Given that I am completing a tutorial series of data analytics dashboards by various authors on YouTube, and my objective is to review, potentially include in my portfolio, and write a Medium story about these top dashboard tutorials, I have chosen to do an individual repository for each project and a combined one approach. The reasons are as follows.
- Organization: I will create individual repositories for each tutorial to maintain a clear organization.
- Specific Feedback: I can provide specific feedback and insights for each tutorial in its dedicated repository, making it easier for users to find information related to a particular video.
- Project Overview: I am able to maintain a combined repository that serves as an overarching project, summarizing your experience across all tutorials.
- Portfolio Inclusion: If I plan to showcase a completed tutorial in your portfolio, a combined repository will provide a holistic view of my dashboard creation skills. This approach allows me to have the best of both worlds, providing dedicated spaces for detailed feedback on each tutorial while offering an overall project summary in a single repository. It also aligns well with my goal of creating a Medium story about my top dashboard tutorials, as you can reference both the individual repositories and the overarching project in your storytelling.
Embark on a hands-on journey with me as I delve into five succinct YouTube video tutorials, each designed to be completed in 45 minutes or less. This immersive exercise aims to assess the accessibility and user-friendliness of dashboard creation tools by following along with diverse tutorials. From mastering data visualization to crafting interactive dashboards, the goal is to gauge the efficiency of each tutorial and the overall experience in completing the projects. Join me on this exploration as I share insights, challenges, and triumphs in the realm of dashboard creation. The GitHub Readme will serve as a comprehensive guide, offering a glimpse into the world of quick and practical tutorials, providing both newcomers and seasoned users with valuable perspectives on the ease of implementation for each tutorial and the project as a whole.
Navigating Mo Chen's YouTube tutorial was a comprehensive and instructive experience, resulting in the successful completion of the project within approximately three hours. While the timeframe exceeded my initial expectations, it was a minor trade-off for the clarity and precision of Mo's instructions. Unlike my usual self-learning courses on platforms like Udemy or Coursera, Mo's tutorial showcased a polished and concise teaching style. The absence of unnecessary personal opinions allowed for a streamlined learning process. Understanding the rationale behind each step was virtually problem-free, and Mo's meticulous guidance ensured a smooth execution. Considering the tutorial's effectiveness, I'm inclined to revisit the project, experimenting with different datasets and customizations to further enhance my Tableau skills.
- Here is the link to Mo Chen's YouTube tutorial for the "British Airways Review" dashboard project: https://www.youtube.com/watch?v=KlAKAarfLRQ
Embark on a rapid journey into data visualization with the DataScience RoadMap's Tableau tutorial, crafting a Netflix dashboard in under 30 minutes. This concise yet comprehensive tutorial provides clear insights and practical guidance, ensuring swift mastery in Tableau dashboard creation. Navigating through the DataScience RoadMap tutorial proved to be a smoother experience compared to Mo Chen's "British Airways Review" dashboard tutorial though I would say both are equal in value. Despite similar video lengths and instructional depth, the ease of understanding this tutorial was notably higher. Both tutorials, however, share a common omission in detailing the ETL (extract, transform, load) process for dataset acquisition. While this is a minor tradeoff for a more direct project approach, a welcome addition would be insights into their dataset or project selection process, an aspect currently lacking in the tutorials. A glimpse into their decision-making could provide valuable context for learners, enhancing the overall learning experience. Access the starter files via the provided link and elevate your data visualization proficiency, navigating the world of dynamic and impactful dashboards with efficiency and engagement.
- A link to DataScienc RoadMap's YouTube tutorial for this Netflix dashboard project: https://www.youtube.com/watch?v=KlAKAarfLRQ
The iDATA Analytics Hub's Excel Dashboard tutorial presented a unique learning experience, diverging from the previous two tutorials. With a duration akin to Mo Chen's tutorial, clocking in at around three hours, it required a bit more effort due to the absence of live narration. The lack of verbal guidance resulted in occasional setbacks, making the process slightly more intricate and time-consuming. Nonetheless, the tutorial's reliance on text prompts with pointers facilitated navigation through Excel's workspace. Despite this not being my preferred learning style, it proved effective. Surpassing the other two in satisfaction, this is largely attributed to my familiarity with Excel over Tableau. iDATA Analytics Hub's extensive course offerings hint at their expertise, and though I had to navigate a couple of hurdles independently, the overall experience was enjoyable.
- A link to iDATA Analytics Hub's YouTube tutorial for this Adidas dashboard project: https://www.youtube.com/watch?v=-qt_nFudQkY&t=453s