VBA With Power Query: Maximize Efficiency and Automate Your Data Processes in Excel (with VBA code)

What are the benefits of using VBA with Power Query?

Using VBA in conjunction with Power Query can provide significant benefits, especially when you need to automate complex workflows, integrate data from multiple sources, or perform advanced transformations programmatically. Here are the key benefits of using VBA over just using Power Query directly:

  1. Automation and Repetition:
    • Automation: VBA allows you to automate repetitive tasks, such as importing data from multiple files, applying the same transformations, and saving the results in a consistent format.
    • Scheduling: You can schedule VBA macros to run at specific times, ensuring data is updated automatically.
  2. Customization and Flexibility:
    • Custom Functions: VBA enables you to create custom functions and procedures that can be used within Power Query M code.
    • Dynamic Parameters: You can pass dynamic parameters to Power Query queries using VBA, allowing for more flexible data processing. This alone is a huge benefit!!
  3. Integration with Other Applications:
    • Interoperability: VBA can interact with other applications and services, such as databases, web APIs, and email clients, enhancing the capabilities of Power Query.
    • Data Export: You can use VBA to export data to various formats, such as PDF, CSV, or other Excel files, after it has been processed by Power Query.
  4. Complex Logic and Control:
    • Conditional Logic: VBA provides powerful conditional logic and control structures that can be used to handle complex data processing tasks.
    • Error Handling: You can implement robust error handling in VBA to manage unexpected issues during data processing.
  5. User Interface:
    • Custom UserForms: VBA allows you to create custom user interfaces (UserForms) for data entry and interaction, making it easier for users to perform complex tasks without needing to know Power Query M code.
    • Buttons and Macros: You can add buttons and macros to Excel worksheets to trigger VBA scripts, making it user-friendly.
  6. Advanced Data Manipulation:
    • Data Cleaning: VBA can be used for advanced data cleaning tasks, such as removing specific patterns, handling missing data, and normalizing data formats.
    • Data Transformation: VBA can perform complex transformations that might be difficult or impossible to achieve with Power Query alone.
  7. Version Control and Collaboration:
    • Version Control: VBA code can be version-controlled using tools like Git, allowing for better collaboration and tracking changes.
    • Shared Macros: You can share VBA macros with your team, ensuring consistency in data processing workflows. This can be especially helpful for vacation coverage or spreading the workload among multiple team members!
  8. Performance Optimization:
    • Efficiency: For large datasets, VBA can be more efficient in certain scenarios, especially when combined with Power Query for initial data loading and filtering.
    • Resource Management: VBA can manage system resources more effectively, ensuring smooth performance during data processing.

When to Use VBA Over Power Query

  • Complex Workflows: When you need to perform a series of complex transformations and data manipulations that are difficult to achieve with Power Query alone.
  • Integration with Other Systems: When you need to integrate Excel with other applications, databases, or web services.
  • Automated Reporting: When you need to automate the generation of reports and dashboards based on dynamic data sources.
  • Custom User Interfaces: When you need to create custom user interfaces for data entry and interaction.
  • Advanced Error Handling: When you need robust error handling and logging for data processing tasks.

When to Use Power Query Alone

  • Simple Data Transformation: When you need to perform simple data transformations and cleaning tasks.
  • Data Visualization: When you need to create dynamic data visualizations and dashboards.
  • Data Integration: When you need to integrate and combine data from multiple sources without complex logic.
  • Data Refresh: When you need to refresh data regularly from external sources.
  • Data Transformation: Power Query allows for complex data transformations, such as filtering, merging, and aggregating data.
  • Refreshable Data: Data imported using Power Query can be easily refreshed to update with new data.
  • Scalability: Power Query is better suited for larger datasets and more complex data processing tasks.

VBA with Power Query Code Samples with Explanations

Use Case: Importing Data from CSV Files Using Power Query

Power Query is a more advanced and flexible tool for data import and transformation in Excel. It allows for more complex data transformations and can handle larger datasets more efficiently. Here’s how you can use VBA to import a CSV file using VBA with Power Query.

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Explanation of Power Query VBA Code

  1. File Path and Connection Name:
    • filePath is the path to your CSV file
    • connName is the name of the Power Query connection.
  2. Delete Existing Connection:
    • The code checks if the connection already exists and deletes it to avoid conflicts.
  3. Create New Power Query Connection:
    • The Queries.Add method creates a new Power Query connection.
    • The Formula parameter specifies the Power Query M code to import and transform the CSV file.
  4. Load Query into Worksheet:
    • A new worksheet is created, and the query is loaded into it using LoadFromText

Use Case: Importing and Transforming Data from an Excel File Using Power Query and VBA

Objective: Import data from a specific worksheet in an Excel file, filter out rows with specific criteria, perform some transformations, and load the cleaned data into a new worksheet.

Preparation:

  1. Prepare the Source Excel File:
    • Ensure your source Excel file is located at a known path, e.g., C:\Data\source_data.xlsx.
    • Ensure the data is in a worksheet named SalesData.
  2. VBA Code to Import and Transform Data Using Power Query:

Explanation of the VBA Code

  1. Set File Path, Workbook Name, Sheet Name, and Names:
    • sourceFilePath is the path to your source Excel file.
    • sourceWorkbookName is the name of the source Excel file.
    • sourceSheetName is the name of the worksheet containing the data.
    • connName is the name of the initial Power Query connection.
    • queryName is the name of the transformed Power Query query.
  2. Delete Existing Connection and Query:
    • The code checks if the connection and query already exist and deletes them to avoid conflicts.
  3. Create a New Power Query Connection:
    • The Queries.Add method creates a new Power Query connection to import data from the specified worksheet in the Excel file.
    • The Formula parameter specifies the Power Query M code to import the data.
  4. Create a New Power Query Query for Transformation:
    • This query uses the initial connection as its source.
    • It skips the first row (assuming headers).
    • It removes duplicates based on specified columns.
    • It filters rows where Sales is greater than 100.
    • It sorts the filtered rows by Date in ascending order.
    • It adds a new column TotalSales calculated as Sales * Quantity.
  5. Load the Transformed Query into a New Worksheet:
    • A new worksheet is created, and the transformed query is loaded into it using LoadFromText.
  6. Format the Worksheet:
    • The code automatically fits the columns and applies a table style for better readability.

Detailed Steps

  1. Prepare the Source Excel File:
    • Update the path to match your source Excel file.
    • Ensure the data is in a worksheet named SalesData, or update that variable to match your data.
  2. Open VBA Editor:
    • Press Alt + F11 to open the VBA editor.
  3. Insert a New Module:
    • In the VBA editor, go to Insert > Module to create a new module.
  4. Copy and Paste the VBA Code:
    • Copy the above VBA code and paste it into the module.
  5. Run the Macro:
    • Close the VBA editor and return to Excel.
    • Press Alt + F8, select ImportAndTransformExcelDataWithPowerQuery, and click Run.
  6. View the Results:
    • A new worksheet named TransformedData will be created, showing the imported and transformed data.

Additional Tips

  • Customizing Columns:
    • You can customize the column names and the criteria for filtering and sorting based on your specific dataset.
  • Handling Different Workbooks and Sheets:
    • Adjust the sourceFilePath, sourceWorkbookName, and sourceSheetName variables to match your source file and worksheet.
  • Error Handling:
    • Add error handling to manage potential issues, such as file not found or invalid data.

Example: Combining VBA with Power Query for Automation of Reporting

Here’s a more detailed example that combines VBA with Power Query to automate a complex data processing workflow that can automate data reporting from start to finish, including transforming the data and outputting a user-friendly report.

Use Case: Automating Data Import, Transformation, and Reporting

Objective: Import data from multiple Excel files, perform transformations, and generate a consolidated report.

VBA Code:

Explanation of the VBA Code

  1. Set Folder Path and Names:
    • folderPath is the path to the folder containing the Excel files.
    • connName is the name of the initial Power Query connection.
    • queryName is the name of the transformed Power Query query.
  2. Delete Existing Connection and Query:
    • The code checks if the connection and query already exist and deletes them to avoid conflicts.
  3. Initialize a New Worksheet:
    • A new worksheet named ConsolidatedData is created to store the consolidated data.
  4. Loop Through Excel Files:
    • The code loops through all Excel files in the specified folder.
    • For each file, it creates a new Power Query connection to import data from the SalesData worksheet.
  5. Create a New Power Query Query for Transformation:
    • This query uses the initial connection as its source.
    • It skips the first row (assuming headers).
    • It removes duplicates based on specified columns.
    • It filters rows where Sales is greater than 100.
    • It sorts the filtered rows by Date in ascending order.
    • It adds a new column TotalSales calculated as Sales * Quantity.
  6. Load the Transformed Query into the Consolidated Worksheet:
    • The transformed data is loaded into the ConsolidatedData worksheet.
  7. Delete the Power Query Connection and Query:
    • After processing each file, the connection and query are deleted to clean up.
  8. Format the Worksheet:
    • The code automatically fits the columns and applies a table style for better readability.

Conclusion

Using VBA in conjunction with Power Query provides a powerful combination for automating and managing complex data workflows. While Power Query is excellent for data transformation and integration, VBA offers the flexibility and control needed for advanced automation and integration tasks. By combining these tools, you can create robust and efficient data processing solutions.

Feel free to comment other examples you would like to see as we continue to explore automation of workflows via both VBA and Power Query!

Hosting Your Own AI/Local LLM On Your PC (For Free)!

Hosting your own AI local LLM (Large Language Model) can offer several benefits, especially for individuals and organizations looking to leverage advanced AI capabilities while maintaining control and security. Here are some key advantages:

Control and Customization:

  • Tailored Solutions: Customize the model to fit specific business needs, industries, or datasets.
  • Data Privacy: Ensure that sensitive data remains within your control and is not shared with external providers.

Security:

  • Data Security: Protect sensitive information by hosting the model on-premises or in a secure cloud environment under your control.
  • Compliance: Meet regulatory and compliance requirements by having full control over data handling and model deployment.

Latency and Performance:

  • Reduced Latency: Host the model closer to where it is needed, reducing latency and improving response times.
  • Optimized Performance: Fine-tune the model and infrastructure for optimal performance tailored to your specific use case.

Cost Efficiency:

  • Long-term Savings: While initial setup costs can be high, hosting your own model can be more cost-effective in the long run, especially for large-scale deployments.
  • Avoid Vendor Lock-in: Reduce reliance on third-party services and potential vendor lock-in, giving you more flexibility in choosing solutions.

Scalability:

  • Flexible Scaling: Easily scale the model and infrastructure to meet changing demands without relying on third-party providers.
  • Resource Allocation: Allocate resources more efficiently based on your specific needs and budget.

Innovation and Research:

  • Advanced Research: Engage in cutting-edge research and development by leveraging the full capabilities of the model and infrastructure.
  • Experimentation: Conduct experiments and iterate on models without the constraints of third-party services.

Integration:

  • Seamless Integration: Integrate the model with existing systems and workflows more easily, ensuring a cohesive and efficient operation.
  • Custom APIs: Develop custom APIs and interfaces tailored to your specific requirements.

Resilience and Reliability:

  • Uptime: Ensure high availability and uptime by managing the infrastructure directly.
  • Disaster Recovery: Implement robust disaster recovery and backup strategies to protect against data loss and downtime.

By hosting your own LLM, you gain significant control over your AI infrastructure, enabling you to tailor solutions to your specific needs while maintaining security and performance. Read on as we walk through the process together.

Instructions (Windows)

  • Download Ollama. Head on over to ollama.com and download for Windows.
  • Install the application.
host your own local LLM - installation image for Ollama.
  • In the meantime, head over to the models page on the Ollama website and read through them to decide which you would like to install. Each model has a command to install it next to the tags. In the example below, it is ollama run llama3.3; copy this command.
  • Once Ollama is installed, start the application from the Start menu.
  • Open a command prompt (Windows logo key + R, type cmd and hit enter).
  • When the command prompt window opens, paste the command you copied from the model page and hit enter.
  • Close Ollama by typing /bye and hitting enter.
  • Next, download the appropriate version of Docker Desktop for your computer.
  • Go to the Open UI github here and scroll to the installation instructions.
  • Copy the “If Ollama is on your computer” command.
  • Run this command in the command prompt. The package is large and may take several minutes to download and install.
  • After the installation is complete, go to the Docker application and note the open-webui container.
  • In your browser, head to http://localhost:3000/
  • Note: On my machine, I had to stop and restart the Docker container the first time; if you are having an issue, try that first.
  • Select the model at the top.
  • You now have a lovely interface to interact with your model! The possibilities are endless.

Errors in Excel – Identifying and Overcoming Them Quickly!

Common Errors in Excel and How to Fix Them

Excel is a powerful tool, but it’s not without its quirks. Anyone who has spent time working with spreadsheets has encountered those frustrating error messages. Whether you’re a beginner or an experienced user, understanding and resolving these errors is crucial for accurate data analysis. In this article, we will explore some of the most common Excel errors and provide detailed solutions to fix them.

1. #VALUE! Error: Understanding Invalid Data Types

The #VALUE! error occurs when Excel can’t recognize the data type in a formula or function. This error often happens when you’re trying to perform calculations with incompatible data types.

To fix this error, double-check your formulas and ensure that all the data types are compatible. For example, make sure you’re not trying to perform mathematical operations on text cells without converting them to numbers first.

2. #REF! Error: Dealing with Invalid Cell References

The #REF! error indicates an invalid cell reference, often caused by deleting or moving cells that are referred to in formulas. This error can mess up your entire spreadsheet if not addressed promptly.

To fix #REF! errors, carefully review your formulas and check if any cell references are no longer valid. Update the formulas to use the correct cell references, or adjust your data ranges to include the appropriate cells.

errors in excel, excel error, help me; person pressing button under help me sgh

Photo by Mikhail Nilov on Pexels.com

3. #DIV/0! Error: Handling Division by Zero

The #DIV/0! error occurs when you’re trying to divide a number by zero. Excel cannot perform this operation, and it displays this error to indicate the problem.

To avoid #DIV/0! errors, you can use the IF function to check if the divisor is zero before performing the division. For example, you can modify your formula like this:

=IF(B2<>0, A2/B2, "Divide by Zero Error")

This formula checks if cell B2 is not zero. If it is, it performs the division; otherwise, it displays a custom error message.

4. #NAME? Error: Fixing Unrecognized Functions or Formulas

The #NAME? error occurs when Excel doesn’t recognize a function or formula name in a cell. This can happen due to misspellings, missing quotation marks, or incorrect syntax.

To fix #NAME? errors, double-check the spelling and syntax of your functions and formulas. Ensure that all function names are spelled correctly and are accompanied by the necessary parentheses and arguments.

5. #N/A Error: Handling Not Available or Missing Data

The #N/A error stands for “Not Available” and occurs when Excel can’t find the value you’re looking for, often in functions like VLOOKUP or MATCH.

To handle #N/A errors, you can use the IFERROR function to display a custom message or value when an error occurs. For instance:

=IFERROR(VLOOKUP(A2, Table, 2, FALSE), "Not Found")

In this formula, if the VLOOKUP function returns an error, it will display “Not Found” instead of #N/A.

6. #NUM! Error: Dealing with Invalid Numerical Values

The #NUM! error in Excel occurs when a numerical calculation is invalid, such as taking the square root of a negative number.

To fix #NUM! errors, review the mathematical operations in your formulas. Check for any calculations that might result in negative numbers where they are not allowed or other mathematically impossible operations.

7. Errors in Excel – Prevention Techniques: Data Validation and Cell Auditing

Preventing errors is as important as fixing them. Excel offers various tools to help you prevent errors before they occur. One such tool is data validation, which allows you to set rules for the type and range of data that can be entered into a cell. By using data validation, you can significantly reduce the likelihood of invalid data causing errors in your spreadsheets.

Another helpful feature is cell auditing, which enables you to trace the precedents and dependents of a cell. By understanding how cells are connected in your spreadsheet, you can identify potential sources of errors and correct them proactively.

8. Excel’s Built-in Error Checking Tools: How to Use Them Effectively

Excel provides built-in error checking options that can automatically detect and highlight potential errors in your spreadsheet. To access these options, go to the “Formulas” tab, click on “Error Checking,” and choose “Error Checking Options.”

Here, you can customize the types of errors Excel should check for and how it should alert you. By utilizing these built-in tools, you can quickly spot errors and address them before they cause significant issues in your calculations.

In conclusion, mastering the art of handling common Excel errors is essential for anyone working with spreadsheets. By understanding the causes of these errors and implementing the provided solutions, you can ensure the accuracy and reliability of your Excel-based analyses. Additionally, utilizing preventive measures and Excel’s error checking tools will empower you to create error-free spreadsheets, saving you time and frustration in your data-driven tasks.

Remember, practice makes perfect. The more you work with Excel and encounter these errors in Excel, the more adept you’ll become at identifying and resolving them efficiently. Happy Excel-ling!

Convert Date in Access – Serial Number, Text String, First of Month, End of Month, etc.

Convert Date In Access – Serial Number, Text Date, First of Month, End of Month/last day of month.  MS Access will not automatically convert dates into different types, so this post will assist you with doing so quickly. To begin, you will create a new field in your query, and then continue with the conversion below that applies in your scenario. 

Helpful hint: Substitute [yourdate] with the name of the field that you are converting.

To convert a date in the date/time format to the serial number (7/1/2019 to 43647), use:

Cdbl ([yourdate])

———————————–

To convert a date in the serial number format to date/time format (43647 to 7/1/2019), use:

Cdate ([yourdate])

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To convert a text or string date to the date/time format, try:

DateValue ([yourdate])

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To convert a date to the first day of the month:

DateSerial (year([yourdate]),month([yourdate]),1)

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To convert a date to the last day of the month:

DateSerial (year([yourdate]),month([yourdate])+1,1)-1

———————————-

You can also convert a date/timeformat to a string – here is one example:

Format([yourdate],”mmmmyyyy”)

This would render 7/1/19 in your date field as July2019.

More information on the Format function and syntax can be found on the Microsoft Office Support site.

Please feel free to contact me or comment if there are other short tutorials/how-to articles you would like to see. I’d love to help you out.

If I helped you, please consider leaving a tip via PayPal to support the blog! Thanks!!

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Things I Have Learned – LPT Episode #1

Greetings, dear friend! Welcome to the very first installment of the “Things I Have Learned” series!  I am so excited to document and share some of the many things I am so fortunate to learn as I journey through this life.

The subject matter will vary – I consider myself a pretty well rounded person – meaning I have a wide range of interests and hobbies.  I am also quite passionate about my work and continuing to grow in that capacity, so naturally some of the LPT (Life Pro Tip) items I share may be technical in nature. Some of what I share may be silly as I’m known for being a bit of a comedian at times. 🙂

I hope that the items I share help you, and I would love to hear feedback from you.  Also, if you have something you would like to share with other readers, please don’t hesitate!

Without further ado, behold this first installment!

Lightning/Storms

If you’re ever caught outside in a thunderstorm and you suddenly feel your hair stand on end, squat as low to the ground on the balls of your feet as possible. Place your hands over your ears and your head between your knees. Make yourself the smallest target possible and minimize your contact with the ground.  Getting struck by lightning has always been a big fear of mine (hopefully irrational)!

SaverLife

SaverLife is an awesome organization that will pay rewards to you if you meet your savings goals (as of 5/29/19).  It appears that they (“EARN”) are a non-profit and there are several useful articles related to personal finance on their website.  I signed up last year and received $60 from them over the course of six months.  Note: This is not an affiliate offer and I have nothing to personally gain if you sign up. Just some free money and great tools/educational material surrounding budgeting and saving for the future. Check it out!

 

Introducing the Things I Have Learned Series (LPT)

Every day I am so fortunate to learn new things about others, the world, myself and so on.  I’ve decided that I’d like to start sharing some of that with you and the world.

Sometimes it’s some small fact, other times it’s something somewhat obvious that pretty much everyone else seemingly already knows.

I hope you enjoy the Things I Have Learnedseries, and I welcome your feedback and additions to this little knowledge base!