- Define conditions that check for valid data (e.g., if a number column is within a certain range).

4. Custom Functions for Validation:
- Write custom functions to perform complex validation.
- Use the `Advanced Editor` to create custom M code functions that validate data based on your criteria.

Error Handling

1. Error Checking:
- Use the `Remove Errors` feature to eliminate rows with errors: `Home` tab > `Remove Rows` > `Remove Rows with Errors`.
- Alternatively, create a separate query that extracts rows with errors for review: `Add Column` > `Column From Examples` > `Extract Errors`.

2. Replace Errors:
- Replace errors with a default value using the `Replace Errors` feature.
- Select the column, then go to the `Transform` tab > `Replace Errors`.

3. Try and Otherwise Function:
- Use the `try` and `otherwise` functions in M code to handle errors gracefully.
- In the `Advanced Editor`, you can write code like:
```m
try [column] otherwise "Default Value"
```

4. Conditional Columns for Error Handling:
- Create a conditional column that identifies and flags errors.
- Go to `Add Column` > `Conditional Column` and set up conditions to check for errors.

Example of M Code for Validation and Error Handling

Here's an example of how you can use M code to handle errors and validate data:

```m
let
Source = Excel.Workbook(File.Contents("C:\path\to\file.xlsx"), null, true),
Data = Source{[Name="Sheet1"]}[Data],
// Replace null values with a default
ReplaceNulls = Table.ReplaceValue(Data, null, "Default Value", Replacer.ReplaceValue, {"Column1"}),
// Change data type and handle type errors
ChangeType = Table.TransformColumnTypes(ReplaceNulls, {{"Column1", type number}}),
// Handle type conversion errors
HandleErrors = Table.TransformColumns(ChangeType, {{"Column1", each try _ otherwise -1}}),
// Add a validation column
ValidationColumn = Table.AddColumn(HandleErrors, "Validation", each if [Column1] < 0 then "Error" else "Valid")
in
ValidationColumn
```

By implementing these techniques, you can ensure robust data validation and effective error handling in Power Query.