Drishyam

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  Country-wise Data

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  Time Series Analysis

Inspiration

We wanted to work on a dataset that was out of league yet helped address a major cause in Southern Asia. Also, we wanted to work with various AWS services available for visualization purposes. It was then that we came across Devpost's AWS Data Exchange Challenge, and we agreed to take part in it.

What it does

This is a Data visualization project , named Drishyam , on gender equality in entrepreneurship, which shows the details about the changes in gender ratio in entrepreneurship over a span of time (1976-2019) in various countries.

How we built it

We build it using five AWS services :

1. AWS Data Exchange
2. Amazon S3
3. AWS Glue
4. AWS Athena
5. AWS QuickSight

Challenges we ran into

We had never work with AWS Data Exchange and had no clue how to go about visualizing data obtain from AWS Data Exchange. Working remotely was also a challenge in itself, the work that could have been done within a day or so took longer than usual.

What we learned

We learned how to work remotely. We learned how to use following services :

1. AWS Data Exchange
2. AWS Glue
3. AWS Athena
4. AWS QuickSight

Built With

• amazon-web-services
• athena
• aws-data-exchange
• awsquicksight
• glue
• s3