Today’s dashboard task was to analyse data for videos that trended on youtube in the last year and a half. The trending video’s data was from Kaggle (https://www.kaggle.com/rsrishav/youtube-trending-video-dataset). I used this data to create a dashboard with the aim to identify what makes a video trend how anyone can create a trending video.
Firstly, I had to join the data in Alteryx. There was data from 11 countries but I decided to use data from only the English-speaking country due to the foreign symbols in video titles. In alteryx, I parsed out the category names from the json file using the 6 steps found (here). I replaced these values back in the original dataset and joined the three countries together. Here is what the Alteryx workflow looked like. 
The next step was Tableau. I wanted to analyse how the top channels of each category were able to get so many of their videos onto the featured page of youtube. After filtering to the top channels I decided to look at a few ratios; like-dislike, comment-views, and like-views. By comparing how each of these ratios ranked against the number of days in which each video trended, we are able to gain insights on which metric is most important.
Here is what the dashboard looks like. 
