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Timileyin Ikumapayi
Timileyin Ikumapayi

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Amazon QuickSight for Data Visualization on Streaming Platforms: A Netflix Case Study

What is Amazon QuickSight?
Amazon QuickSight is a cloud-powered business intelligence (BI) and data visualization service offered by AWS. It allows users to easily create and analyse interactive dashboards, reports, and visualizations from various data sources.

How I used Amazon QuickSight in this project

I used it to visualize Tv shows and Movies from Netflix based on some of the grouping and labels from the dataset available. I represented those data in different graphs and tables of my choice.

One thing I didn’t expect in this project was…

I did not expect for it to be as fun and tasking. It took longer than expected because of the filter and many options to pick from.

This project took me…

I spent almost 2 hours on it.

Upload project files into S3
My S3 bucket here is used in this project to store two needed files, which are the manifest.JSON and netflix.csv file

I created the bucket, using all the default settings and named it “network-quicksight-timi”

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You can downloaded the files here (Link)

I uploaded both files to the bucket, selected Netflix file and Copied its Object URL, then I edited the manifest.JSON file by opening it in my Notepad and updating the URL with the one copied from my bucket. It’s important to edit this file because you want to get the document to point to the right URL.

Create QuickSight account
Creating a QuickSight account cost nothing, it is totally free to create the account, you only pay for services used.

Creating an account took me about 10 minutes as there are some vital steps that are needed to be done carefully

I searched for QuickSight and Signed up for a free trial of the Enterprise edition.

There are a couple of things to note whilst creating a QuickSight account:

  1. Make sure to Uncheck the Add Paginated Reports checkbox so your AWS does not get charged.

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  1. Ensure the email used is the same as the email on your AWS Account.

  2. Make sure to select Amazon s3, adding the right bucket that was created earlier.

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Now I have successfully created a QuickSight account

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Download the Dataset
I connected the S3 bucket to QuickSight by visiting the dataset section, clicking on S3 and filling the needed boxes.

From the left hand navigation bar, I selected Datasets, then New dataset.. Select S3.. For the first field (source name), enter kaggle-netflix-data. I opened a new tab in my browser and navigated to my AWS management console and went to the s3 bucket I created, selected the manifest object and copied the object’s URL. Then, I moved back to the QuickSight page and pasted the URL I just copied and select Connect.

The manifest.JSON file was important in this step because it is like a map that helps in connecting Quicksight to the S3 bucket and tells QuickSight how to present and visualise the data from the dataset.

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My first visualization
To create visualizations on QuickSight, I would need to paste the correct object URL to the manifest.JSON file and select the graph I want and how I want it to visualise the available fields and grouping.

With QuickSight, you can sort, filter, and customise your data top create visualisations. You can also experiment with different types of graphs like bar charts, pie charts, line graphs, etc.. You can see on the left hand panel that the dataset’s fields are already imported.

To create my first visualization, I dragged Release_year into the Y-Axis heading. Now I can see a breakdown on the year that these Netflix-featured TV shows and movies were released

To create a new visual, I selected + ADD under the Visuals heading on my middle navigation bar, and another blank frame pop out.

So I can see a breakdown of TV shows vs movies for every year, I dragged the release_year label into the Y Axis heading. Next, I dragged the type label into the Group/Color heading.

The donut chart (a type of pie chart) shown below is a breakdown of the release year of Netflix shows while the bar chart shows the records by the Release_year and the type of the Netflix shows.

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Using filters
Filters are useful for showing the exact grouping and records you would like to see from the dataset.

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An Image showing The Fields that can be used to filter the data.

This visualization is a breakdown of the TV shows and movies with the listing ‘Action & Adventure’, ‘TV Comedies’, or ‘Thrillers’, how many were released on 2015 or after. Here I added a filter by selecting Release_year (2015–2021) and Genre (Action & Adventure, TV Comedies and Thrillers).

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Setting up a dashboard
As a finishing touch, I edited the title of the graphs individually and then I adjusted the size by going to the top right and choosing Fit to Width. Then I Published it and named the dashboard appropriately.

Did you know you could export your dashboard as PDFs too? I did this by clicking on the Export icon at the top right corner of the screen and chose Generate PDF, then the site did its magic and my dashboard was ready to be downloaded as PDF.

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Here are some of the questions the remaining graphs on my dashboard are answering.

· A breakdown of TV shows/movies for each release year. Would it be possible to stack movies and TV shows in the same row, so you can visualise the % of each?

· Now can you show me the same thing in a table? i.e. please show me the number of movies vs TV shows per release year in a table.

· On what day did Netflix add the largest number of movies/TV shows to their catalogue

· Of the TV shows and movies featured, how many were listed as ‘Action & Adventure’, ‘TV Comedies’, or ‘Thrillers’? For simplicity, ignore the TV shows and movies that have multiple listings/categories

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