Abstract In the world of social media, we are subjected to a constant overload of information. Of all the information we get, not everything is correct. It is advisable to rely on only reliable sources. Even if we stick to only reliable sources, we are unable to understand or make head or tail of all the information we get. Data about the number of people infected, the number of active cases and the number of people dead vary from one source to another. People usually use up a lot of effort and time to navigate through different websites to get better and accurate results. However, it takes lots of time and still leaves people skeptical. This study is based on webscraping & web-crawlingapproach to get better and accurate results from six COVID-19 data web sources.The scraping script is programmed with Python library & crawlers operate with HTML tags while application architecture is programmed using Cascading style sheet(CSS) &Hypertext markup language(HTML). The scraped data is stored in a PostgreSQL database on Heroku server and the processed data is provided on the dashboard.