The total amount of data created, captured, copied, and consumed globally is forecast to increase rapidly, reaching *** zettabytes in 2024. Over the next five years up to 2028, global data creation is projected to grow to more than *** zettabytes. In 2020, the amount of data created and replicated reached a new high. The growth was higher than previously expected, caused by the increased demand due to the COVID-19 pandemic, as more people worked and learned from home and used home entertainment options more often. Storage capacity also growing Only a small percentage of this newly created data is kept though, as just * percent of the data produced and consumed in 2020 was saved and retained into 2021. In line with the strong growth of the data volume, the installed base of storage capacity is forecast to increase, growing at a compound annual growth rate of **** percent over the forecast period from 2020 to 2025. In 2020, the installed base of storage capacity reached *** zettabytes.

Here are a few use cases for this project:

1. Optical Character Recognition: This model can be employed to digitize printed or hand-written documents by recognizing characters in images. It will enable searchability, editing, and easy sharing of physical texts—even in situations when direct scanning isn't possible.

2. Automated License Plate Recognition: The model can be applied in traffic control units to automatically read license plates in images or video footage. This would be helpful in tracking stolen vehicles, monitoring traffic violations, and managing parking.

3. Educational Tools: The model can be used to develop educational applications for children. Such as an interactive game app where children are required to identify letters and numbers in various images, helping them to learn and recognize characters better.

4. Assistive Technology: In aiding visually impaired individuals, the model can interpret text in real-world images, converting the recognized letters and numbers into audio output.

5. Inventory Management: It can help in recognizing and classifying alphanumeric codes on inventory items in a warehouse, assisting in better tracking and management of stock.

description: The Global Database of Events, Language, and Tone (GDELT Project) monitors the world's broadcast, print, and web news from nearly every corner of every country in over 100 languages and identifies the people, locations, organizations, counts, themes, sources, and events driving our global society every second of every day, creating a free open platform for computing on the entire world. It was uploaded via the World Wide Human Geography Data (WWHGD) working group.; abstract: The Global Database of Events, Language, and Tone (GDELT Project) monitors the world's broadcast, print, and web news from nearly every corner of every country in over 100 languages and identifies the people, locations, organizations, counts, themes, sources, and events driving our global society every second of every day, creating a free open platform for computing on the entire world. It was uploaded via the World Wide Human Geography Data (WWHGD) working group.

Context

The novel coronavirus that has infected more than 79,551 people worldwide (as of time of writing this context) is spreading rapidly, and independently, in countries outside of China, including Italy, South Korea, and Iran. The viral illness is being diagnosed among hundreds of people in South Korea, Italy and Iran who have no connection to China.

Content

In the notebook I use the time series data. Time series data columns are described in the column description.

Acknowledgements

Thanks to the Johns Hopkins University for providing this data-set for educational purposes. https://github.com/CSSEGISandData/COVID-19

Inspiration

To visualize COVID-19 spread world wide.