Dashboard Bake-Off!

[jordan.zenko]

Time to put those dashboarding skills to good use!

We recently released a new blog, titled Exploring Hidden Relationships Within Netflix’s Original Content

In this blog, I compiled publicly available data on Netflix’s original content (genre, title, premiere date, seasons, etc.) and visualized it as a Relationship Diagram. This was the final result:

Now, being the data visualization guru’s you are, I’m sure you can do much better than myself!

So it’s your turn to shine! I want you to take the data I used, and see if you can come up with different conclusions! You can use any type of data visualization you want!

If you didn’t download the data set from the challenge, you can do so here:

https://www.dropbox.com/s/i7gewwas6l81x3o/Netflix_Original_Series_2013_2017%20%285%29.xlsx?dl=0

Here’s what’s on the line:

1. I’ll award 300 points for every data visualization I receive (take a screen shot and post it below), as long as it’s different than mine
2. It would be great if you included a couple of sentences, highlighting the conclusions you were able to come to as well
3. Our favorite visualization will be featured in a follow-up blog (full credit to you!)

So let’s see those visualizations!

[luis.silva]

The conclusion from the above histogram is that Netflix production in terms of episode duration is basically focused on short term duration, from 20 to 40 minutes. By taking a closer look, we can perceive that 20-40s bin represents a percentage over 50% of all titles!

[colin.michael]

Okay, time for Netflix execs to assess the new batch of Originals launched this year and decide what shows to cut and what to keep. Yes, they're making money overall, but money is never unlimited, so something has to go so that we can fund some new show ideas. Here is just ONE consideration, the IMDB scores of the shows. If they fall below our arbitrary goal of 75 then they get the critical eyeball from the brass and the bean counters. We've included the number of episodes for each show, just to be sure we're comparing apples to apples. Hey, even a slow starter deserves a chance to dance.

This is a one-time use metric, so I'm glad it only took a few minutes to put together using Dundas BI!

[mohammad.qasim]

I used Sanky Diagram to see the releation between year and major Genre, with using the number of Episodes for highlighting the width and IMDB for highlighting he score, As a result it is clearly shown that

1. 2015/2017 was the highest year in producing highest IMDB series

2. Family aniamation series is highest in the number of episodes, even with less IMDB scores in general.

3. 2017 concentrates on new generation of series.

4. forget to see any comedy series after 2014 :(

[elmar.hulshof]

I wanted to see which major genres would get the best scores on IMDB after that I wanted to see what the scores where of the subgenres. To get a overview I used a treemap where I used the IMDB rating for the size and color. This way you can see a clearer difference within the major genres except for the major genre Drama which has similar scores. But at the docu-series, reality, femily live action and comedy the differences are clear. In a dashboard you could also change the year (+1) every 30 seconds so you could see if scores between the genres is changing over time.

[mark.josephson]

I created a calculated measure that averaged the IMDB rating across all genres and set that as the baseline. Then I plotted the average IMDB rating by major genre and number of pending shows against the respective ratings.

Interestingly, the major genres with the greatest number of pending shows also have average IMDB ratings that are closest to the overall average implying that the company is focusing their efforts on the major genres that have the widest appeal.

[devbyrd (Devon Byrd)]

This completely useless* insight attempts to correlate the month in which a series premiered to the IMDB rating. It looks like if you are a writer you'd prefer to keep your job longer by having your show premiere in the middle of summer... however, if you are Netflix and REALLY care about IMDB ratings, then you should premiere shows in late spring to early summer. DEFINITELY avoid January and August though... people don't rate those shows very highly, relatively speaking.

*I said this is useless because I was seeing if I could find a random correlation and there obviously isn't anything super helpful here. If that wasn't obvious... didn't want anyone to think I thought this exercise was useless.

[james.davis]

I wanted to know what was pending, renewed, ended, ongoing and not known by genre and title.

The link Length is on Episodes and width on IMDB rating.

The Node Size is IMDB Rating and color by status. I wanted to make the first node color code only for status then its children color by genre but could figure that out.

I know isued a relational Digram but I did look at the data differently to answer different questions or at lest shown it from a different perpective.

[tim.carpenter]

This dashboard allows us to move data between multiple systems. Each button click either deletes data form tables using stored procedures or moves data from one table to another using the same stored procedure.

[utsav.kale]

I wanted to see the status of all ongoing netflix project based on genres and further drill down to titles.

Majority of the projects are in pending or renewed status.

Also concern would be the projects with NA status.

[thomas (Thomas Tucha)]

Tried to find out, if there is a coherence between major genre / sub-genre and average minimum and maximum episode length. One can group the subgenres into 3 or 4 clusters.