# Power BI dashboard for data science survey results

**Tools:** Microsoft Excel, Microsoft Power BI

**Keywords:** HR, data professional, data visualizations, data cleaning

<figure><img src="https://539050446-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FW65tN1jweulcjF26J7LM%2Fuploads%2F8Zl0PjRengaDmz54cQZz%2FData%20Professionals.jpg?alt=media&#x26;token=9fe42650-9aaa-4c87-b11d-0308f86ad6ed" alt=""><figcaption></figcaption></figure>

Data-related job position has been in high demand for quite a while now, and is expected to be in even higher demand in the coming future. With the ever growing of talented data professionals by companies and small business, a thorough, easy-to-read salary survey is necessary for HR managers to manage the work condition and satisfactory level of employees working in data-related position.

This project aims to use a real world HR data professional survey dataset, and build a informative dashboard that provides easy-to-understand, informative dashboard using Microsoft Power BI.

## Data cleaning

We first examine the dataset and drop all unnecessary columns.

<figure><img src="https://539050446-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FW65tN1jweulcjF26J7LM%2Fuploads%2FxlnI899LnbcJokXm0Hih%2FScreenshot%202025-12-24%20100810.png?alt=media&#x26;token=0cb281ca-533c-4119-b72a-f75af06dc6db" alt=""><figcaption></figcaption></figure>

> Original dataset before cleaning

<figure><img src="https://539050446-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FW65tN1jweulcjF26J7LM%2Fuploads%2FuSNnYb2XCRBIc28Y3AMp%2FScreenshot%202025-12-24%20101641.png?alt=media&#x26;token=3457d350-44f5-48dc-b8b3-549d4ad7fa89" alt=""><figcaption></figcaption></figure>

> Cleaned dataset using Power Query Editor in Microsoft Power BI

By using the Power Query Editor in Power BI, we identified columns that were entirely emptied were irrelevant to our dashboard. These columns were dropped using the Power Query Editor as well.

Also, we examined the columns for any data in irregular patters (e.g. the "Other" categories answered by survey respondents who also provide their own response in a seperated textbox), and standarized their data for the viewers' easier comprehension of the survey results.

## Dashboard

<figure><img src="https://539050446-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FW65tN1jweulcjF26J7LM%2Fuploads%2FkNMU7MMEkHrXM9UowGmd%2FScreenshot%202025-12-24%20111638.png?alt=media&#x26;token=0d371620-396d-4455-8176-79f271ba3dcd" alt=""><figcaption></figcaption></figure>

After cleaning and standardized the data using Power Query Editor, we build the dashboard and create different charts to present the survey results according to the type of response.

You may find the dataset and the files by visiting this [GitHub repository](https://github.com/cedricyu000925/Getting-to-know-more-about-data-science-Creating-a-Power-BI-Dashboard?tab=readme-ov-file).