NETFLIX ANALYSIS(project 2 and experience)

NETFLIX ANALYSIS(project 2 and experience)

On this week's edition of data analysis, it was a bit tasky because we had to move from one dataset given initially to a new one in the middle of the week and that was the new given dataset from Netflix.

We decided to embark on the journey, mind you the objectives that were given to achieve from the project looked and seem easy but weren’t actually, and that made it hard.

we decided to start the research on Netflix and it was hard to find so much information online especially thinking it is Netflix, the dataset given was also very limited in the real sense but we had to come up with something.

It was discouraging because we didn't think we could achieve the assignment at first but let me say at this junction, I have the best team ever, we slept on the project and when we eventually had our first session, we started dissecting the project gradually and to think along the line we discovered we could do more with the dataset

So, we started dropping ideas and started jotting down possible solutions to the objectives still it was a little difficult but my team came through for some of the objectives to be achieved, though we looked outside the box also.

In the cause of this whole process of having sessions, we also had members who became busy by the virtue of other assignments (exams), which also reduced manpower and ideas but they never stopped checking and dropping their ideas also.

in the middle of everything we got to the stage where we had to start all over again because we weren’t getting the desired result, but we had to reach a consensus which helped us.

We started tying down the possible solutions and yeah everyone was cooperative with it as I designated tasks for some of the members of the team which aided ease of the work.

Eventually, we concluded the project and breathe a little (smile).

Based on the objectives of the project,

LIMITATIONS

The data set did not contain the number of views for each production; hence the analysis of the most popular show was based on production data.

RECOMMENDATIONS

Based on the insight from the analysis Movie production is nearly three times higher than TV shows.

However, TV shows have seen a significant increase in production in recent years of analysis. Productions rated TV-MA and TV-14 are in good standing in both Movies and TV Shows.

Based on the above it is recommended that Movies continue to take a significant chunk of the investment with a lot more focus on TV-MA, TV-14 and R-rated content, while it maintains a steady increase for TV Shows, especially the Kid's TV category.