💻 We are pulling data from Kaggle, exploring and analysing it in Excel, cleaning and testing it in SQL, and visualizing it in Power BI. Follow along at your own pace - feel free to drop any questions or feedback you have in the comments below.
📩 Join my community here:
- https://data100.carrd.co/
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Become a data analyst using Analyst Builder here -
https://www.analystbuilder.com/?via=stephen-david-williams
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📲 Socials:
- TikTok - https://www.tiktok.com/@sdw.online
- LinkedIn - https://www.linkedin.com/in/stephen-david-williams-860428123/
- GitHub - https://github.com/sdw-online
- Twitter/X - https://twitter.com/sdw_online
- Instagram - https://instagram.com/sdw.online
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🎁 Free Resources:
Here are some of the free resources I’ve created that you may find useful for your own data projects:
* My articles/ blogs - https://medium.com/@sdw-online
* My newsletter - https://datainsights.beehiiv.com/subscribe
* My templates & guides (coming soon, feel free to ask me for them!!!)
Here are some of the resources used in this project:
- Kaggle (Dataset) - https://www.kaggle.com/datasets/bhavyadhingra00020/top-100-social-media-influencers-2024-countrywise?resource=download
- GitHub repo - https://github.com/sdw-online/top_uk_youtubers_2024
- My portfolio website (made in this project) - https://sdw-online.github.io/top_uk_youtubers_2024
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📩 Installation links:
Download these resources mentioned in the project:
- SSMS - https://learn.microsoft.com/en-us/sql/ssms/download-sql-server-management-studio-ssms?view=sql-server-ver16
- Power BI - https://powerbi.microsoft.com/en-us/downloads/
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🎶 Music used:
Morning Routine by Ghostrifter Official | https://soundcloud.com/ghostrifter-official
Music promoted by https://www.chosic.com/free-music/all/
Creative Commons CC BY-SA 3.0
https://creativecommons.org/licenses/by-sa/3.0
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⏲️ Timestamps:
- Introduction (
00:00:00)
- Pipeline architecture (
00:01:29)
- Stages of the project (
00:02:33)
- Objective (
00:06:21)
- Create the requirements (
00:08:30)
- Design the dashboard (
00:13:11)
- Get data from Kaggle (
00:17:39)
- Explore the data (
00:18:41)
- Import into SQL (
00:21:45)
- Clean data with SQL (
00:24:54)
- Create SQL view (
00:36:37)
- Test data (
00:38:40)
- Import into Power BI (
00:53:00)
- Create DAX measures (
00:55:10)
- Build the visuals (
01:07:52)
- Create the table visual (
01:08:34)
- Create the tree map visual (
01:11:46)
- Create the scorecards (
01:14:48)
- Create the bar chart (
01:17:43)
- Clean up the dashboard (
01:08:34)
- Set up GitHub Pages (
01:28:57)
- Create an ‘assets’ folder (
01:30:43)
- Create a ‘_config.yml’ file (
01:36:53)
- Enable GitHub Pages (
01:38:13)
- Edit ‘README.md’ file (
01:39:39)
- Change theme of portfolio website (
01:41:17)
- Create Excel analysis workbook (
01:45:28)
- Calculate potential ROI in Excel (
01:53:32)
- Validate calculations in SQL (
02:01:28)
- Define variables in SQL (
02:04:00)
- Create a CTE (
02:05:53)
- Create calculated columns in SQL (
02:11:54)
- Sort SQL results by net profit (
02:17:00)
- Create a ‘difference’ table in Excel (
02:18:50)
- Populate remaining columns in Excel (
02:23:05)
- Format Excel analysis workbook (
02:24:37)
- Analyse the data (
02:25:57)
- Add recommendation to Excel workbook (
02:29:46)
- Overview of GitHub portfolio website (
02:32:55)
- Update GitHub portfolio via ‘README.md’ file (
02:36:01)
- Add headers (
02:36:41)
- Add table of contents (
02:37:53)
- Add images (
02:38:48)
- Add code blocks (
02:39:23)
- Add markdown tables (
02:40:09)
- Find markdown cheat sheet (
02:41:58)
- Closing announcements (
02:44:13)